Google-provided utility templates

Google provides a set of open-source Cloud Dataflow templates. For general information about templates, see the Overview page. For a list of all Google-provided templates, see the Get started with Google-provided templates page.

This page documents utility templates:

Bulk Compress Cloud Storage Files
Bulk Decompress Cloud Storage Files
Cloud Datastore Bulk Delete

Bulk Compress Cloud Storage Files

The Bulk Compress Cloud Storage Files template is a batch pipeline that compresses files on Cloud Storage to a specified location. This template can be useful when you need to compress large batches of files as part of a periodic archival process. The supported compression modes are: BZIP2, DEFLATE, GZIP, ZIP. Files output to the destination location will follow a naming schema of original filename appended with the compression mode extension. The extensions appended will be one of: .bzip2, .deflate, .gz, .zip.

Any errors which occur during the compression process will be output to the failure file in CSV format of filename, error message. If no failures occur during execution, the error file will still be created but will contain no error records.

Requirements for this pipeline:

The compression must be in one of the following formats: BZIP2, DEFLATE, GZIP, ZIP.
The output directory must exist prior to pipeline execution.

Template parameters

Parameter	Description
`inputFilePattern`	The input file pattern to read from. For example, `gs://bucket-name/uncompressed/*.txt`.
`outputDirectory`	The output location to write to. For example, `gs://bucket-name/compressed/`.
`outputFailureFile`	The error log output file to use for write failures that occur during the compression process. For example, `gs://bucket-name/compressed/failed.csv`. If there are no failures, the file is still created but will be empty. The file contents are in CSV format (Filename, Error) and consist of one line for each file that fails compression.
`compression`	The compression algorithm used to compress the matched files. Must be one of: `BZIP2`, `DEFLATE`, `GZIP`, `ZIP`

Executing the Bulk Compress Cloud Storage Files template

CONSOLE

Execute from the Google Cloud Platform Console

Go to the Cloud Dataflow page in the GCP Console.

Go to the Cloud Dataflow page

Click Create job from template.

Select the Bulk Compress Cloud Storage Files template from the Cloud Dataflow template drop-down menu.
Enter a job name in the Job Name field. Your job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Enter your parameter values in the provided parameter fields.
Click Run Job.

GCLOUD

Execute from the gcloud command-line tool

Note: To use the gcloud command-line tool to execute templates, you must have Cloud SDK version 138.0.0 or higher.

You must replace the following values in this example:

Replace YOUR_PROJECT_ID with your project ID.
Replace JOB_NAME with a job name of your choice. The job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Replace YOUR_BUCKET_NAME with the name of your Cloud Storage bucket.
Replace COMPRESSION with your choice of compression algorithm.

gcloud dataflow jobs run JOB_NAME \
    --gcs-location gs://dataflow-templates/latest/Bulk_Compress_GCS_Files \
    --parameters \
inputFilePattern=gs://YOUR_BUCKET_NAME/uncompressed/*.txt,\
outputDirectory=gs://YOUR_BUCKET_NAME/compressed,\
outputFailureFile=gs://YOUR_BUCKET_NAME/failed/failure.csv,\
compression=COMPRESSION

API

Execute from the REST API

When executing this template, you'll need the Cloud Storage path to the template:

gs://dataflow-templates/VERSION/Bulk_Compress_GCS_Files

To execute this template with a REST API request, send an HTTP POST request with your project ID. This request requires authorization.

You must replace the following values in this example:

Replace YOUR_PROJECT_ID with your project ID.
Replace JOB_NAME with a job name of your choice. The job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Replace YOUR_BUCKET_NAME with the name of your Cloud Storage bucket.
Replace COMPRESSION with your choice of compression algorithm.

POST https://dataflow.googleapis.com/v1b3/projects/YOUR_PROJECT_ID/templates:launch?gcsPath=gs://dataflow-templates/latest/Bulk_Compress_GCS_Files
{
   "jobName": "JOB_NAME",
   "parameters": {
       "inputFilePattern": "gs://YOUR_BUCKET_NAME/uncompressed/*.txt",
       "outputDirectory": "gs://YOUR_BUCKET_NAME/compressed",
       "outputFailureFile": "gs://YOUR_BUCKET_NAME/failed/failure.csv",
       "compression": "COMPRESSION"
   },
   "environment": { "zone": "us-central1-f" }
}

