Pub/Sub to Avro Files on Cloud Storage template

The Pub/Sub to Avro files on Cloud Storage template is a streaming pipeline that reads data from a Pub/Sub topic and writes Avro files into the specified Cloud Storage bucket.

Pipeline requirements

The input Pub/Sub topic must exist prior to pipeline execution.

Template parameters

Required parameters

inputTopic : The Pub/Sub topic to subscribe to for message consumption. The topic name must be in the format projects/<PROJECT_ID>/topics/<TOPIC_NAME>.
outputDirectory : The output directory where output Avro files are archived. Must contain / at the end. For example: gs://example-bucket/example-directory/.
avroTempDirectory : The directory for temporary Avro files. Must contain / at the end. For example: gs://example-bucket/example-directory/.

Optional parameters

outputFilenamePrefix : The output filename prefix for the Avro files. Defaults to: output.
outputFilenameSuffix : The output filename suffix for the Avro files. Defaults to empty.
outputShardTemplate : The shard template defines the dynamic portion of each windowed file. By default, the pipeline uses a single shard for output to the file system within each window. Therefore, all data outputs into a single file per window. The outputShardTemplate defaults to W-P-SS-of-NN, where W is the window date range, P is the pane info, S is the shard number, and N is the number of shards. In case of a single file, the SS-of-NN portion of the outputShardTemplate is 00-of-01.
yearPattern : Pattern for formatting the year. Must be one or more of y or Y. Case makes no difference in the year. Optionally, wrap the pattern with characters that aren't alphanumeric or the directory ('/') character. Defaults to YYYY.
monthPattern : Pattern for formatting the month. Must be one or more of the M character. Optionally, wrap the pattern with characters that aren't alphanumeric or the directory ('/') character. Defaults to MM.
dayPattern : Pattern for formatting the day. Must be one or more of d for day of month or D for day of year. Optionally, wrap the pattern with characters that aren't alphanumeric or the directory ('/') character. Defaults to dd.
hourPattern : Pattern for formatting the hour. Must be one or more of the H character. Optionally, wrap the pattern with characters that aren't alphanumeric or the directory ('/') character. Defaults to HH.
minutePattern : Pattern for formatting the minute. Must be one or more of the m character. Optionally, wrap the pattern with characters that aren't alphanumeric or the directory ('/') character. Defaults to mm.

Run the template

Console

Go to the Dataflow Create job from template page.

Go to Create job from template

In the Job name field, enter a unique job name.
Optional: For Regional endpoint, select a value from the drop-down menu. The default region is us-central1.
For a list of regions where you can run a Dataflow job, see Dataflow locations.
From the Dataflow template drop-down menu, select the Pub/Sub to Avro Files on Cloud Storage template.
In the provided parameter fields, enter your parameter values.
Click Run job.

gcloud

In your shell or terminal, run the template:

gcloud dataflow jobs run JOB_NAME \
    --gcs-location gs://dataflow-templates-REGION_NAME/VERSION/Cloud_PubSub_to_Avro \
    --region REGION_NAME \
    --staging-location STAGING_LOCATION \
    --parameters \
inputTopic=projects/PROJECT_ID/topics/TOPIC_NAME,\
outputDirectory=gs://BUCKET_NAME/output/,\
outputFilenamePrefix=FILENAME_PREFIX,\
outputFilenameSuffix=FILENAME_SUFFIX,\
outputShardTemplate=SHARD_TEMPLATE,\
avroTempDirectory=gs://BUCKET_NAME/temp/

Replace the following:

JOB_NAME: a unique job name of your choice
REGION_NAME: the region where you want to deploy your Dataflow job—for example, us-central1
VERSION: the version of the template that you want to use
You can use the following values:
- latest to use the latest version of the template, which is available in the non-dated parent folder in the bucket— gs://dataflow-templates-REGION_NAME/latest/
- the version name, like 2023-09-12-00_RC00, to use a specific version of the template, which can be found nested in the respective dated parent folder in the bucket— gs://dataflow-templates-REGION_NAME/
Caution: The latest version of templates might update with breaking changes. Your production environments should use templates kept in the most recent dated parent folder to prevent these breaking changes from affecting your production workflows.
STAGING_LOCATION: the location for staging local files (for example, gs://your-bucket/staging)
TOPIC_NAME: the Pub/Sub topic name
BUCKET_NAME: the name of your Cloud Storage bucket
FILENAME_PREFIX: the preferred output filename prefix
FILENAME_SUFFIX: the preferred output filename suffix
SHARD_TEMPLATE: the preferred output shard template

