Uniqueness Analysis.ipynb

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   "source": [
    "import os\n",
    "import shutil\n",
    "import pandas as pd\n",
    "from pyspark.sql.functions import *\n",
    "from pyspark.sql.types import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "75ae362f-7ad2-43bf-be97-7e28ff5365d0",
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: nltk==3.7 in /opt/conda/miniconda3/lib/python3.8/site-packages (3.7)\n",
      "Requirement already satisfied: click in /opt/conda/miniconda3/lib/python3.8/site-packages (from nltk==3.7) (7.1.2)\n",
      "Requirement already satisfied: regex>=2021.8.3 in /opt/conda/miniconda3/lib/python3.8/site-packages (from nltk==3.7) (2022.10.31)\n",
      "Requirement already satisfied: joblib in /opt/conda/miniconda3/lib/python3.8/site-packages (from nltk==3.7) (1.2.0)\n",
      "Requirement already satisfied: tqdm in /opt/conda/miniconda3/lib/python3.8/site-packages (from nltk==3.7) (4.64.1)\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
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    {
     "data": {
      "text/plain": [
       "True"
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     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "!pip install nltk==3.7\n",
    "import re\n",
    "from pyspark.ml.feature import MinHashLSH\n",
    "from pyspark.ml.feature import CountVectorizer,  IDF, CountVectorizerModel, Tokenizer, RegexTokenizer, StopWordsRemover\n",
    "import nltk\n",
    "from nltk.corpus import stopwords\n",
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "db06a579-588e-4046-b8b1-28eb8ed132b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql.functions import monotonically_increasing_id, row_number\n",
    "from pyspark.sql.window import Window\n",
    "pd.set_option(\"display.max_colwidth\",None)\n",
    "from google.cloud import storage\n",
    "from pyspark.sql import Row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7ff2718b-6e75-49fb-abc5-4160809c7f97",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "spark = SparkSession.builder.getOrCreate()\n",
    "spark.conf.set(\"spark.sql.repl.eagerEval.enabled\",True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a45abdf5-315a-465e-a4ad-b4773facbb03",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:28:32 WARN org.apache.spark.sql.catalyst.util.package: Truncated the string representation of a plan since it was too large. This behavior can be adjusted by setting 'spark.sql.debug.maxToStringFields'.\n"
     ]
    }
   ],
   "source": [
    "tw_df=spark.read.parquet('gs://msca-bdp-students-bucket/shared_data/kishorkumarreddy/Final_Project-100millionFilterHashtag')\n",
    "#path: msca-bdp-students-bucket/shared_data/kishorkumarreddy/Final_Project-100millionFilterHashtag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5ebe1818-12cf-4076-97d0-0c5413bbb529",
   "metadata": {},
   "outputs": [],
   "source": [
    "tw_df.createOrReplaceTempView(\"tw_df\")\n",
    "query = '''select tweet_text as text,\n",
    "retweeted_status.id as rt_object_id,\n",
    "user.description as desc\n",
    "from tw_df'''\n",
    "tw_Q4 = spark.sql(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c8cd07f6-98f0-4c9d-bb0f-3dce5f4a9bdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "tw_Q4 = tw_Q4.sample(0.025)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c04893d6-6b4c-4c47-b522-029c24463851",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 1:>                                                          (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+-------------------+--------------------+------+----------+\n",
      "|                text|       rt_object_id|                desc|   org|tweet_type|\n",
      "+--------------------+-------------------+--------------------+------+----------+\n",
      "|massive protests ...|               null|Follow http://ind...|  news|     tweet|\n",
      "|real story about ...|1571340634820325377|Nationalist, हिंद...|Others|   retweet|\n",
      "|real story about ...|1571340634820325377|    Savage/sweetness|Others|   retweet|\n",
      "|she sucked her be...|1570601230287900682|                null|Others|   retweet|\n",
      "|#justice_for_maga...|1570014495350886401|                null|Others|   retweet|\n",
      "|#justice_for_maga...|1570014572572180480|                null|Others|   retweet|\n",
      "|#justice_for_maga...|1570014309564174340|                null|Others|   retweet|\n",
      "|#justice_for_maga...|1570014207701286912|      I am a student|Others|   retweet|\n",
      "|#justice_for_maga...|1570013849767804930|                null|Others|   retweet|\n",
      "|@pennlaw @dorothy...|               null|  یک سینیور اورتینکر|Others|     tweet|\n",
      "|let go of student...|1576709566951137280|                null|Others|   retweet|\n",
      "|#justice_for_maga...|1570024669234991105|                null|Others|   retweet|\n",
      "|#justice_for_maga...|1570016515143135233|                null|Others|   retweet|\n",
      "|on #worlddisabili...|1599437809819193344|                null|Others|   retweet|\n",
      "|let go of student...|1576709566951137280|   هم رنگ واقعیت ...|Others|   retweet|\n",
      "|let go of student...|1576709566951137280|علاقمند به فوتبال...|Others|   retweet|\n",
      "|let go of student...|1576709566951137280|                null|Others|   retweet|\n",
      "|let go of student...|1576709566951137280|                null|Others|   retweet|\n",
      "|let go of student...|1576709566951137280|                null|Others|   retweet|\n",
      "|let go of student...|1576709566951137280|#مهسا_امینی\n",
      "#mahs...|Others|   retweet|\n",
      "+--------------------+-------------------+--------------------+------+----------+\n",
      "only showing top 20 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "tw_Q4 = tw_Q4.withColumn(\"org\",when(col(\"desc\").rlike('.*government.*|.*Government.*|.*minister.*|.*Minister.*|.*gov.*'),\"gov\")\n",
    "                         .when(col(\"desc\").rlike('.*University.*|.*university.*|.*school.*|.*School.*'),\"edu\")\n",
    "                         .when(col(\"desc\").rlike('.*News.*|.*news.*|.*Media.*|.*media.*'),\"news\")\n",
    "                         .when(col(\"desc\").rlike('.*nonprofit.*|.*Nonprofit.*|.*NGO.*|.*aid.*'),\"ngo\")\n",
    "                         .when(col(\"desc\").rlike('.*influencer.*|.*Influencer.*'),\"influencer\").otherwise('Others'))\n",
    "tw_df1 = tw_Q4.withColumn(\"tweet_type\",when(col(\"rt_object_id\").isNull() != True,\"retweet\").otherwise(\"tweet\"))\n",
    "tw_df1.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ab95967c-f442-43e0-8480-27921622cc5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 2:>                                                          (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+------------+-------------------------+------+----------+\n",
      "|                text|rt_object_id|                     desc|   org|tweet_type|\n",
      "+--------------------+------------+-------------------------+------+----------+\n",
      "|massive protests ...|        null|     Follow http://ind...|  news|     tweet|\n",
      "|@pennlaw @dorothy...|        null|       یک سینیور اورتینکر|Others|     tweet|\n",
      "|@cnnbrk in front ...|        null|스티와 아미 💜We are t...|Others|     tweet|\n",
      "|my boobs were so ...|        null|     24 yr ✰ bisex (no...|Others|     tweet|\n",
      "|it's that time of...|        null|     Official Twitter ...|Others|     tweet|\n",
      "|@harvard we need ...|        null|                     null|Others|     tweet|\n",
      "|freaky teen eatin...|        null|     main @pyttingz de...|Others|     tweet|\n",
      "|@harvard in front...|        null|     هرچی که توی مغزمه...|Others|     tweet|\n",
      "|@eunoiavirago_ be...|        null|     یک عدد دانشجو که ...|Others|     tweet|\n",
      "|the #everyonesinv...|        null|     A real-time repor...|Others|     tweet|\n",
      "|see our latest le...|        null|     Follow this accou...|Others|     tweet|\n",
      "|bravo to the iran...|        null|     Actor. Writer. Pr...|Others|     tweet|\n",
      "|can you say #stup...|        null|     Old white man tha...|Others|     tweet|\n",
      "|@whcos @jod46 the...|        null|                     null|Others|     tweet|\n",
      "|@tedcruz @mayrafl...|        null|     silence the world...|Others|     tweet|\n",
      "|@golshifteh @guar...|        null|                     null|Others|     tweet|\n",
      "|#cycletoschoolwee...|        null|     Cheshire West and...|  news|     tweet|\n",
      "|2 day 11 hrs an 5...|        null|     insta: @ paulina....|Others|     tweet|\n",
      "|@nazaninboniadi t...|        null|       صبح میشه این شب 🜚|Others|     tweet|\n",
      "|@mime_1999 the st...|        null|     ??! 15 years old ...|Others|     tweet|\n",
      "+--------------------+------------+-------------------------+------+----------+\n",
      "only showing top 20 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "tw_df1 = tw_df1.filter(col('tweet_type') == 'tweet')\n",
    "tw_df1.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a54d27cc-7b48-4dd8-b554-bc9e1d843b16",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 3:>                                                          (0 + 1) / 1]\r"
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      "+-----------+--------------------+------------------+--------------------+--------------------+--------------------+--------------+---------+------------+----+-------------------+-------------------+-----------------------+---------------------+-------------------------+-------------------+-----------------------+---------------+----+-----+------------------+-----------+--------------------+-------------------+--------------------+-----------------------+--------------------+-----------+-------------+---------+---------------+--------------------+--------------------+--------------------+-------------+---------+--------------------+--------------------+---------------------+--------------------+\n",
      "|coordinates|          created_at|display_text_range|            entities|   extended_entities|      extended_tweet|favorite_count|favorited|filter_level| geo|                 id|             id_str|in_reply_to_screen_name|in_reply_to_status_id|in_reply_to_status_id_str|in_reply_to_user_id|in_reply_to_user_id_str|is_quote_status|lang|place|possibly_sensitive|quote_count|       quoted_status|   quoted_status_id|quoted_status_id_str|quoted_status_permalink|         quoted_text|reply_count|retweet_count|retweeted| retweeted_from|    retweeted_status|              source|                text| timestamp_ms|truncated|          tweet_text|                user|withheld_in_countries|            stripped|\n",
      "+-----------+--------------------+------------------+--------------------+--------------------+--------------------+--------------+---------+------------+----+-------------------+-------------------+-----------------------+---------------------+-------------------------+-------------------+-----------------------+---------------+----+-----+------------------+-----------+--------------------+-------------------+--------------------+-----------------------+--------------------+-----------+-------------+---------+---------------+--------------------+--------------------+--------------------+-------------+---------+--------------------+--------------------+---------------------+--------------------+\n",
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      "|       null|Sat Oct 29 18:40:...|              null|{[{[85, 92], abpo...|                null|                null|             0|    false|         low|null|1586427862793744384|1586427862793744384|                   null|                 null|                     null|               null|                   null|           true|  en| null|              null|          0|{null, Fri Oct 28...|1586019839986257920| 1586019839986257920|   {twitter.com/wing...|We’ve been losing...|          0|            0|       RT|      karleeh26|{null, Sat Oct 29...|<a href=\"http://t...|RT @karleeh26: My...|1667068851551|    false|my school haven’t...|{false, Thu Feb 2...|                 null|my school haven’t...|\n",