Template source code

Java

View on GitHub Feedback

/*
 * Copyright (C) 2018 Google Inc.
 *
 * 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.common.collect.ImmutableList;
import com.google.common.io.ByteStreams;
import java.io.IOException;
import java.nio.channels.ReadableByteChannel;
import java.nio.channels.WritableByteChannel;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.PipelineResult;
import org.apache.beam.sdk.io.Compression;
import org.apache.beam.sdk.io.FileIO;
import org.apache.beam.sdk.io.FileSystems;
import org.apache.beam.sdk.io.TextIO;
import org.apache.beam.sdk.io.fs.MatchResult;
import org.apache.beam.sdk.io.fs.ResolveOptions.StandardResolveOptions;
import org.apache.beam.sdk.io.fs.ResourceId;
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.Validation.Required;
import org.apache.beam.sdk.options.ValueProvider;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.MapElements;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.util.MimeTypes;
import org.apache.beam.sdk.values.KV;
import org.apache.beam.sdk.values.PCollectionTuple;
import org.apache.beam.sdk.values.TupleTag;
import org.apache.beam.sdk.values.TupleTagList;
import org.apache.beam.sdk.values.TypeDescriptors;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * The {@link BulkCompressor} is a batch pipeline that compresses files on matched by an input file
 * pattern and outputs them to a specified file location. This pipeline can be useful when you need
 * to compress large batches of files as part of a perodic archival process. The supported
 * compression modes are: <code>BZIP2</code>, <code>DEFLATE</code>, <code>GZIP</code>, <code>ZIP
 * </code>. Files output to the destination location will follow a naming schema of original
 * filename appended with the compression mode extension. The extensions appended will be one of:
 * <code>.bzip2</code>, <code>.deflate</code>, <code>.gz</code>, <code>.zip</code> as determined by
 * the compression type.
 *
 * <p>Any errors which occur during the compression process will be output to the failure file in
 * CSV format of filename, error message. If no failures occur during execution, the error file will
 * still be created but will contain no error records.
 *
 * <p><b>Pipeline Requirements</b>
 *
 * <ul>
 *   <li>The compression must be in one of the following formats: <code>BZIP2</code>, <code>DEFLATE
 *       </code>, <code>GZIP</code>, <code>ZIP</code>.
 *   <li>The output directory must exist prior to pipeline execution.
 * </ul>
 *
 * <p><b>Example Usage</b>
 *
 * <pre>
 * # Set the pipeline vars
 * PROJECT_ID=PROJECT ID HERE
 * PIPELINE_FOLDER=gs://${PROJECT_ID}/dataflow/pipelines/bulk-compressor
 *
 * # Set the runner
 * RUNNER=DataflowRunner
 *
 * # Build the template
 * mvn compile exec:java \
 * -Dexec.mainClass=com.google.cloud.teleport.templates.BulkCompressor \
 * -Dexec.cleanupDaemonThreads=false \
 * -Dexec.args=" \
 * --project=${PROJECT_ID} \
 * --stagingLocation=${PIPELINE_FOLDER}/staging \
 * --tempLocation=${PIPELINE_FOLDER}/temp \
 * --templateLocation=${PIPELINE_FOLDER}/template \
 * --runner=${RUNNER}"
 *
 * # Execute the template
 * JOB_NAME=bulk-compressor-$USER-`date +"%Y%m%d-%H%M%S%z"`
 *
 * gcloud dataflow jobs run ${JOB_NAME} \
 * --gcs-location=${PIPELINE_FOLDER}/template \
 * --zone=us-east1-d \
 * --parameters \
 * "inputFilePattern=${PIPELINE_FOLDER}/test/uncompressed/*,\
 * outputDirectory=${PIPELINE_FOLDER}/test/compressed,\
 * outputFailureFile=${PIPELINE_FOLDER}/test/failure/failed-${JOB_NAME}.csv,\
 * compression=GZIP"
 * </pre>
 */
public class BulkCompressor {

  /** The logger to output status messages to. */
  private static final Logger LOG = LoggerFactory.getLogger(BulkCompressor.class);

  /** The tag used to identify the main output of the {@link Compressor}. */
  private static final TupleTag<String> COMPRESSOR_MAIN_OUT = new TupleTag<String>() {};

  /** The tag used to identify the dead-letter output of the {@link Compressor}. */
  private static final TupleTag<KV<String, String>> DEADLETTER_TAG =
      new TupleTag<KV<String, String>>() {};

  /**
   * The {@link Options} class provides the custom execution options passed by the executor at the
   * command-line.
   */
  public interface Options extends PipelineOptions {
    @Description("The input file pattern to read from (e.g. gs://bucket-name/uncompressed/*.gz)")
    @Required
    ValueProvider<String> getInputFilePattern();

    void setInputFilePattern(ValueProvider<String> value);

    @Description("The output location to write to (e.g. gs://bucket-name/compressed)")
    @Required
    ValueProvider<String> getOutputDirectory();

    void setOutputDirectory(ValueProvider<String> value);

    @Description(
        "The output file to write failures during the compression process "
            + "(e.g. gs://bucket-name/compressed/failed.txt). The contents will be one line for "
            + "each file which failed compression. Note that this parameter will "
            + "allow the pipeline to continue processing in the event of a failure.")
    @Required
    ValueProvider<String> getOutputFailureFile();

    void setOutputFailureFile(ValueProvider<String> value);