API

To run the template using the REST API, send an HTTP POST request. For more information on the API and its authorization scopes, see projects.templates.launch.

POST https://dataflow.googleapis.com/v1b3/projects/PROJECT_ID/locations/LOCATION/templates:launch?gcsPath=gs://dataflow-templates-LOCATION/VERSION/Cloud_PubSub_to_Avro
{
   "jobName": "JOB_NAME",
   "environment": {
       "ipConfiguration": "WORKER_IP_UNSPECIFIED",
       "additionalExperiments": []
    },
   "parameters": {
       "inputTopic": "projects/PROJECT_ID/topics/TOPIC_NAME",
       "outputDirectory": "gs://BUCKET_NAME/output/",
       "avroTempDirectory": "gs://BUCKET_NAME/temp/",
       "outputFilenamePrefix": "FILENAME_PREFIX",
       "outputFilenameSuffix": "FILENAME_SUFFIX",
       "outputShardTemplate": "SHARD_TEMPLATE"
   }
}

Replace the following:

PROJECT_ID: the Google Cloud project ID where you want to run the Dataflow job
JOB_NAME: a unique job name of your choice
LOCATION: the region where you want to deploy your Dataflow job—for example, us-central1
VERSION: the version of the template that you want to use
You can use the following values:
- latest to use the latest version of the template, which is available in the non-dated parent folder in the bucket— gs://dataflow-templates-REGION_NAME/latest/
- the version name, like 2023-09-12-00_RC00, to use a specific version of the template, which can be found nested in the respective dated parent folder in the bucket— gs://dataflow-templates-REGION_NAME/
Caution: The latest version of templates might update with breaking changes. Your production environments should use templates kept in the most recent dated parent folder to prevent these breaking changes from affecting your production workflows.
STAGING_LOCATION: the location for staging local files (for example, gs://your-bucket/staging)
TOPIC_NAME: the Pub/Sub topic name
BUCKET_NAME: the name of your Cloud Storage bucket
FILENAME_PREFIX: the preferred output filename prefix
FILENAME_SUFFIX: the preferred output filename suffix
SHARD_TEMPLATE: the preferred output shard template

Template source code

Java

/*
 * Copyright (C) 2018 Google LLC
 *
 * Licensed 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 com.google.cloud.teleport.templates;

import com.google.cloud.teleport.avro.AvroPubsubMessageRecord;
import com.google.cloud.teleport.io.WindowedFilenamePolicy;
import com.google.cloud.teleport.metadata.Template;
import com.google.cloud.teleport.metadata.TemplateCategory;
import com.google.cloud.teleport.metadata.TemplateCreationParameter;
import com.google.cloud.teleport.metadata.TemplateParameter;
import com.google.cloud.teleport.options.WindowedFilenamePolicyOptions;
import com.google.cloud.teleport.templates.PubsubToAvro.Options;
import com.google.cloud.teleport.util.DurationUtils;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.PipelineResult;
import org.apache.beam.sdk.extensions.avro.io.AvroIO;
import org.apache.beam.sdk.io.FileBasedSink;
import org.apache.beam.sdk.io.fs.ResourceId;
import org.apache.beam.sdk.io.gcp.pubsub.PubsubIO;
import org.apache.beam.sdk.io.gcp.pubsub.PubsubMessage;
import org.apache.beam.sdk.options.Default;
import org.apache.beam.sdk.options.Description;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.options.Validation.Required;
import org.apache.beam.sdk.options.ValueProvider;
import org.apache.beam.sdk.options.ValueProvider.NestedValueProvider;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.transforms.SerializableFunction;
import org.apache.beam.sdk.transforms.windowing.FixedWindows;
import org.apache.beam.sdk.transforms.windowing.Window;
import org.apache.beam.sdk.values.PCollection;