      "|       null|Sat Oct 29 18:40:...|          [0, 140]|{[{[73, 81], veve...|                null|{[0, 125], {[{[73...|             0|    false|         low|null|1586427862323585024|1586427862323585024|                   null|                 null|                     null|               null|                   null|          false|  en| null|             false|          0|                null|               null|                null|                   null|                null|          0|            0|         |           null|                null|<a href=\"http://t...|I've been complet...|1667068851439|     true|i've been complet...|{false, Sun Oct 1...|                 null|i've been complet...|\n",
      "|       null|Thu May 26 10:31:...|              null|{[{[32, 36], pyt}...|                null|                null|             0|    false|         low|null|1529772188341084163|1529772188341084163|                   null|                 null|                     null|               null|                   null|          false|  en| null|              null|          0|                null|               null|                null|                   null|                null|          0|            0|       RT|  kittenlove420|{null, Fri May 20...|<a href=\"http://t...|RT @kittenlove420...|1653561086150|    false|happy friday #pyt...|{false, Sun Nov 1...|                 null|happy friday pyt ...|\n",
      "|       null|Thu May 26 10:32:...|          [0, 140]|{[{[0, 15], Uvald...|                null|{[0, 280], {[{[0,...|             0|    false|         low|null|1529772343039561728|1529772343039561728|             CSojourner|  1529772338505457666|      1529772338505457666|          352848671|              352848671|          false|  en| null|             false|          0|                null|               null|                null|                   null|                null|          0|            0|         |           null|                null|<a href=\"https://...|#UvaldeMassacre #...|1653561123033|     true|#uvaldemassacre #...|{false, Thu Aug 1...|                 null|uvaldemassacre ro...|\n",
      "+-----------+--------------------+------------------+--------------------+--------------------+--------------------+--------------+---------+------------+----+-------------------+-------------------+-----------------------+---------------------+-------------------------+-------------------+-----------------------+---------------+----+-----+------------------+-----------+--------------------+-------------------+--------------------+-----------------------+--------------------+-----------+-------------+---------+---------------+--------------------+--------------------+--------------------+-------------+---------+--------------------+--------------------+---------------------+--------------------+\n",
      "only showing top 20 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "tw_df2 = tw_df1.select('org')\n",
    "tw_df.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fbb75690-8ccb-4721-bbbb-a944795cd3c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "tw_df1 = tw_df1.select('text',substring('text',1,100)).withColumnRenamed(\"substring(text, 1, 100)\",\"tweet_text\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "aaf9f674-ae77-45e5-8eff-2268be9e8658",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- text: string (nullable = true)\n",
      " |-- tweet_text: string (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "tw_df1.printSchema()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e7c4c46a-eef0-44c9-b449-48c6b9bffcd2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border='1'>\n",
       "<tr><th>tweet_text</th><th>id</th></tr>\n",
       "<tr><td>{what’s the worst...</td><td>449</td></tr>\n",
       "<tr><td>{study mbbs in pm...</td><td>450</td></tr>\n",
       "<tr><td>{thank you!!! #co...</td><td>451</td></tr>\n",
       "<tr><td>{minnesota studen...</td><td>452</td></tr>\n",
       "<tr><td>{chinese ambassad...</td><td>453</td></tr>\n",
       "</table>\n"
      ],
      "text/plain": [
       "+--------------------+---+\n",
       "|          tweet_text| id|\n",
       "+--------------------+---+\n",
       "|{we are glad to w...|508|\n",
       "|{@sportchefengren...|509|\n",
       "|{link in bio 👆👆...|510|\n",
       "|{important tips t...|511|\n",
       "|{phd position in ...|512|\n",
       "+--------------------+---+"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "body_text = tw_df1.rdd.map(lambda x : x['tweet_text']).filter(lambda x: x is not None)\n",
    "StopWords = stopwords.words(\"english\")\n",
    "row = Row('text')\n",
    "text_df=body_text.map(row).zipWithIndex().toDF(['tweet_text','id'])\n",
    "text_df.limit(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1124c94b-f847-41ab-98b1-197223364ed6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "tokens = body_text\\\n",
    "    .map( lambda document: document.strip().lower())\\\n",
    "    .map( lambda document: re.split(\" \", document))\\\n",
    "    .map( lambda word: [x for x in word if len(x) > 1] )\\\n",
    "    .zipWithIndex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5b328169-19b9-47c3-b174-ed282fcc9e68",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "df_tokens = spark.createDataFrame(tokens, [\"list_of_words\",'id'])\n",
    "#Drop records with no tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ab49001e-47c2-4723-8679-004318928dfd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tokens=df_tokens.withColumn('row_index', row_number().over(Window.orderBy(monotonically_increasing_id())))\n",
    "tw_df2=tw_df2.withColumn('row_index', row_number().over(Window.orderBy(monotonically_increasing_id())))\n",
    "\n",
    "df_tokens = df_tokens.join(tw_df2, on=[\"row_index\"]).drop(\"row_index\")\n",
    "df_tokens = df_tokens.where(col('list_of_words').getItem(0).isNotNull())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "42aef780-bda4-4809-a592-ef52cee4f5a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:30:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:30:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:35 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:35 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:38 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:38 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:38 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# countvectorize\n",
    "vectorize = CountVectorizer(inputCol=\"list_of_words\", outputCol=\"features\", minDF=1.0)\n",
    "df_vectorize = vectorize.fit(df_tokens).transform(df_tokens) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "774b516a-3b2e-4686-9e01-2bf260a52172",
   "metadata": {},
   "outputs": [],
   "source": [
    "# fit MinHashLSH for hash table\n",
    "mh = MinHashLSH(inputCol=\"features\", outputCol=\"hashes\", numHashTables=5)\n",
    "model = mh.fit(df_vectorize)\n",
    "df_hashed = mh.fit(df_vectorize).transform(df_vectorize) #.cache()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2442e2b0-d826-408d-905f-c6e85e6d2da5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hashed_text = text_df.join(df_hashed, \"id\", how = 'left') #.cache()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1f2a511-389f-4582-b0e2-9db8132c5d2f",
   "metadata": {},
   "source": [
    "# Tweet Uniqueness Graph Based on Jaccard Similarity (0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "48cf98f7-e8f1-463d-8e24-72bd5935e70f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:31:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:31:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:47 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:47 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:47 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:47 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:47 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:47 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:47 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:47 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:32:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                \r"
     ]
    },
    {
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       "      <td>0.285714</td>\n",
       "      <td>news</td>\n",
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       "      <td>2933</td>\n",
       "      <td>(@teacherinkinder @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;amp;,)</td>\n",
       "      <td>(@mrs_al_13 @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;amp; my cl,)</td>\n",
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       "      <td>(@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)</td>\n",
       "      <td>(@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)</td>\n",
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       "      <td>(@janethlovsbooks @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)</td>\n",
       "      <td>(@techmidschteach @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)</td>\n",
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       "      <th>11</th>\n",
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       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
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       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
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       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
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       "      <td>3212</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
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       "      <td>1552</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
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       "      <td>1113</td>\n",
       "      <td>1502</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>8711</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>3248</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>1552</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>1502</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>1113</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>3628</td>\n",
       "      <td>5287</td>\n",
       "      <td>(back to school with nhatthanh \\n@sontungmtp777\\n\\n#sontungmtp #theresnooneatall\\n#stanworld #backtoswsch,)</td>\n",
       "      <td>(back to school with nhatthanh \\n@sontungmtp777\\n\\n#sontungmtp #theresnooneatall\\n#stanworld #backtoswsch,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>5628</td>\n",
       "      <td>5944</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>3556</td>\n",
       "      <td>5944</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>3556</td>\n",
       "      <td>5628</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>2643</td>\n",
       "      <td>3441</td>\n",
       "      <td>(the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)</td>\n",
       "      <td>(the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>1502</td>\n",
       "      <td>1552</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     distCol     org  id_A  id_B  \\\n",
       "0   0.285714    news   767  2933   \n",
       "2   0.230769  Others   620   621   \n",
       "1   0.166667  Others  3320  8619   \n",
       "11  0.000000  Others   134  3212   \n",
       "18  0.000000  Others  1113  8711   \n",
       "17  0.000000  Others  1113  3248   \n",
       "16  0.000000  Others  1113  3212   \n",
       "15  0.000000  Others  1113  1552   \n",
       "14  0.000000  Others  1113  1502   \n",
       "13  0.000000  Others   134  8711   \n",
       "12  0.000000  Others   134  3248   \n",
       "10  0.000000  Others   134  1552   \n",
       "9   0.000000  Others   134  1502   \n",
       "8   0.000000  Others   134  1113   \n",
       "7   0.000000  Others  3628  5287   \n",
       "6   0.000000     edu  5628  5944   \n",
       "5   0.000000     edu  3556  5944   \n",
       "4   0.000000     edu  3556  5628   \n",
       "3   0.000000  Others  2643  3441   \n",
       "19  0.000000  Others  1502  1552   \n",
       "\n",
       "                                                                                                         text_A  \\\n",
       "0       (@teacherinkinder @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;,)   \n",