    @Description("The compression algorithm to use on the matched files.")
    @Required
    ValueProvider<Compression> getCompression();

    void setCompression(ValueProvider<Compression> value);
  }

  /**
   * The main entry-point for pipeline execution. This method will start the pipeline but will not
   * wait for it's execution to finish. If blocking execution is required, use the {@link
   * BulkCompressor#run(Options)} method to start the pipeline and invoke {@code
   * result.waitUntilFinish()} on the {@link PipelineResult}.
   *
   * @param args The command-line args passed by the executor.
   */
  public static void main(String[] args) {
    Options options = PipelineOptionsFactory.fromArgs(args).withValidation().as(Options.class);

    run(options);
  }

  /**
   * Runs the pipeline to completion with the specified options. This method does not wait until the
   * pipeline is finished before returning. Invoke {@code result.waitUntilFinish()} on the result
   * object to block until the pipeline is finished running if blocking programmatic execution is
   * required.
   *
   * @param options The execution options.
   * @return The pipeline result.
   */
  public static PipelineResult run(Options options) {

    // Create the pipeline
    Pipeline pipeline = Pipeline.create(options);

    /*
     * Steps:
     *   1) Find all files matching the input pattern
     *   2) Compress the files found and output them to the output directory
     *   3) Write any errors to the failure output file
     */
    PCollectionTuple compressOut =
        pipeline
            .apply("Match File(s)", FileIO.match().filepattern(options.getInputFilePattern()))
            .apply(
                "Compress File(s)",
                ParDo.of(new Compressor(options.getOutputDirectory(), options.getCompression()))
                    .withOutputTags(COMPRESSOR_MAIN_OUT, TupleTagList.of(DEADLETTER_TAG)));

    compressOut
        .get(DEADLETTER_TAG)
        .apply(
            "Format Errors",
            MapElements.into(TypeDescriptors.strings())
                .via(kv -> String.format("%s,%s", kv.getKey(), kv.getValue())))
        .apply(
            "Write Error File",
            TextIO.write()
                .to(options.getOutputFailureFile())
                .withHeader("Filename,Error")
                .withoutSharding());

    return pipeline.run();
  }

  /**
   * The {@link Compressor} accepts {@link MatchResult.Metadata} from the FileSystems API and
   * compresses each file to an output location. Any compression failures which occur during
   * execution will be output to a separate output for further processing.
   */
  @SuppressWarnings("serial")
  public static class Compressor extends DoFn<MatchResult.Metadata, String> {

    private final ValueProvider<String> destinationLocation;
    private final ValueProvider<Compression> compressionValue;

    Compressor(ValueProvider<String> destinationLocation, ValueProvider<Compression> compression) {
      this.destinationLocation = destinationLocation;
      this.compressionValue = compression;
    }

    @ProcessElement
    public void processElement(ProcessContext context) {
      ResourceId inputFile = context.element().resourceId();
      Compression compression = compressionValue.get();

      // Add the compression extension to the output filename. Example: demo.txt -> demo.txt.gz
      String outputFilename = inputFile.getFilename() + compression.getSuggestedSuffix();

      // Resolve the necessary resources to perform the transfer
      ResourceId outputDir = FileSystems.matchNewResource(destinationLocation.get(), true);
      ResourceId outputFile =
          outputDir.resolve(outputFilename, StandardResolveOptions.RESOLVE_FILE);
      ResourceId tempFile =
          outputDir.resolve("temp-" + outputFilename, StandardResolveOptions.RESOLVE_FILE);

      // Perform the copy of the compressed channel to the destination.
      try (ReadableByteChannel readerChannel = FileSystems.open(inputFile)) {
        try (WritableByteChannel writerChannel =
            compression.writeCompressed(FileSystems.create(tempFile, MimeTypes.BINARY))) {

          // Execute the copy to the temporary file
          ByteStreams.copy(readerChannel, writerChannel);
        }

        // Rename the temporary file to the output file
        FileSystems.rename(ImmutableList.of(tempFile), ImmutableList.of(outputFile));

        // Output the path to the uncompressed file
        context.output(outputFile.toString());
      } catch (IOException e) {
        LOG.error("Error occurred during compression of {}", inputFile.toString(), e);
        context.output(DEADLETTER_TAG, KV.of(inputFile.toString(), e.getMessage()));
      }
    }
  }
}

Python

Python source code is not available.

Bulk Decompress Cloud Storage Files

The Bulk Decompress Cloud Storage Files template is a batch pipeline that decompresses files on Cloud Storage to a specified location. This functionality is useful when you want to use compressed data to minimize network bandwidth costs during a migration, but would like to maximize analytical processing speed by operating on uncompressed data after migration. The pipeline automatically handles multiple compression modes during a single execution and determines the decompression mode to use based on the file extension (.bzip2, .deflate, .gz, .zip).

