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Add Managed Iceberg example #32678

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4 changes: 4 additions & 0 deletions examples/java/build.gradle
Original file line number Diff line number Diff line change
Expand Up @@ -66,6 +66,8 @@ dependencies {
implementation project(":sdks:java:extensions:python")
implementation project(":sdks:java:io:google-cloud-platform")
implementation project(":sdks:java:io:kafka")
runtimeOnly project(":sdks:java:io:iceberg")
implementation project(":sdks:java:managed")
implementation project(":sdks:java:extensions:ml")
implementation library.java.avro
implementation library.java.bigdataoss_util
Expand Down Expand Up @@ -100,6 +102,8 @@ dependencies {
implementation "org.apache.httpcomponents:httpcore:4.4.13"
implementation "com.fasterxml.jackson.core:jackson-annotations:2.14.1"
implementation "com.fasterxml.jackson.core:jackson-core:2.14.1"
runtimeOnly library.java.hadoop_client
runtimeOnly library.java.bigdataoss_gcs_connector
testImplementation project(path: ":runners:direct-java", configuration: "shadow")
testImplementation project(":sdks:java:io:google-cloud-platform")
testImplementation project(":sdks:java:extensions:ml")
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,119 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.beam.examples.cookbook;

import java.util.Arrays;
import java.util.Map;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.extensions.gcp.options.GcpOptions;
import org.apache.beam.sdk.io.gcp.pubsub.PubsubIO;
import org.apache.beam.sdk.managed.Managed;
import org.apache.beam.sdk.options.Default;
import org.apache.beam.sdk.options.Description;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.options.Validation;
import org.apache.beam.sdk.schemas.Schema;
import org.apache.beam.sdk.schemas.transforms.Filter;
import org.apache.beam.sdk.transforms.JsonToRow;
import org.apache.beam.sdk.values.Row;
import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.ImmutableMap;

/**
* Reads real-time NYC taxi ride information from {@code
* projects/pubsub-public-data/topics/taxirides-realtime} and writes to Iceberg tables using Beam's
* {@link Managed} IcebergIO sink.
*
* <p>This is a streaming pipeline that writes records to Iceberg tables dynamically, depending on
* each record's passenger count. New tables are created as needed. We set a triggering frequency of
* 10s; at around this interval, the sink will accumulate records and write them to the appropriate
* table, creating a new snapshot each time.
*/
public class IcebergTaxiExamples {
private static final String TAXI_RIDES_TOPIC =
"projects/pubsub-public-data/topics/taxirides-realtime";
private static final Schema TAXI_RIDE_INFO_SCHEMA =
Schema.builder()
.addStringField("ride_id")
.addInt32Field("point_idx")
.addDoubleField("latitude")
.addDoubleField("longitude")
.addStringField("timestamp")
.addDoubleField("meter_reading")
.addDoubleField("meter_increment")
.addStringField("ride_status")
.addInt32Field("passenger_count")
.build();

public static void main(String[] args) {
IcebergPipelineOptions options =
PipelineOptionsFactory.fromArgs(args).as(IcebergPipelineOptions.class);
options.setProject("apache-beam-testing");

// each record's 'passenger_count' value will be substituted in to determine
// its final table destination
// e.g. an event with 3 passengers will be written to 'iceberg_taxi.3_passengers'
String tableIdentifierTemplate = "iceberg_taxi.{passenger_count}_passengers";

Map<String, String> catalogProps =
ImmutableMap.<String, String>builder()
.put("catalog-impl", options.getCatalogImpl())
.put("warehouse", options.getWarehouse())
.build();
Map<String, Object> icebergWriteConfig =
ImmutableMap.<String, Object>builder()
.put("table", tableIdentifierTemplate)
.put("catalog_name", options.getCatalogName())
.put("catalog_properties", catalogProps)
.put("triggering_frequency_seconds", 10)
// perform a final filter to only write these two columns
.put("keep", Arrays.asList("ride_id", "meter_reading"))
.build();

Pipeline p = Pipeline.create(options);
p
// Read taxi ride data
.apply(PubsubIO.readStrings().fromTopic(TAXI_RIDES_TOPIC))
// Convert JSON strings to Beam Rows
.apply(JsonToRow.withSchema(TAXI_RIDE_INFO_SCHEMA))
// Filter to only include drop-offs
.apply(Filter.<Row>create().whereFieldName("ride_status", "dropoff"::equals))
// Write to Iceberg tables
.apply(Managed.write(Managed.ICEBERG).withConfig(icebergWriteConfig));
p.run();
}

public interface IcebergPipelineOptions extends GcpOptions {
@Description("Warehouse location where the table's data will be written to.")
@Default.String("gs://apache-beam-samples/iceberg-examples")
String getWarehouse();

void setWarehouse(String warehouse);

@Description("Fully-qualified name of the catalog class to use.")
@Default.String("org.apache.iceberg.hadoop.HadoopCatalog")
String getCatalogImpl();

void setCatalogImpl(String catalogName);

@Validation.Required
@Default.String("example-catalog")
String getCatalogName();

void setCatalogName(String catalogName);
}
}
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