       "2      (@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)   \n",
       "1       (@janethlovsbooks @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)   \n",
       "11      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "18      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "17      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "16      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "15      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "14      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "13      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "12      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "10      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "9       (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "8       (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "7   (back to school with nhatthanh \\n@sontungmtp777\\n\\n#sontungmtp #theresnooneatall\\n#stanworld #backtoswsch,)   \n",
       "6                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "5                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "4                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "3       (the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)   \n",
       "19      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "\n",
       "                                                                                                         text_B  \n",
       "0       (@mrs_al_13 @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp; my cl,)  \n",
       "2      (@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)  \n",
       "1       (@techmidschteach @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)  \n",
       "11      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "18      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "17      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "16      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "15      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "14      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "13      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "12      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "10      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "9       (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "8       (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "7   (back to school with nhatthanh \\n@sontungmtp777\\n\\n#sontungmtp #theresnooneatall\\n#stanworld #backtoswsch,)  \n",
       "6                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  \n",
       "5                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  \n",
       "4                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  \n",
       "3       (the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)  \n",
       "19      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jaccard_distance = 0.3\n",
    "df_dups_text_30 = model.approxSimilarityJoin(df_hashed_text, df_hashed_text, jaccard_distance).filter(\"datasetA.id < datasetB.id\").select(\n",
    "            col(\"distCol\"),col(\"datasetA.org\").alias('org'),\n",
    "             col(\"datasetA.id\").alias(\"id_A\"),\n",
    "             col(\"datasetB.id\").alias(\"id_B\"), \n",
    "            col('datasetA.tweet_text').alias('text_A'),\n",
    "            col('datasetB.tweet_text').alias('text_B')) \n",
    "df_dups_txt_30 = df_dups_text_30\n",
    "df_dups_text_30.limit(20).toPandas().sort_values('distCol',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "876a8a3c-43cb-4d7f-8875-d219bd34d6a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:33:16 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:33:16 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:15 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:15 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:19 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:19 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:34:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:01 WARN org.apache.spark.deploy.yarn.YarnAllocator: Container from a bad node: container_1678398282650_0018_01_000015 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.744]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.745]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.746]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 WARN org.apache.spark.deploy.yarn.YarnAllocator: Container from a bad node: container_1678398282650_0018_01_000019 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.748]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.753]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.753]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 WARN org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Requesting driver to remove executor 15 for reason Container from a bad node: container_1678398282650_0018_01_000015 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.744]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.745]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.746]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 WARN org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Requesting driver to remove executor 19 for reason Container from a bad node: container_1678398282650_0018_01_000019 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.748]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.753]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.753]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 ERROR org.apache.spark.scheduler.cluster.YarnScheduler: Lost executor 15 on hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal: Container from a bad node: container_1678398282650_0018_01_000015 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.744]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.745]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.746]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 143.0 in stage 48.0 (TID 3366) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal executor 15): ExecutorLostFailure (executor 15 exited caused by one of the running tasks) Reason: Container from a bad node: container_1678398282650_0018_01_000015 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.744]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.745]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.746]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 105.0 in stage 50.0 (TID 3365) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal executor 15): ExecutorLostFailure (executor 15 exited caused by one of the running tasks) Reason: Container from a bad node: container_1678398282650_0018_01_000015 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.744]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.745]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.746]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 ERROR org.apache.spark.scheduler.cluster.YarnScheduler: Lost executor 19 on hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal: Container from a bad node: container_1678398282650_0018_01_000019 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.748]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.753]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.753]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 144.0 in stage 48.0 (TID 3367) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal executor 19): ExecutorLostFailure (executor 19 exited caused by one of the running tasks) Reason: Container from a bad node: container_1678398282650_0018_01_000019 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.748]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.753]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.753]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:01 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 107.0 in stage 50.0 (TID 3375) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal executor 19): ExecutorLostFailure (executor 19 exited caused by one of the running tasks) Reason: Container from a bad node: container_1678398282650_0018_01_000019 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: 143. Diagnostics: [2023-03-10 18:35:01.748]Container killed on request. Exit code is 143\n",
      "[2023-03-10 18:35:01.753]Container exited with a non-zero exit code 143. \n",
      "[2023-03-10 18:35:01.753]Killed by external signal\n",
      ".\n",
      "23/03/10 18:35:02 WARN org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Requesting driver to remove executor 20 for reason Container marked as failed: container_1678398282650_0018_01_000020 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: -100. Diagnostics: Container released on a *lost* node.\n",
      "23/03/10 18:35:02 WARN org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Requesting driver to remove executor 21 for reason Container marked as failed: container_1678398282650_0018_01_000021 on host: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal. Exit status: -100. Diagnostics: Container released on a *lost* node.\n",
      "23/03/10 18:35:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:29 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:29 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:29 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:29 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:29 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:29 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:29 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:29 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:33 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:33 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:33 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:33 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:33 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:33 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:33 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:33 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:42 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 2.0 in stage 52.0 (TID 3815) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-ztmk.c.msca-bdp-students.internal executor 4): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=2, mapId=3001, reduceId=7, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:42 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 15.0 in stage 52.0 (TID 3816) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-ztmk.c.msca-bdp-students.internal executor 4): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=15, mapId=3014, reduceId=5, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:42 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 21.0 in stage 52.0 (TID 3817) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-nvn8.c.msca-bdp-students.internal executor 16): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=21, mapId=3020, reduceId=2, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:42 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 34.0 in stage 52.0 (TID 3818) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-2w12.c.msca-bdp-students.internal executor 5): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=34, mapId=3033, reduceId=4, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:42 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 39.0 in stage 52.0 (TID 3819) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-g03c.c.msca-bdp-students.internal executor 8): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=39, mapId=3063, reduceId=3, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:42 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 43.0 in stage 52.0 (TID 3820) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-qwpk.c.msca-bdp-students.internal executor 10): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=43, mapId=3067, reduceId=0, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:42 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 54.0 in stage 52.0 (TID 3821) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-hkx2.c.msca-bdp-students.internal executor 18): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=54, mapId=3100, reduceId=12, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:42 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 