feat(ingest/sql): auto extract and use mode query user metadata (data…

…hub-project#11307)

Co-authored-by: Harshal Sheth <[email protected]>

metadata-ingestion/src/datahub/emitter/mce_builder.py

@@ -50,7 +50,6 @@
     UpstreamLineageClass,
     _Aspect as AspectAbstract,
 )
-from datahub.metadata.urns import CorpGroupUrn, CorpUserUrn
 from datahub.utilities.urn_encoder import UrnEncoder
 from datahub.utilities.urns.data_flow_urn import DataFlowUrn
 from datahub.utilities.urns.dataset_urn import DatasetUrn
@@ -225,21 +224,6 @@ def make_user_urn(username: str) -> str:
     )
 
 
-def make_actor_urn(actor: str) -> Union[CorpUserUrn, CorpGroupUrn]:
-    """
-    Makes a user urn if the input is not a user or group urn already
-    """
-    return (
-        CorpUserUrn(actor)
-        if not actor.startswith(("urn:li:corpuser:", "urn:li:corpGroup:"))
-        else (
-            CorpUserUrn.from_string(actor)
-            if actor.startswith("urn:li:corpuser:")
-            else CorpGroupUrn.from_string(actor)
-        )
-    )
-
-
 def make_group_urn(groupname: str) -> str:
     """
     Makes a group urn if the input is not a user or group urn already

metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/queries_extractor.py

@@ -36,6 +36,7 @@
     BigQueryIdentifierBuilder,
 )
 from datahub.ingestion.source.usage.usage_common import BaseUsageConfig
+from datahub.metadata.urns import CorpUserUrn
 from datahub.sql_parsing.schema_resolver import SchemaResolver
 from datahub.sql_parsing.sql_parsing_aggregator import (
     ObservedQuery,
@@ -363,7 +364,9 @@ def _parse_audit_log_row(self, row: BigQueryJob) -> ObservedQuery:
             session_id=row["session_id"],
             timestamp=row["creation_time"],
             user=(
-                self.identifiers.gen_user_urn(row["user_email"])
+                CorpUserUrn.from_string(
+                    self.identifiers.gen_user_urn(row["user_email"])
+                )
                 if row["user_email"]
                 else None
             ),

metadata-ingestion/src/datahub/ingestion/source/redshift/lineage_v2.py

@@ -31,6 +31,7 @@
 from datahub.metadata.urns import DatasetUrn
 from datahub.sql_parsing.sql_parsing_aggregator import (
     KnownQueryLineageInfo,
+    ObservedQuery,
     SqlParsingAggregator,
 )
 from datahub.utilities.perf_timer import PerfTimer
@@ -118,11 +119,13 @@ def build(
         if self.config.resolve_temp_table_in_lineage:
             for temp_row in self._lineage_v1.get_temp_tables(connection=connection):
                 self.aggregator.add_observed_query(
-                    query=temp_row.query_text,
-                    default_db=self.database,
-                    default_schema=self.config.default_schema,
-                    session_id=temp_row.session_id,
-                    query_timestamp=temp_row.start_time,
+                    ObservedQuery(
+                        query=temp_row.query_text,
+                        default_db=self.database,
+                        default_schema=self.config.default_schema,
+                        session_id=temp_row.session_id,
+                        timestamp=temp_row.start_time,
+                    ),
                     # The "temp table" query actually returns all CREATE TABLE statements, even if they
                     # aren't explicitly a temp table. As such, setting is_known_temp_table=True
                     # would not be correct. We already have mechanisms to autodetect temp tables,
@@ -263,11 +266,13 @@ def _process_sql_parser_lineage(self, lineage_row: LineageRow) -> None:
         # TODO actor
 
         self.aggregator.add_observed_query(
-            query=ddl,
-            default_db=self.database,
-            default_schema=self.config.default_schema,
-            query_timestamp=lineage_row.timestamp,
-            session_id=lineage_row.session_id,
+            ObservedQuery(
+                query=ddl,
+                default_db=self.database,
+                default_schema=self.config.default_schema,
+                timestamp=lineage_row.timestamp,
+                session_id=lineage_row.session_id,
+            )
         )
 
     def _make_filtered_target(self, lineage_row: LineageRow) -> Optional[DatasetUrn]:

metadata-ingestion/src/datahub/sql_parsing/sql_parsing_aggregator.py

@@ -16,7 +16,7 @@
 import datahub.emitter.mce_builder as builder
 import datahub.metadata.schema_classes as models
 from datahub.configuration.time_window_config import get_time_bucket
-from datahub.emitter.mce_builder import get_sys_time, make_actor_urn, make_ts_millis
+from datahub.emitter.mce_builder import get_sys_time, make_ts_millis
 from datahub.emitter.mcp import MetadataChangeProposalWrapper
 from datahub.emitter.sql_parsing_builder import compute_upstream_fields
 from datahub.ingestion.api.closeable import Closeable
@@ -47,6 +47,10 @@
     get_query_fingerprint,
     try_format_query,
 )
+from datahub.sql_parsing.tool_meta_extractor import (
+    ToolMetaExtractor,
+    ToolMetaExtractorReport,
+)
 from datahub.utilities.cooperative_timeout import CooperativeTimeoutError
 from datahub.utilities.file_backed_collections import (
     ConnectionWrapper,
@@ -88,9 +92,16 @@ class LoggedQuery:
 