/**
 * This pipeline ingests incoming data from a Cloud Pub/Sub topic and outputs the raw data into
 * windowed Avro files at the specified output directory.
 *
 * <p>Files output will have the following schema:
 *
 * <pre>
 *   {
 *      "type": "record",
 *      "name": "AvroPubsubMessageRecord",
 *      "namespace": "com.google.cloud.teleport.avro",
 *      "fields": [
 *        {"name": "message", "type": {"type": "array", "items": "bytes"}},
 *        {"name": "attributes", "type": {"type": "map", "values": "string"}},
 *        {"name": "timestamp", "type": "long"}
 *      ]
 *   }
 * </pre>
 *
 * <p>Check out <a
 * href="https://github.com/GoogleCloudPlatform/DataflowTemplates/blob/main/v1/README_Cloud_PubSub_to_Avro.md">README</a>
 * for instructions on how to use or modify this template.
 */
@Template(
    name = "Cloud_PubSub_to_Avro",
    category = TemplateCategory.STREAMING,
    displayName = "Pub/Sub to Avro Files on Cloud Storage",
    description =
        "The Pub/Sub to Avro files on Cloud Storage template is a streaming pipeline that reads data from a Pub/Sub "
            + "topic and writes Avro files into the specified Cloud Storage bucket.",
    optionsClass = Options.class,
    skipOptions = "inputSubscription",
    documentation =
        "https://cloud.google.com/dataflow/docs/guides/templates/provided/pubsub-to-avro",
    contactInformation = "https://cloud.google.com/support",
    requirements = {"The input Pub/Sub topic must exist prior to pipeline execution."},
    streaming = true,
    supportsAtLeastOnce = true)
public class PubsubToAvro {

  /**
   * Options supported by the pipeline.
   *
   * <p>Inherits standard configuration options.
   */
  public interface Options
      extends PipelineOptions, StreamingOptions, WindowedFilenamePolicyOptions {
    @TemplateParameter.PubsubSubscription(
        order = 1,
        description = "Pub/Sub input subscription",
        helpText =
            "Pub/Sub subscription to read the input from, in the format of"
                + " 'projects/your-project-id/subscriptions/your-subscription-name'",
        example = "projects/your-project-id/subscriptions/your-subscription-name")
    ValueProvider<String> getInputSubscription();

    void setInputSubscription(ValueProvider<String> value);

    @TemplateParameter.PubsubTopic(
        order = 2,
        description = "Pub/Sub input topic",
        helpText =
            "The Pub/Sub topic to subscribe to for message consumption. The topic name must be in the format projects/<PROJECT_ID>/topics/<TOPIC_NAME>.")
    ValueProvider<String> getInputTopic();

    void setInputTopic(ValueProvider<String> value);

    @TemplateCreationParameter(value = "false")
    @Description(
        "This determines whether the template reads from " + "a pub/sub subscription or a topic")
    @Default.Boolean(false)
    Boolean getUseSubscription();

    void setUseSubscription(Boolean value);

    @TemplateParameter.GcsWriteFolder(
        order = 4,
        description = "Output file directory in Cloud Storage",
        helpText =
            "The output directory where output Avro files are archived. Must contain / at the end. For example: gs://example-bucket/example-directory/")
    @Required
    ValueProvider<String> getOutputDirectory();

    void setOutputDirectory(ValueProvider<String> value);

    @TemplateParameter.Text(
        order = 5,
        optional = true,
        description = "Output filename prefix of the files to write",
        helpText = "The output filename prefix for the Avro files.",
        regexes = "^[a-zA-Z\\-]+$")
    @Default.String("output")
    ValueProvider<String> getOutputFilenamePrefix();

    void setOutputFilenamePrefix(ValueProvider<String> value);