58.0 in stage 52.0 (TID 3822) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-g03c.c.msca-bdp-students.internal executor 8): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=58, mapId=3106, reduceId=0, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:43 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 68.0 in stage 52.0 (TID 3823) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-nvn8.c.msca-bdp-students.internal executor 1): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=68, mapId=3138, reduceId=6, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:43 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 72.0 in stage 52.0 (TID 3824) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-q637.c.msca-bdp-students.internal executor 9): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=72, mapId=3144, reduceId=0, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:43 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 81.0 in stage 52.0 (TID 3825) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-qwpk.c.msca-bdp-students.internal executor 13): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=81, mapId=3178, reduceId=2, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:43 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 84.0 in stage 52.0 (TID 3826) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-qwpk.c.msca-bdp-students.internal executor 10): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=84, mapId=3182, reduceId=3, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:43 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 104.0 in stage 52.0 (TID 3829) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-q637.c.msca-bdp-students.internal executor 9): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=104, mapId=3251, reduceId=0, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:43 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 92.0 in stage 52.0 (TID 3827) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-htf6.c.msca-bdp-students.internal executor 2): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=92, mapId=3213, reduceId=11, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:43 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 95.0 in stage 52.0 (TID 3828) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-2f0k.c.msca-bdp-students.internal executor 7): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=95, mapId=3217, reduceId=3, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:44 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 106.0 in stage 52.0 (TID 3835) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-qwpk.c.msca-bdp-students.internal executor 13): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=106, mapId=3253, reduceId=14, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:44 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 119.0 in stage 52.0 (TID 3838) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-nvn8.c.msca-bdp-students.internal executor 16): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=119, mapId=3291, reduceId=12, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:44 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 120.0 in stage 52.0 (TID 3840) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-nvn8.c.msca-bdp-students.internal executor 1): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=120, mapId=3292, reduceId=0, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:44 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 132.0 in stage 52.0 (TID 3842) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-htf6.c.msca-bdp-students.internal executor 17): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=132, mapId=3329, reduceId=9, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Connecting to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337 failed in the last 4750 ms, fail this connection directly\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:44 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 131.0 in stage 52.0 (TID 3841) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-htf6.c.msca-bdp-students.internal executor 17): FetchFailed(BlockManagerId(15, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=13, mapIndex=131, mapId=3328, reduceId=8, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:777)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:48 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:48 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:48 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:48 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:48 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 0.0 in stage 54.0 (TID 3843) (hub-msca-bdp-dphub-students-kishorkumarreddy-sw-htf6.c.msca-bdp-students.internal executor 2): FetchFailed(BlockManagerId(19, hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal, 7337, None), shuffleId=15, mapIndex=9, mapId=3056, reduceId=0, message=\n",
      "org.apache.spark.shuffle.FetchFailedException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:775)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:690)\n",
      "\tat org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)\n",
      "\tat org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29)\n",
      "\tat scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)\n",
      "\tat scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)\n",
      "\tat org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)\n",
      "\tat scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\n",
      "\tat org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7.sort_addToSorter_0$(Unknown Source)\n",
      "\tat org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7.processNext(Unknown Source)\n",
      "\tat org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)\n",
      "\tat org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)\n",
      "\tat org.apache.spark.sql.execution.window.WindowExecAbstract$$anon$1.fetchNextRow(WindowExecAbstract.scala:67)\n",
      "\tat org.apache.spark.sql.execution.window.WindowExecAbstract$$anon$1.<init>(WindowExecAbstract.scala:76)\n",
      "\tat org.apache.spark.sql.execution.window.WindowExecAbstract.$anonfun$doExecute$3(WindowExecAbstract.scala:56)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:863)\n",
      "\tat org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:863)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)\n",
      "\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)\n",
      "\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:337)\n",
      "\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)\n",
      "\tat org.apache.spark.scheduler.Task.run(Task.scala:131)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:505)\n",
      "\tat org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)\n",
      "\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:508)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat java.lang.Thread.run(Thread.java:750)\n",
      "Caused by: java.io.IOException: Failed to connect to hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal:7337\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:287)\n",
      "\tat org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)\n",
      "\tat org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:105)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)\n",
      "\tat org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)\n",
      "\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n",
      "\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n",
      "\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n",
      "\tat io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)\n",
      "\t... 1 more\n",
      "Caused by: java.net.UnknownHostException: hub-msca-bdp-dphub-students-kishorkumarreddy-sw-5p4v.c.msca-bdp-students.internal\n",
      "\tat java.net.InetAddress$CachedAddresses.get(InetAddress.java:764)\n",
      "\tat java.net.InetAddress.getAllByName0(InetAddress.java:1282)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1140)\n",
      "\tat java.net.InetAddress.getAllByName(InetAddress.java:1064)\n",
      "\tat java.net.InetAddress.getByName(InetAddress.java:1014)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:156)\n",
      "\tat io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:153)\n",
      "\tat java.security.AccessController.doPrivileged(Native Method)\n",
      "\tat io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:153)\n",
      "\tat io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:41)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:61)\n",
      "\tat io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:53)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:55)\n",
      "\tat io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:31)\n",
      "\tat io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:106)\n",
      "\tat io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:206)\n",
      "\tat io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:46)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:180)\n",
      "\tat io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:166)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:577)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:551)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:490)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:615)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.setSuccess0(DefaultPromise.java:604)\n",
      "\tat io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)\n",
      "\tat io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:84)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:984)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:504)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:417)\n",
      "\tat io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:474)\n",
      "\tat io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472)\n",
      "\tat io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:500)\n",
      "\tat io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)\n",
      "\tat io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)\n",
      "\t... 2 more\n",
      "\n",
      ")\n",
      "23/03/10 18:35:55 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:55 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:55 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:55 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:55 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:35:55 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "[Stage 56:>                                                         (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total records:  8807\n",
      "Duplicate Tweets based on { 0.3 } jaccard distance:  577\n",
      "Unique Tweets based on { 0.3 } jaccard distance:  0.3 :  8230\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "records = df_hashed_text.count()\n",
    "dups_30 = df_dups_text_30.select('id_A').distinct().count()\n",
    "uniques = records - dups_30\n",
    "\n",
    "print ('Total records: ', records)\n",
    "print ('Duplicate Tweets based on {', jaccard_distance, '} jaccard distance: ', dups_30)\n",
    "print ('Unique Tweets based on {', jaccard_distance, '} jaccard distance: ', jaccard_distance, ': ', uniques)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e7c676c0-3018-4c5c-8a92-280230b741c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dups_text_30.createOrReplaceTempView(\"tw_df\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0d97fe3-ffb0-499d-905d-066632a502cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:36:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:36:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:36:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:36:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                ]\r"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Others</td>\n",
       "      <td>1584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ngo</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gov</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>influencer</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          org  count(1)\n",