Requirements for this pipeline:

The files to decompress must be in one of the following formats: Bzip2, Deflate, Gzip, Zip.
The output directory must exist prior to pipeline execution.

Template parameters

Parameter	Description
`inputFilePattern`	The input file pattern to read from. For example, `gs://bucket-name/compressed/*.gz`.
`outputDirectory`	The output location to write to. For example, `gs://bucket-name/decompressed`.
`outputFailureFile`	The error log output file to use for write failures that occur during the decompression process. For example, `gs://bucket-name/decompressed/failed.csv`. If there are no failures, the file is still created but will be empty. The file contents are in CSV format (Filename, Error) and consist of one line for each file that fails decompression.

Executing the Bulk Decompress Cloud Storage Files template

CONSOLE

Execute from the Google Cloud Platform Console

Go to the Cloud Dataflow page in the GCP Console.

Go to the Cloud Dataflow page

Click Create job from template.

Select the Bulk Decompress Cloud Storage Files template from the Cloud Dataflow template drop-down menu.
Enter a job name in the Job Name field. Your job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Enter your parameter values in the provided parameter fields.
Click Run Job.

GCLOUD

Execute from the gcloud command-line tool

Note: To use the gcloud command-line tool to execute templates, you must have Cloud SDK version 138.0.0 or higher.

When executing this template, you'll need the Cloud Storage path to the template:

gs://dataflow-templates/VERSION/Bulk_Decompress_GCS_Files

You must replace the following values in this example:

Replace YOUR_PROJECT_ID with your project ID.
Replace JOB_NAME with a job name of your choice. The job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Replace YOUR_BUCKET_NAME with the name of your Cloud Storage bucket.
Replace OUTPUT_FAILURE_FILE_PATH with your choice of path to the file containing failure information.

gcloud dataflow jobs run JOB_NAME \
    --gcs-location gs://dataflow-templates/latest/Bulk_Decompress_GCS_Files \
    --parameters \
inputFilePattern=gs://YOUR_BUCKET_NAME/compressed/*.gz,\
outputDirectory=gs://YOUR_BUCKET_NAME/decompressed,\
outputFailureFile=OUTPUT_FAILURE_FILE_PATH

API

Execute from the REST API

When executing this template, you'll need the Cloud Storage path to the template:

gs://dataflow-templates/VERSION/Bulk_Decompress_GCS_Files

To execute this template with a REST API request, send an HTTP POST request with your project ID. This request requires authorization.

You must replace the following values in this example:

Replace YOUR_PROJECT_ID with your project ID.
Replace JOB_NAME with a job name of your choice. The job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Replace YOUR_BUCKET_NAME with the name of your Cloud Storage bucket.
Replace OUTPUT_FAILURE_FILE_PATH with your choice of path to the file containing failure information.

POST https://dataflow.googleapis.com/v1b3/projects/YOUR_PROJECT_ID/templates:launch?gcsPath=gs://dataflow-templates/latest/Bulk_Decompress_GCS_Files
{
   "jobName": "JOB_NAME",
   "parameters": {
       "inputFilePattern": "gs://YOUR_BUCKET_NAME/compressed/*.gz",
       "outputDirectory": "gs://YOUR_BUCKET_NAME/decompressed",
       "outputFailureFile": "OUTPUT_FAILURE_FILE_PATH"
   },
   "environment": { "zone": "us-central1-f" }
}