    @TemplateParameter.Text(
        order = 6,
        optional = true,
        description = "Output filename suffix of the files to write",
        helpText = "The output filename suffix for the Avro files.")
    @Default.String("")
    ValueProvider<String> getOutputFilenameSuffix();

    void setOutputFilenameSuffix(ValueProvider<String> value);

    @TemplateParameter.GcsWriteFolder(
        order = 7,
        description = "Temporary Avro write directory",
        helpText =
            "The directory for temporary Avro files. Must contain / at the end. For example: gs://example-bucket/example-directory/.")
    @Required
    ValueProvider<String> getAvroTempDirectory();

    void setAvroTempDirectory(ValueProvider<String> value);
  }

  /**
   * Main entry point for executing the pipeline.
   *
   * @param args The command-line arguments to the pipeline.
   */
  public static void main(String[] args) {

    Options options = PipelineOptionsFactory.fromArgs(args).withValidation().as(Options.class);
    options.setStreaming(true);

    run(options);
  }

  /**
   * Runs the pipeline with the supplied options.
   *
   * @param options The execution parameters to the pipeline.
   * @return The result of the pipeline execution.
   */
  public static PipelineResult run(Options options) {
    // Create the pipeline
    Pipeline pipeline = Pipeline.create(options);

    PCollection<PubsubMessage> messages = null;

    /*
     * Steps:
     *   1) Read messages from PubSub
     *   2) Window the messages into minute intervals specified by the executor.
     *   3) Output the windowed data into Avro files, one per window by default.
     */

    if (options.getUseSubscription()) {
      messages =
          pipeline.apply(
              "Read PubSub Events",
              PubsubIO.readMessagesWithAttributes()
                  .fromSubscription(options.getInputSubscription()));
    } else {
      messages =
          pipeline.apply(
              "Read PubSub Events",
              PubsubIO.readMessagesWithAttributes().fromTopic(options.getInputTopic()));
    }
    messages
        .apply("Map to Archive", ParDo.of(new PubsubMessageToArchiveDoFn()))
        .apply(
            options.getWindowDuration() + " Window",
            Window.into(FixedWindows.of(DurationUtils.parseDuration(options.getWindowDuration()))))

        // Apply windowed file writes. Use a NestedValueProvider because the filename
        // policy requires a resourceId generated from the input value at runtime.
        .apply(
            "Write File(s)",
            AvroIO.write(AvroPubsubMessageRecord.class)
                .to(
                    WindowedFilenamePolicy.writeWindowedFiles()
                        .withOutputDirectory(options.getOutputDirectory())
                        .withOutputFilenamePrefix(options.getOutputFilenamePrefix())
                        .withShardTemplate(options.getOutputShardTemplate())
                        .withSuffix(options.getOutputFilenameSuffix())
                        .withYearPattern(options.getYearPattern())
                        .withMonthPattern(options.getMonthPattern())
                        .withDayPattern(options.getDayPattern())
                        .withHourPattern(options.getHourPattern())
                        .withMinutePattern(options.getMinutePattern()))
                .withTempDirectory(
                    NestedValueProvider.of(
                        options.getAvroTempDirectory(),
                        (SerializableFunction<String, ResourceId>)
                            input -> FileBasedSink.convertToFileResourceIfPossible(input)))
                /*.withTempDirectory(FileSystems.matchNewResource(
                options.getAvroTempDirectory(),
                Boolean.TRUE))
                */
                .withWindowedWrites()
                .withNumShards(options.getNumShards()));

    // Execute the pipeline and return the result.
    return pipeline.run();
  }

  /**
   * Converts an incoming {@link PubsubMessage} to the {@link AvroPubsubMessageRecord} class by
   * copying its fields and the timestamp of the message.
   */
  static class PubsubMessageToArchiveDoFn extends DoFn<PubsubMessage, AvroPubsubMessageRecord> {
    @ProcessElement
    public void processElement(ProcessContext context) {
      PubsubMessage message = context.element();
      context.output(
          new AvroPubsubMessageRecord(
              message.getPayload(), message.getAttributeMap(), context.timestamp().getMillis()));
    }
  }
}

What's next

Learn about Dataflow templates.
See the list of Google-provided templates.