       "0        news        11\n",
       "1      Others      1584\n",
       "2         edu       128\n",
       "3         ngo         1\n",
       "4         gov        26\n",
       "5  influencer        13"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df = spark.sql('select org,count(*) from tw_df group by org').toPandas()\n",
    "dup_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4032e74d-d45c-4b0b-91f1-b6ad129a1495",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hashed_text.createOrReplaceTempView(\"tw_df\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d69f3b5d-0252-4255-b0ca-f7e32bde3647",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:37:56 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:37:56 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:38:57 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:38:57 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:38:59 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:38:59 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:39:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:39:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:39:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:39:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:39:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "all_df = spark.sql('select org,count(*) from tw_df group by org').toPandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7d65a85-a628-4c2e-9dc7-5dc5255ea3db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gov</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>1395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>influencer</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Others</td>\n",
       "      <td>6702</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          org  count(1)\n",
       "0        news       530\n",
       "1         gov       103\n",
       "2         edu      1395\n",
       "3  influencer        16\n",
       "4      Others      6702"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b05e7a64-2ef4-439a-81b3-accf7fc4edd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Others</td>\n",
       "      <td>1584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ngo</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gov</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      org  count(1)\n",
       "0    news        11\n",
       "1  Others      1584\n",
       "2     edu       128\n",
       "3     ngo         1\n",
       "4     gov        26"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e02748d3-ad05-466e-b699-5a34634e15a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gov</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>1395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Others</td>\n",
       "      <td>6702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ngo</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      org  count(1)\n",
       "0    news       530\n",
       "1     gov       103\n",
       "2     edu      1395\n",
       "4  Others      6702\n",
       "5     ngo        61"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df.sort_values(by='org',inplace=True)\n",
    "all_df.drop(3,inplace=True)\n",
    "all_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0faa1a1-abe0-4bae-b874-3a9895280e56",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Others</td>\n",
       "      <td>1584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gov</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>influencer</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ngo</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          org  count(1)\n",
       "1      Others      1584\n",
       "2         edu       128\n",
       "4         gov        26\n",
       "5  influencer        13\n",
       "0        news        11\n",
       "3         ngo         1"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "05f05516-1d1a-480a-99d4-13e952821f89",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_df.sort_values(by='org',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "adae011b-f0f7-4e13-a3e2-c895d372c0c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "index = np.arange(len(dup_df['org']))\n",
    "index2 = np.arange(len(all_df['org']))\n",
    "\n",
    "bar_width = 0.35\n",
    "opacity = 0.8\n",
    "\n",
    "ax.bar(index, dup_df['count(1)'], color='orange', align='edge', width=bar_width, label = 'Duplicate Count')\n",
    "ax.bar(index2, all_df['count(1)'], color='blue', align='edge', width=-bar_width,label = 'Unique Count')\n",
    "\n",
    "# Assign the tick labels\n",
    "ax.set_xticks(index)\n",
    "ax.set_xticklabels(dup_df['org'], rotation=90)\n",
    "plt.title('Tweet Similarity at Jaccard 0.3')\n",
    "plt.xlabel('Organization')\n",
    "plt.ylabel('Count of Tweets')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1fada771-f0d4-439a-8a82-72b5d55123e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Define custom colors\n",
    "bar_colors = ['#1F77B4', '#FFA07A']\n",
    "\n",
    "# Create figure and axis objects\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "\n",
    "# Define bar width and opacity\n",
    "bar_width = 0.4\n",
    "opacity = 0.8\n",
    "\n",
    "# Define index arrays for each set of bars\n",
    "index = np.arange(len(dup_df['org']))\n",
    "index2 = np.arange(len(all_df['org']))\n",
    "\n",
    "# Create the two sets of vertical bars\n",
    "ax.bar(index, dup_df['count(1)'], color=bar_colors[0], align='edge', width=bar_width, alpha=opacity, label='Duplicates')\n",
    "ax.bar(index2, all_df['count(1)'], color=bar_colors[1], align='edge', width=-bar_width, alpha=opacity, label='Unique')\n",
    "\n",
    "# Set the tick labels and axis limits\n",
    "ax.set_xticks(index)\n",
    "ax.set_xticklabels(dup_df['org'], fontsize=12, rotation=90)\n",
    "ax.set_ylim(bottom=0)\n",
    "ax.set_ylabel('Count', fontsize=14)\n",
    "ax.set_xlabel('Organization', fontsize=14)\n",
    "\n",
    "# Add a title and adjust the subplot spacing\n",
    "ax.set_title('Duplicate vs. Unique Entries by Organization at Jaccard 0.3', fontsize=16)\n",
    "plt.subplots_adjust(left=0.2, right=0.9, top=0.9, bottom=0.1)\n",
    "\n",
    "# Add a legend with custom formatting\n",
    "legend = ax.legend(loc='upper right', fontsize=12)\n",
    "for i, text in enumerate(legend.get_texts()):\n",
    "    plt.setp(text, color=bar_colors[i], weight='bold')\n",
    "\n",
    "# Remove spines and set a grid\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.yaxis.grid(color='gray', linestyle='dashed')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d93d32bf-de1b-47c9-b001-df94ab647ed7",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_df.sort_values(by='org',inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43da3506-7950-4d48-851d-59cf7c3592d2",
   "metadata": {},
   "source": [
    "# Tweet Uniqueness Graph Based on Jaccard Similarity (0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8e5f73ee-4e34-4fc7-be88-d5eb0127ddfb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "826593d1-ebe0-4861-b912-b6a62262961d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:39:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:39:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:39:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:39:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:09 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:09 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:09 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:09 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:09 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:09 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:09 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:09 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:10 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:10 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:10 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:10 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>distCol</th>\n",
       "      <th>org</th>\n",
       "      <th>id_A</th>\n",
       "      <th>id_B</th>\n",
       "      <th>text_A</th>\n",
       "      <th>text_B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.470588</td>\n",
       "      <td>Others</td>\n",
       "      <td>1374</td>\n",
       "      <td>2286</td>\n",
       "      <td>(big snowman: lined notebook by daisy ford design https://t.co/hyaailolb2 via @amazon #notebook #scho,)</td>\n",
       "      <td>(blue cat: lined notebook by daisy ford design https://t.co/54jqdvxaom via @amazon #notebook #diary #,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.357143</td>\n",
       "      <td>Others</td>\n",
       "      <td>573</td>\n",
       "      <td>620</td>\n",
       "      <td>(@antonioguterres ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, ar,)</td>\n",
       "      <td>(@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.307692</td>\n",
       "      <td>Others</td>\n",
       "      <td>573</td>\n",
       "      <td>621</td>\n",
       "      <td>(@antonioguterres ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, ar,)</td>\n",
       "      <td>(@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.285714</td>\n",
       "      <td>news</td>\n",
       "      <td>767</td>\n",
       "      <td>2933</td>\n",
       "      <td>(@teacherinkinder @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;amp;,)</td>\n",
       "      <td>(@mrs_al_13 @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;amp; my cl,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.230769</td>\n",
       "      <td>Others</td>\n",
       "      <td>620</td>\n",
       "      <td>621</td>\n",
       "      <td>(@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)</td>\n",
       "      <td>(@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.166667</td>\n",
       "      <td>Others</td>\n",
       "      <td>3320</td>\n",
       "      <td>8619</td>\n",
       "      <td>(@janethlovsbooks @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)</td>\n",
       "      <td>(@techmidschteach @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>1552</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>1113</td>\n",
       "      <td>1552</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>1113</td>\n",
       "      <td>1502</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>8711</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>3248</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>3212</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>3628</td>\n",
       "      <td>5287</td>\n",
       "      <td>(back to school with nhatthanh \\n@sontungmtp777\\n\\n#sontungmtp #theresnooneatall\\n#stanworld #backtoswsch,)</td>\n",
       "      <td>(back to school with nhatthanh \\n@sontungmtp777\\n\\n#sontungmtp #theresnooneatall\\n#stanworld #backtoswsch,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>1502</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>134</td>\n",
       "      <td>1113</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>5628</td>\n",
       "      <td>5944</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>3556</td>\n",
       "      <td>5944</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>3556</td>\n",
       "      <td>5628</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>2643</td>\n",
       "      <td>3441</td>\n",
       "      <td>(the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)</td>\n",
       "      <td>(the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>1113</td>\n",
       "      <td>3212</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "      <td>(time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     distCol     org  id_A  id_B  \\\n",
       "1   0.470588  Others  1374  2286   \n",
       "3   0.357143  Others   573   620   \n",
       "4   0.307692  Others   573   621   \n",
       "0   0.285714    news   767  2933   \n",
       "5   0.230769  Others   620   621   \n",
       "2   0.166667  Others  3320  8619   \n",
       "13  0.000000  Others   134  1552   \n",
       "18  0.000000  Others  1113  1552   \n",
       "17  0.000000  Others  1113  1502   \n",
       "16  0.000000  Others   134  8711   \n",