Template source code

Java

View on GitHub Feedback

/*
 * Copyright (C) 2018 Google Inc.
 *
 * 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.common.annotations.VisibleForTesting;
import com.google.common.collect.ImmutableList;
import com.google.common.io.ByteStreams;
import com.google.common.io.Files;
import java.io.IOException;
import java.io.StringWriter;
import java.nio.channels.ReadableByteChannel;
import java.nio.channels.WritableByteChannel;
import java.util.Set;
import java.util.stream.Collectors;
import java.util.stream.Stream;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.PipelineResult;
import org.apache.beam.sdk.io.Compression;
import org.apache.beam.sdk.io.FileIO;
import org.apache.beam.sdk.io.FileSystems;
import org.apache.beam.sdk.io.TextIO;
import org.apache.beam.sdk.io.fs.MatchResult;
import org.apache.beam.sdk.io.fs.MoveOptions;
import org.apache.beam.sdk.io.fs.ResolveOptions.StandardResolveOptions;
import org.apache.beam.sdk.io.fs.ResourceId;
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.Validation.Required;
import org.apache.beam.sdk.options.ValueProvider;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.MapElements;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.util.MimeTypes;
import org.apache.beam.sdk.values.KV;
import org.apache.beam.sdk.values.PCollectionTuple;
import org.apache.beam.sdk.values.TupleTag;
import org.apache.beam.sdk.values.TupleTagList;
import org.apache.beam.sdk.values.TypeDescriptors;
import org.apache.commons.csv.CSVFormat;
import org.apache.commons.csv.CSVPrinter;
import org.apache.commons.csv.QuoteMode;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * This pipeline decompresses file(s) from Google Cloud Storage and re-uploads them to a destination
 * location.
 *
 * <p><b>Parameters</b>
 *
 * <p>The {@code --inputFilePattern} parameter specifies a file glob to process. Files found can be
 * expressed in the following formats:
 *
 * <pre>
 * --inputFilePattern=gs://bucket-name/compressed-dir/*
 * --inputFilePattern=gs://bucket-name/compressed-dir/demo*.gz
 * </pre>
 *
 * <p>The {@code --outputDirectory} parameter can be expressed in the following formats:
 *
 * <pre>
 * --outputDirectory=gs://bucket-name
 * --outputDirectory=gs://bucket-name/decompressed-dir
 * </pre>
 *
 * <p>The {@code --outputFailureFile} parameter indicates the file to write the names of the files
 * which failed decompression and their associated error messages. This file can then be used for
 * subsequent processing by another process outside of Dataflow (e.g. send an email with the
 * failures, etc.). If there are no failures, the file will still be created but will be empty. The
 * failure file structure contains both the file that caused the error and the error message in CSV
 * format. The file will contain one header row and two columns (Filename, Error). The filename
 * output to the failureFile will be the full path of the file for ease of debugging.
 *
 * <pre>
 * --outputFailureFile=gs://bucket-name/decompressed-dir/failed.csv
 * </pre>
 *
 * <p>Example Output File:
 *
 * <pre>
 * Filename,Error
 * gs://docs-demo/compressedFile.gz, File is malformed or not compressed in BZIP2 format.
 * </pre>
 *
 * <p><b>Example Usage</b>
 *
 * <pre>
 * mvn compile exec:java \
 * -Dexec.mainClass=com.google.cloud.teleport.templates.BulkDecompressor \
 * -Dexec.cleanupDaemonThreads=false \
 * -Dexec.args=" \
 * --project=${PROJECT_ID} \
 * --stagingLocation=gs://${PROJECT_ID}/dataflow/pipelines/${PIPELINE_FOLDER}/staging \
 * --tempLocation=gs://${PROJECT_ID}/dataflow/pipelines/${PIPELINE_FOLDER}/temp \
 * --runner=DataflowRunner \
 * --inputFilePattern=gs://${PROJECT_ID}/compressed-dir/*.gz \
 * --outputDirectory=gs://${PROJECT_ID}/decompressed-dir \
 * --outputFailureFile=gs://${PROJECT_ID}/decompressed-dir/failed.csv"
 * </pre>
 */
public class BulkDecompressor {

  /** The logger to output status messages to. */
  private static final Logger LOG = LoggerFactory.getLogger(BulkDecompressor.class);

  /**
   * A list of the {@link Compression} values excluding {@link Compression#AUTO} and {@link
   * Compression#UNCOMPRESSED}.
   */
  @VisibleForTesting
  static final Set<Compression> SUPPORTED_COMPRESSIONS =
      Stream.of(Compression.values())
          .filter(value -> value != Compression.AUTO && value != Compression.UNCOMPRESSED)
          .collect(Collectors.toSet());

  /** The error msg given when the pipeline matches a file but cannot determine the compression. */
  @VisibleForTesting
  static final String UNCOMPRESSED_ERROR_MSG =
      "Skipping file %s because it did not match any compression mode (%s)";

  @VisibleForTesting
  static final String MALFORMED_ERROR_MSG =
      "The file resource %s is malformed or not in %s compressed format.";

  /** The tag used to identify the main output of the {@link Decompress} DoFn. */
  @VisibleForTesting
  static final TupleTag<String> DECOMPRESS_MAIN_OUT_TAG = new TupleTag<String>() {};

  /** The tag used to identify the dead-letter sideOutput of the {@link Decompress} DoFn. */
  @VisibleForTesting
  static final TupleTag<KV<String, String>> DEADLETTER_TAG = new TupleTag<KV<String, String>>() {};

  /**
   * The {@link Options} class provides the custom execution options passed by the executor at the
   * command-line.
   */
  public interface Options extends PipelineOptions {
    @Description("The input file pattern to read from (e.g. gs://bucket-name/compressed/*.gz)")
    @Required
    ValueProvider<String> getInputFilePattern();

    void setInputFilePattern(ValueProvider<String> value);

    @Description("The output location to write to (e.g. gs://bucket-name/decompressed)")
    @Required
    ValueProvider<String> getOutputDirectory();

    void setOutputDirectory(ValueProvider<String> value);