 
 @dataclasses.dataclass
-class ObservedQuery(LoggedQuery):
+class ObservedQuery:
+    query: str
+    session_id: Optional[str] = None
+    timestamp: Optional[datetime] = None
+    user: Optional[Union[CorpUserUrn, CorpGroupUrn]] = None
+    default_db: Optional[str] = None
+    default_schema: Optional[str] = None
     query_hash: Optional[str] = None
     usage_multiplier: int = 1
+
     # Use this to store addtitional key-value information about query for debugging
     extra_info: Optional[dict] = None
 
@@ -179,6 +190,8 @@ class PreparsedQuery:
     query_type_props: QueryTypeProps = dataclasses.field(
         default_factory=lambda: QueryTypeProps()
     )
+    # Use this to store addtitional key-value information about query for debugging
+    extra_info: Optional[dict] = None
 
 
 @dataclasses.dataclass
@@ -248,6 +261,9 @@ class SqlAggregatorReport(Report):
     num_operations_generated: int = 0
     num_operations_skipped_due_to_filters: int = 0
 
+    # Tool Metadata Extraction
+    tool_meta_report: Optional[ToolMetaExtractorReport] = None
+
     def compute_stats(self) -> None:
         self.schema_resolver_count = self._aggregator._schema_resolver.schema_count()
         self.num_unique_query_fingerprints = len(self._aggregator._query_map)
@@ -422,6 +438,10 @@ def __init__(
                 tablename="query_usage_counts",
             )
 
+        # Tool Extractor
+        self._tool_meta_extractor = ToolMetaExtractor()
+        self.report.tool_meta_report = self._tool_meta_extractor.report
+
     def close(self) -> None:
         self._exit_stack.close()
 
@@ -497,16 +517,7 @@ def add(
         elif isinstance(item, PreparsedQuery):
             self.add_preparsed_query(item)
         elif isinstance(item, ObservedQuery):
-            self.add_observed_query(
-                query=item.query,
-                default_db=item.default_db,
-                default_schema=item.default_schema,
-                session_id=item.session_id,
-                usage_multiplier=item.usage_multiplier,
-                query_timestamp=item.timestamp,
-                user=make_actor_urn(item.user) if item.user else None,
-                query_hash=item.query_hash,
-            )
+            self.add_observed_query(item)
         else:
             raise ValueError(f"Cannot add unknown item type: {type(item)}")
 
@@ -650,18 +661,9 @@ def add_view_definition(
 
     def add_observed_query(
         self,
-        query: str,
-        default_db: Optional[str] = None,
-        default_schema: Optional[str] = None,
-        query_timestamp: Optional[datetime] = None,
-        user: Optional[Union[CorpUserUrn, CorpGroupUrn]] = None,
-        session_id: Optional[
-            str
-        ] = None,  # can only see temp tables with the same session
-        usage_multiplier: int = 1,
+        observed: ObservedQuery,
         is_known_temp_table: bool = False,
         require_out_table_schema: bool = False,
-        query_hash: Optional[str] = None,
     ) -> None:
         """Add an observed query to the aggregator.
 
@@ -675,7 +677,7 @@ def add_observed_query(
         self.report.num_observed_queries += 1
 
         # All queries with no session ID are assumed to be part of the same session.
-        session_id = session_id or _MISSING_SESSION_ID
+        session_id = observed.session_id or _MISSING_SESSION_ID
 
         # Load in the temp tables for this session.
         schema_resolver: SchemaResolverInterface = (
@@ -685,17 +687,17 @@ def add_observed_query(
 
         # Run the SQL parser.
         parsed = self._run_sql_parser(
-            query,
-            default_db=default_db,
-            default_schema=default_schema,
+            observed.query,
+            default_db=observed.default_db,
+            default_schema=observed.default_schema,
             schema_resolver=schema_resolver,
             session_id=session_id,
-            timestamp=query_timestamp,
-            user=user,
+            timestamp=observed.timestamp,
+            user=observed.user,
         )
         if parsed.debug_info.error:
             self.report.observed_query_parse_failures.append(
-                f"{parsed.debug_info.error} on query: {query[:100]}"
+                f"{parsed.debug_info.error} on query: {observed.query[:100]}"
             )
         if parsed.debug_info.table_error:
             self.report.num_observed_queries_failed += 1
@@ -705,14 +707,14 @@ def add_observed_query(
             if isinstance(parsed.debug_info.column_error, CooperativeTimeoutError):
                 self.report.num_observed_queries_column_timeout += 1
 