       "15  0.000000  Others   134  3248   \n",
       "14  0.000000  Others   134  3212   \n",
       "10  0.000000  Others  3628  5287   \n",
       "12  0.000000  Others   134  1502   \n",
       "11  0.000000  Others   134  1113   \n",
       "9   0.000000     edu  5628  5944   \n",
       "8   0.000000     edu  3556  5944   \n",
       "7   0.000000     edu  3556  5628   \n",
       "6   0.000000  Others  2643  3441   \n",
       "19  0.000000  Others  1113  3212   \n",
       "\n",
       "                                                                                                         text_A  \\\n",
       "1       (big snowman: lined notebook by daisy ford design https://t.co/hyaailolb2 via @amazon #notebook #scho,)   \n",
       "3      (@antonioguterres ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, ar,)   \n",
       "4      (@antonioguterres ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, ar,)   \n",
       "0       (@teacherinkinder @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;,)   \n",
       "5      (@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)   \n",
       "2       (@janethlovsbooks @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)   \n",
       "13      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "18      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "17      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "16      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "15      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "14      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "10  (back to school with nhatthanh \\n@sontungmtp777\\n\\n#sontungmtp #theresnooneatall\\n#stanworld #backtoswsch,)   \n",
       "12      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "11      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "9                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "8                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "7                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "6       (the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)   \n",
       "19      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)   \n",
       "\n",
       "                                                                                                         text_B  \n",
       "1       (blue cat: lined notebook by daisy ford design https://t.co/54jqdvxaom via @amazon #notebook #diary #,)  \n",
       "3      (@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)  \n",
       "4      (@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)  \n",
       "0       (@mrs_al_13 @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp; my cl,)  \n",
       "5      (@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)  \n",
       "2       (@techmidschteach @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)  \n",
       "13      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "18      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "17      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "16      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "15      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "14      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "10  (back to school with nhatthanh \\n@sontungmtp777\\n\\n#sontungmtp #theresnooneatall\\n#stanworld #backtoswsch,)  \n",
       "12      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "11      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  \n",
       "9                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  \n",
       "8                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  \n",
       "7                              (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  \n",
       "6       (the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)  \n",
       "19      (time to return to learn! enter the $100 amazon gift card giveaway!  #btevents #backtoschool  https:/,)  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jaccard_distance = 0.5\n",
    "df_dups_text_50 = model.approxSimilarityJoin(df_hashed_text, df_hashed_text, jaccard_distance).filter(\"datasetA.id < datasetB.id\").select(\n",
    "            col(\"distCol\"),col(\"datasetA.org\").alias('org'),\n",
    "             col(\"datasetA.id\").alias(\"id_A\"),\n",
    "             col(\"datasetB.id\").alias(\"id_B\"), \n",
    "            col('datasetA.tweet_text').alias('text_A'),\n",
    "            col('datasetB.tweet_text').alias('text_B')) \n",
    "df_dups_txt_50 = df_dups_text_50\n",
    "df_dups_text_50.limit(20).toPandas().sort_values('distCol',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba91af15-40db-471c-a2f3-87ea69d62748",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:40:36 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:40:36 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:38 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:38 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:40 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:40 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:41:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:46 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:46 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:46 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:46 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:49 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:51 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:51 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:51 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:51 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:51 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:51 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:42:52 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "[Stage 113:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total records:  8807\n",
      "Duplicate Tweets based on { 0.5 } jaccard distance:  858\n",
      "Unique Tweets based on { 0.5 } jaccard distance:  0.5 :  7949\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "records = df_hashed_text.count()\n",
    "dups_50 = df_dups_text_50.select('id_A').distinct().count()\n",
    "uniques = records - dups_50\n",
    "\n",
    "print ('Total records: ', records)\n",
    "print ('Duplicate Tweets based on {', jaccard_distance, '} jaccard distance: ', dups_50)\n",
    "print ('Unique Tweets based on {', jaccard_distance, '} jaccard distance: ', jaccard_distance, ': ', uniques)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8fd033c1-0184-44ab-93ee-4e5478cd73c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dups_text_50.createOrReplaceTempView(\"tw_df\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "357146b3-705b-4792-9606-bfa919870798",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:43:16 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:43:16 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:43:16 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:43:16 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:20 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:21 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:24 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Others</td>\n",
       "      <td>3117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ngo</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gov</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>influencer</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          org  count(1)\n",
       "0        news        14\n",
       "1      Others      3117\n",
       "2         edu       214\n",
       "3         ngo         1\n",
       "4         gov        37\n",
       "5  influencer        13"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df_5 = spark.sql('select org,count(*) from tw_df group by org').toPandas()\n",
    "dup_df_5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6434dda6-c99c-4049-a039-9ae8f2ca3cfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hashed_text.createOrReplaceTempView(\"tw_df\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "089763bd-8bf5-47a0-9518-dbbbbe8f0179",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:44:48 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:44:48 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:50 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:53 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:56 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:56 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:56 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:56 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:56 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "all_df_5 = spark.sql('select org,count(*) from tw_df group by org').toPandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "121d43c6-8305-40c8-88cd-75b9e69944ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gov</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>1395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>influencer</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Others</td>\n",
       "      <td>6702</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          org  count(1)\n",
       "0        news       530\n",
       "1         gov       103\n",
       "2         edu      1395\n",
       "3  influencer        16\n",
       "4      Others      6702"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_df_5.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44264695-6642-4f6c-8711-114b6c80bc91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gov</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>1395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Others</td>\n",
       "      <td>6702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ngo</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      org  count(1)\n",
       "0    news       530\n",
       "1     gov       103\n",
       "2     edu      1395\n",
       "4  Others      6702\n",
       "5     ngo        61"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df_5.sort_values(by='org',inplace=True)\n",
    "all_df_5.drop(3,inplace=True)\n",
    "all_df_5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "487b0ac1-6bdc-4d29-aaf9-65ac460bb0b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Others</td>\n",
       "      <td>3117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gov</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>influencer</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ngo</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          org  count(1)\n",
       "1      Others      3117\n",
       "2         edu       214\n",
       "4         gov        37\n",
       "5  influencer        13\n",
       "0        news        14\n",
       "3         ngo         1"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df_5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0101cdec-f6f0-48c7-8273-d9f343e0d3cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_df_5.sort_values(by='org',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "593f0c55-c77b-4dd4-aecb-be5595d1920e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "index = np.arange(len(dup_df_5['org']))\n",
    "index2 = np.arange(len(all_df_5['org']))\n",
    "\n",
    "bar_width = 0.35\n",
    "opacity = 0.8\n",
    "\n",
    "ax.bar(index, dup_df_5['count(1)'], color='orange', align='edge', width=bar_width, label = 'Duplicate Count')\n",
    "ax.bar(index2, all_df_5['count(1)'], color='blue', align='edge', width=-bar_width,label = 'Unique Count')\n",
    "\n",
    "# Assign the tick labels\n",
    "ax.set_xticks(index)\n",
    "ax.set_xticklabels(dup_df['org'], rotation=90)\n",
    "\n",
    "plt.xlabel('Organization')\n",
    "plt.title('Tweet Similarity at Jaccard 0.5')\n",
    "plt.ylabel('Count of Tweets')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5715d3d-8590-4eaa-9e20-f2227822a64d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "654052c7-a1d3-4529-ab08-85d953233347",
   "metadata": {},
   "source": [