    @Description(
        "The output file to write failures during the decompression process "
            + "(e.g. gs://bucket-name/decompressed/failed.txt). The contents will be one line for "
            + "each file which failed decompression. Note that this parameter will "
            + "allow the pipeline to continue processing in the event of a failure.")
    @Required
    ValueProvider<String> getOutputFailureFile();

    void setOutputFailureFile(ValueProvider<String> value);
  }

  /**
   * The main entry-point for pipeline execution. This method will start the pipeline but will not
   * wait for it's execution to finish. If blocking execution is required, use the {@link
   * BulkDecompressor#run(Options)} method to start the pipeline and invoke {@code
   * result.waitUntilFinish()} on the {@link PipelineResult}.
   *
   * @param args The command-line args passed by the executor.
   */
  public static void main(String[] args) {

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

    run(options);
  }

  /**
   * Runs the pipeline to completion with the specified options. This method does not wait until the
   * pipeline is finished before returning. Invoke {@code result.waitUntilFinish()} on the result
   * object to block until the pipeline is finished running if blocking programmatic execution is
   * required.
   *
   * @param options The execution options.
   * @return The pipeline result.
   */
  public static PipelineResult run(Options options) {

    /*
     * Steps:
     *   1) Find all files matching the input pattern
     *   2) Decompress the files found and output them to the output directory
     *   3) Write any errors to the failure output file
     */

    // Create the pipeline
    Pipeline pipeline = Pipeline.create(options);

    // Run the pipeline over the work items.
    PCollectionTuple decompressOut =
        pipeline
            .apply("MatchFile(s)", FileIO.match().filepattern(options.getInputFilePattern()))
            .apply(
                "DecompressFile(s)",
                ParDo.of(new Decompress(options.getOutputDirectory()))
                    .withOutputTags(DECOMPRESS_MAIN_OUT_TAG, TupleTagList.of(DEADLETTER_TAG)));

    decompressOut
        .get(DEADLETTER_TAG)
        .apply(
            "FormatErrors",
            MapElements.into(TypeDescriptors.strings())
                .via(
                    kv -> {
                      StringWriter stringWriter = new StringWriter();
                      try {
                        CSVPrinter printer =
                            new CSVPrinter(
                                stringWriter,
                                CSVFormat.DEFAULT
                                    .withEscape('\\')
                                    .withQuoteMode(QuoteMode.NONE)
                                    .withRecordSeparator('\n')
                            );
                        printer.printRecord(kv.getKey(), kv.getValue());
                      } catch (IOException e) {
                        throw new RuntimeException(e);
                      }

                      return stringWriter.toString();
                    }))

        // We don't expect error files to be large so we'll create a single
        // file for ease of reprocessing by processes outside of Dataflow.
        .apply(
            "WriteErrorFile",
            TextIO.write()
                .to(options.getOutputFailureFile())
                .withHeader("Filename,Error")
                .withoutSharding());

    return pipeline.run();
  }

  /**
   * Performs the decompression of an object on Google Cloud Storage and uploads the decompressed
   * object back to a specified destination location.
   */
  @SuppressWarnings("serial")
  public static class Decompress extends DoFn<MatchResult.Metadata, String> {

    private final ValueProvider<String> destinationLocation;

    Decompress(ValueProvider<String> destinationLocation) {
      this.destinationLocation = destinationLocation;
    }

    @ProcessElement
    public void processElement(ProcessContext context) {
      ResourceId inputFile = context.element().resourceId();

      // Output a record to the failure file if the file doesn't match a known compression.
      if (!Compression.AUTO.isCompressed(inputFile.toString())) {
        String errorMsg =
            String.format(UNCOMPRESSED_ERROR_MSG, inputFile.toString(), SUPPORTED_COMPRESSIONS);

        context.output(DEADLETTER_TAG, KV.of(inputFile.toString(), errorMsg));
      } else {
        try {
          ResourceId outputFile = decompress(inputFile);
          context.output(outputFile.toString());
        } catch (IOException e) {
          LOG.error(e.getMessage());
          context.output(DEADLETTER_TAG, KV.of(inputFile.toString(), e.getMessage()));
        }
      }
    }

    /**
     * Decompresses the inputFile using the specified compression and outputs to the main output of
     * the {@link Decompress} doFn. Files output to the destination will be first written as temp
     * files with a "temp-" prefix within the output directory. If a file fails decompression, the
     * filename and the associated error will be output to the dead-letter.
     *
     * @param inputFile The inputFile to decompress.
     * @return A {@link ResourceId} which points to the resulting file from the decompression.
     */
    private ResourceId decompress(ResourceId inputFile) throws IOException {
      // Remove the compressed extension from the file. Example: demo.txt.gz -> demo.txt
      String outputFilename = Files.getNameWithoutExtension(inputFile.toString());