-        query_fingerprint = query_hash or parsed.query_fingerprint
+        query_fingerprint = observed.query_hash or parsed.query_fingerprint
         self.add_preparsed_query(
             PreparsedQuery(
                 query_id=query_fingerprint,
-                query_text=query,
-                query_count=usage_multiplier,
-                timestamp=query_timestamp,
-                user=user,
+                query_text=observed.query,
+                query_count=observed.usage_multiplier,
+                timestamp=observed.timestamp,
+                user=observed.user,
                 session_id=session_id,
                 query_type=parsed.query_type,
                 query_type_props=parsed.query_type_props,
@@ -723,6 +725,7 @@ def add_observed_query(
                 column_usage=compute_upstream_fields(parsed),
                 inferred_schema=infer_output_schema(parsed),
                 confidence_score=parsed.debug_info.confidence,
+                extra_info=observed.extra_info,
             ),
             is_known_temp_table=is_known_temp_table,
             require_out_table_schema=require_out_table_schema,
@@ -738,6 +741,12 @@ def add_preparsed_query(
         session_has_temp_tables: bool = True,
         _is_internal: bool = False,
     ) -> None:
+
+        # Adding tool specific metadata extraction here allows it
+        # to work for both ObservedQuery and PreparsedQuery as
+        # add_preparsed_query it used within add_observed_query.
+        self._tool_meta_extractor.extract_bi_metadata(parsed)
+
         if not _is_internal:
             self.report.num_preparsed_queries += 1
 

metadata-ingestion/src/datahub/sql_parsing/tool_meta_extractor.py

@@ -0,0 +1,96 @@
+import json
+import logging
+from dataclasses import dataclass, field
+from typing import Callable, Dict, List, Optional, Tuple, Union
+
+from typing_extensions import Protocol
+
+from datahub.ingestion.api.report import Report
+from datahub.metadata.urns import CorpGroupUrn, CorpUserUrn
+from datahub.utilities.stats_collections import int_top_k_dict
+
+UrnStr = str
+
+logger = logging.getLogger(__name__)
+
+
+class QueryLog(Protocol):
+    """Represents Query Log Entry
+    expected by QueryMetaExractor interface
+    """
+
+    query_text: str
+    user: Optional[Union[CorpUserUrn, CorpGroupUrn]]
+    extra_info: Optional[dict]
+
+
+def _get_last_line(query: str) -> str:
+    return query.rstrip().rsplit("\n", maxsplit=1)[-1]
+
+
+@dataclass
+class ToolMetaExtractorReport(Report):
+    num_queries_meta_extracted: Dict[str, int] = field(default_factory=int_top_k_dict)
+
+
+class ToolMetaExtractor:
+    """Enriches input query log entry with tool-specific details captured as part of query log
+
+    Such as
+    - Queries executed on warehouse by Mode BI tool contain information of actual user interacting
+    with BI tool which is more useful as compared to service account used to execute query as reported
+    by warehouse query logs.
+    """
+
+    def __init__(self) -> None:
+        self.report = ToolMetaExtractorReport()
+        self.known_tool_extractors: List[Tuple[str, Callable[[QueryLog], bool]]] = [
+            (
+                "mode",
+                self._extract_mode_query,
+            )
+        ]
+
+    def _extract_mode_query(self, entry: QueryLog) -> bool:
+        """
+        Returns:
+            bool: whether QueryLog entry is that of mode and mode user info
+            is extracted into entry.
+        """
+        last_line = _get_last_line(entry.query_text)
+
+        if not (
+            last_line.startswith("--")
+            and '"url":"https://modeanalytics.com' in last_line
+        ):
+            return False
+
+        mode_json_raw = last_line[2:]
+        mode_json = json.loads(mode_json_raw)
+
+        original_user = entry.user
+
+        entry.user = email_to_user_urn(mode_json["email"])
+        entry.extra_info = entry.extra_info or {}
+        entry.extra_info["user_via"] = original_user
+
+        # TODO: Generate an "origin" urn.
+
+        return True
+
+    def extract_bi_metadata(self, entry: QueryLog) -> bool:
+
+        for tool, meta_extractor in self.known_tool_extractors:
+            try:
+                if meta_extractor(entry):
+                    self.report.num_queries_meta_extracted[tool] += 1
+                    return True
+            except Exception:
+                logger.debug("Tool metadata extraction failed with error : {e}")
+        return False
+
+
+# NOTE: This is implementing the most common user urn generation scenario
+# however may need to be revisited at later point
+def email_to_user_urn(email: str) -> CorpUserUrn:
+    return CorpUserUrn(email.split("@", 1)[0])