    "# Tweet Uniqueness Graph Based on Jaccard Similarity (0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f038f73b-b467-439f-81e3-0166415ef4e4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:45:58 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:58 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:58 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:45:58 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:02 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:04 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:04 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:04 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:04 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:04 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:04 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:04 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:04 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:05 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:05 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:05 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:05 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:05 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:05 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:05 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:05 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:06 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>distCol</th>\n",
       "      <th>org</th>\n",
       "      <th>id_A</th>\n",
       "      <th>id_B</th>\n",
       "      <th>text_A</th>\n",
       "      <th>text_B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.684211</td>\n",
       "      <td>Others</td>\n",
       "      <td>1374</td>\n",
       "      <td>2811</td>\n",
       "      <td>(big snowman: lined notebook by daisy ford design https://t.co/hyaailolb2 via @amazon #notebook #scho,)</td>\n",
       "      <td>(happiest season: christmas notebooks by daisy ford design https://t.co/457fi08d26 via @amazon #noteb,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.684211</td>\n",
       "      <td>Others</td>\n",
       "      <td>2286</td>\n",
       "      <td>2811</td>\n",
       "      <td>(blue cat: lined notebook by daisy ford design https://t.co/54jqdvxaom via @amazon #notebook #diary #,)</td>\n",
       "      <td>(happiest season: christmas notebooks by daisy ford design https://t.co/457fi08d26 via @amazon #noteb,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.684211</td>\n",
       "      <td>Others</td>\n",
       "      <td>2286</td>\n",
       "      <td>3240</td>\n",
       "      <td>(blue cat: lined notebook by daisy ford design https://t.co/54jqdvxaom via @amazon #notebook #diary #,)</td>\n",
       "      <td>(blue toy train: lined notebook https://t.co/0affnq1pvo via @amazon #notebook #school #college #colle,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.647059</td>\n",
       "      <td>Others</td>\n",
       "      <td>3240</td>\n",
       "      <td>3958</td>\n",
       "      <td>(blue toy train: lined notebook https://t.co/0affnq1pvo via @amazon #notebook #school #college #colle,)</td>\n",
       "      <td>(paris diary: lined journal https://t.co/kzz0dizkhi via @amazon #notebook #journal #school #college #,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.647059</td>\n",
       "      <td>Others</td>\n",
       "      <td>3105</td>\n",
       "      <td>3958</td>\n",
       "      <td>(santa claus on skates: lined notebook https://t.co/qs4f7x4uiv via @amazon #notebook #school #college,)</td>\n",
       "      <td>(paris diary: lined journal https://t.co/kzz0dizkhi via @amazon #notebook #journal #school #college #,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.647059</td>\n",
       "      <td>Others</td>\n",
       "      <td>3847</td>\n",
       "      <td>3958</td>\n",
       "      <td>(honey bee: lined notebook https://t.co/9qwplkfvom via @amazon #notebook #school #college #home #writ,)</td>\n",
       "      <td>(paris diary: lined journal https://t.co/kzz0dizkhi via @amazon #notebook #journal #school #college #,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.615385</td>\n",
       "      <td>Others</td>\n",
       "      <td>1867</td>\n",
       "      <td>4165</td>\n",
       "      <td>(@d900gt @amazon awesome 😁😁 @d900gt\\n\\n#theschooljourney #school #book #bookers,)</td>\n",
       "      <td>(@d900gt @amazon oh wow, nice!! @d900gt \\n\\n#theschooljourney #school #book #bookers #deepikapadukone,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.588235</td>\n",
       "      <td>Others</td>\n",
       "      <td>3105</td>\n",
       "      <td>3240</td>\n",
       "      <td>(santa claus on skates: lined notebook https://t.co/qs4f7x4uiv via @amazon #notebook #school #college,)</td>\n",
       "      <td>(blue toy train: lined notebook https://t.co/0affnq1pvo via @amazon #notebook #school #college #colle,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.588235</td>\n",
       "      <td>Others</td>\n",
       "      <td>3105</td>\n",
       "      <td>3847</td>\n",
       "      <td>(santa claus on skates: lined notebook https://t.co/qs4f7x4uiv via @amazon #notebook #school #college,)</td>\n",
       "      <td>(honey bee: lined notebook https://t.co/9qwplkfvom via @amazon #notebook #school #college #home #writ,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.588235</td>\n",
       "      <td>Others</td>\n",
       "      <td>3240</td>\n",
       "      <td>3847</td>\n",
       "      <td>(blue toy train: lined notebook https://t.co/0affnq1pvo via @amazon #notebook #school #college #colle,)</td>\n",
       "      <td>(honey bee: lined notebook https://t.co/9qwplkfvom via @amazon #notebook #school #college #home #writ,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.470588</td>\n",
       "      <td>Others</td>\n",
       "      <td>1374</td>\n",
       "      <td>2286</td>\n",
       "      <td>(big snowman: lined notebook by daisy ford design https://t.co/hyaailolb2 via @amazon #notebook #scho,)</td>\n",
       "      <td>(blue cat: lined notebook by daisy ford design https://t.co/54jqdvxaom via @amazon #notebook #diary #,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.357143</td>\n",
       "      <td>Others</td>\n",
       "      <td>573</td>\n",
       "      <td>620</td>\n",
       "      <td>(@antonioguterres ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, ar,)</td>\n",
       "      <td>(@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.307692</td>\n",
       "      <td>Others</td>\n",
       "      <td>573</td>\n",
       "      <td>621</td>\n",
       "      <td>(@antonioguterres ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, ar,)</td>\n",
       "      <td>(@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.285714</td>\n",
       "      <td>news</td>\n",
       "      <td>767</td>\n",
       "      <td>2933</td>\n",
       "      <td>(@teacherinkinder @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;amp;,)</td>\n",
       "      <td>(@mrs_al_13 @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;amp; my cl,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.230769</td>\n",
       "      <td>Others</td>\n",
       "      <td>620</td>\n",
       "      <td>621</td>\n",
       "      <td>(@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)</td>\n",
       "      <td>(@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.166667</td>\n",
       "      <td>Others</td>\n",
       "      <td>3320</td>\n",
       "      <td>8619</td>\n",
       "      <td>(@janethlovsbooks @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)</td>\n",
       "      <td>(@techmidschteach @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>Others</td>\n",
       "      <td>2643</td>\n",
       "      <td>3441</td>\n",
       "      <td>(the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)</td>\n",
       "      <td>(the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>3556</td>\n",
       "      <td>5628</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>3556</td>\n",
       "      <td>5944</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>edu</td>\n",
       "      <td>5628</td>\n",
       "      <td>5944</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "      <td>(the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     distCol     org  id_A  id_B  \\\n",
       "2   0.684211  Others  1374  2811   \n",
       "4   0.684211  Others  2286  2811   \n",
       "5   0.684211  Others  2286  3240   \n",
       "10  0.647059  Others  3240  3958   \n",
       "8   0.647059  Others  3105  3958   \n",
       "12  0.647059  Others  3847  3958   \n",
       "3   0.615385  Others  1867  4165   \n",
       "6   0.588235  Others  3105  3240   \n",
       "7   0.588235  Others  3105  3847   \n",
       "9   0.588235  Others  3240  3847   \n",
       "1   0.470588  Others  1374  2286   \n",
       "13  0.357143  Others   573   620   \n",
       "14  0.307692  Others   573   621   \n",
       "0   0.285714    news   767  2933   \n",
       "15  0.230769  Others   620   621   \n",
       "11  0.166667  Others  3320  8619   \n",
       "16  0.000000  Others  2643  3441   \n",
       "17  0.000000     edu  3556  5628   \n",
       "18  0.000000     edu  3556  5944   \n",
       "19  0.000000     edu  5628  5944   \n",
       "\n",
       "                                                                                                      text_A  \\\n",
       "2    (big snowman: lined notebook by daisy ford design https://t.co/hyaailolb2 via @amazon #notebook #scho,)   \n",
       "4    (blue cat: lined notebook by daisy ford design https://t.co/54jqdvxaom via @amazon #notebook #diary #,)   \n",
       "5    (blue cat: lined notebook by daisy ford design https://t.co/54jqdvxaom via @amazon #notebook #diary #,)   \n",
       "10   (blue toy train: lined notebook https://t.co/0affnq1pvo via @amazon #notebook #school #college #colle,)   \n",
       "8    (santa claus on skates: lined notebook https://t.co/qs4f7x4uiv via @amazon #notebook #school #college,)   \n",
       "12   (honey bee: lined notebook https://t.co/9qwplkfvom via @amazon #notebook #school #college #home #writ,)   \n",
       "3                          (@d900gt @amazon awesome 😁😁 @d900gt\\n\\n#theschooljourney #school #book #bookers,)   \n",
       "6    (santa claus on skates: lined notebook https://t.co/qs4f7x4uiv via @amazon #notebook #school #college,)   \n",
       "7    (santa claus on skates: lined notebook https://t.co/qs4f7x4uiv via @amazon #notebook #school #college,)   \n",
       "9    (blue toy train: lined notebook https://t.co/0affnq1pvo via @amazon #notebook #school #college #colle,)   \n",
       "1    (big snowman: lined notebook by daisy ford design https://t.co/hyaailolb2 via @amazon #notebook #scho,)   \n",
       "13  (@antonioguterres ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, ar,)   \n",
       "14  (@antonioguterres ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, ar,)   \n",
       "0    (@teacherinkinder @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp;,)   \n",
       "15  (@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)   \n",
       "11   (@janethlovsbooks @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)   \n",
       "16   (the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)   \n",
       "17                          (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "18                          (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "19                          (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)   \n",
       "\n",
       "                                                                                                      text_B  \n",
       "2    (happiest season: christmas notebooks by daisy ford design https://t.co/457fi08d26 via @amazon #noteb,)  \n",
       "4    (happiest season: christmas notebooks by daisy ford design https://t.co/457fi08d26 via @amazon #noteb,)  \n",
       "5    (blue toy train: lined notebook https://t.co/0affnq1pvo via @amazon #notebook #school #college #colle,)  \n",
       "10   (paris diary: lined journal https://t.co/kzz0dizkhi via @amazon #notebook #journal #school #college #,)  \n",
       "8    (paris diary: lined journal https://t.co/kzz0dizkhi via @amazon #notebook #journal #school #college #,)  \n",
       "12   (paris diary: lined journal https://t.co/kzz0dizkhi via @amazon #notebook #journal #school #college #,)  \n",
       "3    (@d900gt @amazon oh wow, nice!! @d900gt \\n\\n#theschooljourney #school #book #bookers #deepikapadukone,)  \n",