      // Resolve the necessary resources to perform the transfer.
      ResourceId outputDir = FileSystems.matchNewResource(destinationLocation.get(), true);
      ResourceId outputFile =
          outputDir.resolve(outputFilename, StandardResolveOptions.RESOLVE_FILE);
      ResourceId tempFile =
          outputDir.resolve(Files.getFileExtension(inputFile.toString())
              + "-temp-" + outputFilename, StandardResolveOptions.RESOLVE_FILE);

      // Resolve the compression
      Compression compression = Compression.detect(inputFile.toString());

      // Perform the copy of the decompressed channel into the destination.
      try (ReadableByteChannel readerChannel =
          compression.readDecompressed(FileSystems.open(inputFile))) {
        try (WritableByteChannel writerChannel = FileSystems.create(tempFile, MimeTypes.TEXT)) {
          ByteStreams.copy(readerChannel, writerChannel);
        }

        // Rename the temp file to the output file.
        FileSystems.rename(
            ImmutableList.of(tempFile),
            ImmutableList.of(outputFile),
            MoveOptions.StandardMoveOptions.IGNORE_MISSING_FILES);
      } catch (IOException e) {
        String msg = e.getMessage();

        LOG.error("Error occurred during decompression of {}", inputFile.toString(), e);
        throw new IOException(sanitizeDecompressionErrorMsg(msg, inputFile, compression));
      }

      return outputFile;
    }

    /**
     * The error messages coming from the compression library are not consistent across compression
     * modes. Here we'll attempt to unify the messages to inform the user more clearly when we've
     * encountered a file which is not compressed or malformed. Note that GZIP and ZIP compression
     * modes will not throw an exception when a decompression is attempted on a file which is not
     * compressed.
     *
     * @param errorMsg The error message thrown during decompression.
     * @param inputFile The input file which failed decompression.
     * @param compression The compression mode used during decompression.
     * @return The sanitized error message. If the error was not from a malformed file, the same
     *     error message passed will be returned.
     */
    private String sanitizeDecompressionErrorMsg(
        String errorMsg, ResourceId inputFile, Compression compression) {
      if (errorMsg != null
          && (errorMsg.contains("not in the BZip2 format")
              || errorMsg.contains("incorrect header check"))) {
        errorMsg = String.format(MALFORMED_ERROR_MSG, inputFile.toString(), compression);
      }

      return errorMsg;
    }
  }
}

Python

Python source code is not available.

Cloud Datastore Bulk Delete

The Cloud Datastore Bulk Delete template is a pipeline which reads in Entities from Datastore with a given GQL query and then deletes all matching Entities in the selected target project. The pipeline can optionally pass the JSON encoded Datastore Entities to your Javascript UDF, which you can use to filter out Entities by returning null values.

Requirements for this pipeline:

Cloud Datastore must be set up in the project prior to execution.
If reading and deleting from separate Datastore instances, the Dataflow Controller Service Account must have permission to read from one instance and delete from the other.

Template parameters

Parameter	Description
`datastoreReadGqlQuery`	GQL Query which specifies which entities to match for deletion. e.g: "SELECT * FROM MyKind".
`datastoreReadProjectId`	GCP Project Id of the Cloud Datastore instance from which you want to read entities (using your GQL Query) that are used for matching.
`datastoreDeleteProjectId`	GCP Project Id of the Cloud Datastore instance from which to delete matching entities. This can be the same as `datastoreReadProjectId` if you want to read and delete within the same Cloud Datastore instance.
`datastoreReadNamespace`	[Optional] Namespace of requested Entities. Set as "" for default namespace.
`javascriptTextTransformGcsPath`	[Optional] A Cloud Storage path which contains all your JavaScript code. e.g: "gs://mybucket/mytransforms/*.js". If you don't want to use a UDF leave this field blank.
`javascriptTextTransformFunctionName`	[Optional] Name of the Function to be called. If this function returns a value of undefined or null for a given Datastore Entity, then that Entity will not be deleted. If you have the javascript code of: "function myTransform(inJson) { ...dostuff...}" then your function name is "myTransform". If you don't want to use a UDF leave this field blank.

Executing the Cloud Datastore Bulk Delete template

CONSOLE

Execute from the Google Cloud Platform Console

Go to the Cloud Dataflow page in the GCP Console.

Go to the Cloud Dataflow page

Click Create job from template.

Select the Cloud Datastore Bulk Delete template from the Cloud Dataflow template drop-down menu.
Enter a job name in the Job Name field. Your job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Enter your parameter values in the provided parameter fields.
Click Run Job.

GCLOUD

Execute from the gcloud command-line tool

Note: To use the gcloud command-line tool to execute templates, you must have Cloud SDK version 138.0.0 or higher.