       "6    (blue toy train: lined notebook https://t.co/0affnq1pvo via @amazon #notebook #school #college #colle,)  \n",
       "7    (honey bee: lined notebook https://t.co/9qwplkfvom via @amazon #notebook #school #college #home #writ,)  \n",
       "9    (honey bee: lined notebook https://t.co/9qwplkfvom via @amazon #notebook #school #college #home #writ,)  \n",
       "1    (blue cat: lined notebook by daisy ford design https://t.co/54jqdvxaom via @amazon #notebook #diary #,)  \n",
       "13  (@joebiden ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are trapp,)  \n",
       "14  (@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)  \n",
       "0    (@mrs_al_13 @donorschoose @amazon hi, hello, howdy! happy #sundayvibes it’s #backtoschool &amp; my cl,)  \n",
       "15  (@kamalaharris ⚠️urgent⚠️\\nthe students at #sharif_university, first ranking university in iran, are t,)  \n",
       "11   (@techmidschteach @amazon i'm a hs #specialeducation teacher working with cognitively impaired studen,)  \n",
       "16   (the algebra requirement needed to graduate is the most failed subject in community colleges.        ,)  \n",
       "17                          (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  \n",
       "18                          (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  \n",
       "19                          (the latest national safety school! https://t.co/rqpfbuyjcx #education #edtech,)  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jaccard_distance = 0.7\n",
    "df_dups_text_70 = model.approxSimilarityJoin(df_hashed_text, df_hashed_text, jaccard_distance).filter(\"datasetA.id < datasetB.id\").select(\n",
    "            col(\"distCol\"),col(\"datasetA.org\").alias('org'),\n",
    "             col(\"datasetA.id\").alias(\"id_A\"),\n",
    "             col(\"datasetB.id\").alias(\"id_B\"), \n",
    "            col('datasetA.tweet_text').alias('text_A'),\n",
    "            col('datasetB.tweet_text').alias('text_B')) \n",
    "df_dups_txt_70 = df_dups_text_70\n",
    "df_dups_text_70.limit(20).toPandas().sort_values('distCol',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2c5e958-bd36-4975-9242-8574e8e9d9e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:47:32 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:47:32 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:34 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:34 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:36 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:36 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:38 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:38 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:38 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:40 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:40 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:40 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:48:40 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:42 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:42 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:42 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:42 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:42 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:42 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:42 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:42 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:49:45 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "[Stage 170:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total records:  8807\n",
      "Duplicate Tweets based on { 0.7 } jaccard distance:  1303\n",
      "Unique Tweets based on { 0.7 } jaccard distance:  0.7 :  7504\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "records = df_hashed_text.count()\n",
    "dups_70 = df_dups_text_70.select('id_A').distinct().count()\n",
    "uniques = records - dups_70\n",
    "\n",
    "print ('Total records: ', records)\n",
    "print ('Duplicate Tweets based on {', jaccard_distance, '} jaccard distance: ', dups_70)\n",
    "print ('Unique Tweets based on {', jaccard_distance, '} jaccard distance: ', jaccard_distance, ': ', uniques)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e5687fc4-275d-4bb3-a0a6-e1372ba2564a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dups_text_70.createOrReplaceTempView(\"tw_df\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bfeddb22-f6a4-4f5d-89fd-104ef2b47dbd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:50:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:50:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:50:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:50:08 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:11 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:12 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:12 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:12 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:12 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:12 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:12 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:12 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:12 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:14 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:15 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:15 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:15 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:15 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:15 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:15 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "                                                                                \r"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>45</td>\n",
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       "      <th>1</th>\n",
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       "      <th>2</th>\n",
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       "0        news        45\n",
       "1      Others      6684\n",
       "2         edu       425\n",
       "3         ngo         6\n",
       "4         gov        48\n",
       "5  influencer        13"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df = spark.sql('select org,count(*) from tw_df group by org').toPandas()\n",
    "dup_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7f8e7cd2-8c19-4488-9cee-e3261a970f61",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hashed_text.createOrReplaceTempView(\"tw_df\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0c9b433-6a73-4147-8afa-803d1cd9b934",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/03/10 18:51:37 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:51:37 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:39 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:41 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:41 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:43 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n",
      "23/03/10 18:52:44 WARN org.apache.spark.sql.execution.window.WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.\n"
     ]
    }
   ],
   "source": [
    "all_df = spark.sql('select org,count(*) from tw_df group by org').toPandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf40c557-c131-4306-8e07-e151675afde3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gov</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>1395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>influencer</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Others</td>\n",
       "      <td>6702</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          org  count(1)\n",
       "0        news       530\n",
       "1         gov       103\n",
       "2         edu      1395\n",
       "3  influencer        16\n",
       "4      Others      6702"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "572be640-122c-410b-9c0d-b18b25cf6bfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gov</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>1395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Others</td>\n",
       "      <td>6702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ngo</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      org  count(1)\n",
       "0    news       530\n",
       "1     gov       103\n",
       "2     edu      1395\n",
       "4  Others      6702\n",
       "5     ngo        61"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df.sort_values(by='org',inplace=True)\n",
    "all_df.drop(3,inplace=True)\n",
    "all_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6fe99cfd-7a33-4b7b-be82-66a9c8c747c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org</th>\n",
       "      <th>count(1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Others</td>\n",
       "      <td>6684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>edu</td>\n",
       "      <td>425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gov</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>influencer</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>news</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ngo</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          org  count(1)\n",
       "1      Others      6684\n",
       "2         edu       425\n",
       "4         gov        48\n",
       "5  influencer        13\n",
       "0        news        45\n",
       "3         ngo         6"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dup_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61c3653c-652b-4bb9-b87b-fddcdcf64c89",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_df.sort_values(by='org',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "638b4e2d-149f-405e-a41f-6a865fe78da8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "index = np.arange(len(dup_df['org']))\n",
    "index2 = np.arange(len(all_df['org']))\n",
    "\n",
    "bar_width = 0.35\n",
    "opacity = 0.8\n",
    "\n",
    "ax.bar(index, dup_df['count(1)'], color='orange', align='edge', width=bar_width, label = 'Duplicate Count')\n",
    "ax.bar(index2, all_df['count(1)'], color='blue', align='edge', width=-bar_width,label = 'Unique Count')\n",
    "\n",
    "# Assign the tick labels\n",
    "ax.set_xticks(index)\n",
    "ax.set_xticklabels(dup_df['org'], rotation=90)\n",
    "plt.title('Tweet Similarity at Jaccard 0.7')\n",
    "plt.xlabel('Organization')\n",
    "plt.ylabel('Count of Tweets')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70afcb09-6c5a-4d93-b49e-745784765139",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Define custom colors\n",
    "bar_colors = ['#1F77B4', '#FFA07A']\n",
    "\n",
    "# Create figure and axis objects\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "\n",
    "# Define bar width and opacity\n",
    "bar_width = 0.4\n",
    "opacity = 0.8\n",
    "\n",
    "# Define index arrays for each set of bars\n",
    "index = np.arange(len(dup_df['org']))\n",
    "index2 = np.arange(len(all_df['org']))\n",
    "\n",
    "# Create the two sets of vertical bars\n",
    "ax.bar(index, dup_df['count(1)'], color=bar_colors[0], align='edge', width=bar_width, alpha=opacity, label='Duplicates')\n",
    "ax.bar(index2, all_df['count(1)'], color=bar_colors[1], align='edge', width=-bar_width, alpha=opacity, label='Unique')\n",
    "\n",
    "# Set the tick labels and axis limits\n",
    "ax.set_xticks(index)\n",
    "ax.set_xticklabels(dup_df['org'], fontsize=12, rotation=90)\n",
    "ax.set_ylim(bottom=0)\n",
    "ax.set_ylabel('Count', fontsize=14)\n",
    "ax.set_xlabel('Organization', fontsize=14)\n",
    "\n",
    "# Add a title and adjust the subplot spacing\n",
    "ax.set_title('Duplicate vs. Unique Entries by Organization', fontsize=16)\n",
    "plt.subplots_adjust(left=0.2, right=0.9, top=0.9, bottom=0.1)\n",
    "\n",
    "# Add a legend with custom formatting\n",
    "legend = ax.legend(loc='upper right', fontsize=12)\n",
    "for i, text in enumerate(legend.get_texts()):\n",
    "    plt.setp(text, color=bar_colors[i], weight='bold')\n",
    "\n",
    "# Remove spines and set a grid\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.yaxis.grid(color='gray', linestyle='dashed')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}