When executing this template, you'll need the Cloud Storage path to the template:

gs://dataflow-templates/VERSION/Bulk_Decompress_GCS_Files

You must replace the following values in this example:

Replace JOB_NAME with a job name of your choice. The job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Replace GQL_QUERY with the query you'll use to match entities for deletion.
Replace DATASTORE_READ_AND_DELETE_PROJECT_ID with your Datastore instance project id. This example will both read and delete from the same Datastore instance.

gcloud dataflow jobs run JOB_NAME \
    --gcs-location gs://dataflow-templates/latest/Datastore_to_Datastore_Delete \
    --parameters \
datastoreReadGqlQuery="GQL_QUERY",\
datastoreReadProjectId=DATASTORE_READ_AND_DELETE_PROJECT_ID,\
datastoreDeleteProjectId=DATASTORE_READ_AND_DELETE_PROJECT_ID

API

Execute from the REST API

When executing this template, you'll need the Cloud Storage path to the template:

gs://dataflow-templates/VERSION/Bulk_Decompress_GCS_Files

To execute this template with a REST API request, send an HTTP POST request with your project ID. This request requires authorization.

You must replace the following values in this example:

Replace JOB_NAME with a job name of your choice. The job name must match the regular expression [a-z]([-a-z0-9]{0,38}[a-z0-9])? to be valid.
Replace GQL_QUERY with the query you'll use to match entities for deletion.
Replace DATASTORE_READ_AND_DELETE_PROJECT_ID with your Datastore instance project id. This example will both read and delete from the same Datastore instance.

POST https://dataflow.googleapis.com/v1b3/projects/YOUR_PROJECT_ID/templates:launch?gcsPath=gs://dataflow-templates/latest/Datastore_to_Datastore_Delete
{
   "jobName": "JOB_NAME",
   "parameters": {
       "datastoreReadGqlQuery": "GQL_QUERY",
       "datastoreReadProjectId": "READ_PROJECT_ID",
       "datastoreDeleteProjectId": "DELETE_PROJECT_ID"
   },
   "environment": { "zone": "us-central1-f" }
   }
}

Template source code

Java

View on GitHub Feedback

/*
 * Copyright (C) 2018 Google Inc.
 *
 * 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.templates.common.DatastoreConverters.DatastoreDeleteEntityJson;
import com.google.cloud.teleport.templates.common.DatastoreConverters.DatastoreDeleteOptions;
import com.google.cloud.teleport.templates.common.DatastoreConverters.DatastoreReadOptions;
import com.google.cloud.teleport.templates.common.DatastoreConverters.ReadJsonEntities;
import com.google.cloud.teleport.templates.common.JavascriptTextTransformer.JavascriptTextTransformerOptions;
import com.google.cloud.teleport.templates.common.JavascriptTextTransformer.TransformTextViaJavascript;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;

/**
 * Dataflow template which deletes pulled Datastore Entities.
 */
public class DatastoreToDatastoreDelete {
  interface DatastoreToDatastoreDeleteOptions extends
      PipelineOptions,
      DatastoreReadOptions,
      JavascriptTextTransformerOptions,
      DatastoreDeleteOptions {}

  /**
   * Runs a pipeline which reads in Entities from datastore, passes in the JSON encoded Entities
   * to a Javascript UDF, and deletes all the Entities.
   *
   * <p>If the UDF returns value of undefined or null for a given Entity, then that Entity will not
   * be deleted.
   *
   * @param args arguments to the pipeline
   */
  public static void main(String[] args) {
    DatastoreToDatastoreDeleteOptions options = PipelineOptionsFactory.fromArgs(args)
        .withValidation()
        .as(DatastoreToDatastoreDeleteOptions.class);

    Pipeline pipeline = Pipeline.create(options);

    pipeline
        .apply(ReadJsonEntities.newBuilder()
            .setGqlQuery(options.getDatastoreReadGqlQuery())
            .setProjectId(options.getDatastoreReadProjectId())
            .setNamespace(options.getDatastoreReadNamespace())
            .build())
        .apply(TransformTextViaJavascript.newBuilder()
            .setFileSystemPath(options.getJavascriptTextTransformGcsPath())
            .setFunctionName(options.getJavascriptTextTransformFunctionName())
            .build())
        .apply(DatastoreDeleteEntityJson.newBuilder()
            .setProjectId(options.getDatastoreDeleteProjectId())
            .build());

    pipeline.run();
  }

}

Python

Python source code is not available.

Bulk Compress Cloud Storage Files

Template parameters

Executing the Bulk Compress Cloud Storage Files template

CONSOLE

GCLOUD

API

Template source code

Java

Python

Bulk Decompress Cloud Storage Files

Template parameters

Executing the Bulk Decompress Cloud Storage Files template

CONSOLE

GCLOUD

API

Template source code

Java

Python

Cloud Datastore Bulk Delete

Template parameters

Executing the Cloud Datastore Bulk Delete template

CONSOLE

GCLOUD

API

Template source code

Java

Python

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