Get started with Google-provided templates

Google provides a set of open source Dataflow templates. For general information about templates, see the Overview page. To get started, use the WordCount template. See other Google-provided templates:

Streaming templates - Templates for processing data continuously:

Batch templates - Templates for processing data in bulk:

Utility templates:

WordCount

The WordCount template is a batch pipeline that reads text from Cloud Storage, tokenizes the text lines into individual words, and performs a frequency count on each of the words. For more information about WordCount, see WordCount Example Pipeline.

Template parameters

Parameter	Description
`inputFile`	The Cloud Storage input file's path.
`output`	The Cloud Storage output file's path and prefix.

Running the WordCount template

Console

Run using Google Cloud Console.

Go to the Dataflow page in the Cloud Console.

Go to the Dataflow page

Click Create job from template.

Select the WordCount template from the Dataflow template drop-down menu.
Enter a job name in the Job Name field.
Enter your parameter values in the provided parameter fields.
Click Run Job.

gcloud

Run using gcloud command-line tool.

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

When running this template, you need the Cloud Storage path to the template:

gs://dataflow-templates/latest/Word_Count

Run the following command:

gcloud dataflow jobs run JOB_NAME \
    --gcs-location gs://dataflow-templates/latest/Word_Count \
    --parameters \
    inputFile=gs://dataflow-samples/shakespeare/kinglear.txt,\
    output=gs://BUCKET_NAME/output/my_output

Replace the following:

JOB_NAME: a job name of your choice
BUCKET_NAME: the name of your Cloud Storage bucket.

API

Run using REST API.

When running this template, you need the Cloud Storage path to the template:

gs://dataflow-templates/latest/Word_Count

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

POST https://dataflow.googleapis.com/v1b3/projects/PROJECT_ID/templates:launch?gcsPath=gs://dataflow-templates/latest/Word_Count
{
    "jobName": "JOB_NAME",
    "parameters": {
       "inputFile" : "gs://dataflow-samples/shakespeare/kinglear.txt",
       "output": "gs://BUCKET_NAME/output/my_output"
    },
    "environment": { "zone": "us-central1-f" }
}

Replace the following:

PROJECT_ID: your project ID
JOB_NAME: a job name of your choice
BUCKET_NAME: the name of your Cloud Storage bucket.

Template source code

Java

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/*
 * Copyright (C) 2016 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 org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.io.TextIO;
import org.apache.beam.sdk.metrics.Counter;
import org.apache.beam.sdk.metrics.Metrics;
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.ValueProvider;
import org.apache.beam.sdk.transforms.Count;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.MapElements;
import org.apache.beam.sdk.transforms.PTransform;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.transforms.SimpleFunction;
import org.apache.beam.sdk.values.KV;
import org.apache.beam.sdk.values.PCollection;

/**
 * An template that counts words in Shakespeare.
 */
public class WordCount {

  static class ExtractWordsFn extends DoFn<String, String> {
    private final Counter emptyLines = Metrics.counter(ExtractWordsFn.class, "emptyLines");

    @ProcessElement
    public void processElement(ProcessContext c) {
      if (c.element().trim().isEmpty()) {
        emptyLines.inc();
      }

      // Split the line into words.
      String[] words = c.element().split("[^a-zA-Z']+");

      // Output each word encountered into the output PCollection.
      for (String word : words) {
        if (!word.isEmpty()) {
          c.output(word);
        }
      }
    }
  }

  /** A SimpleFunction that converts a Word and Count into a printable string. */
  public static class FormatAsTextFn extends SimpleFunction<KV<String, Long>, String> {
    @Override
    public String apply(KV<String, Long> input) {
      return input.getKey() + ": " + input.getValue();
    }
  }

  /**
   * A PTransform that converts a PCollection containing lines of text into a PCollection of
   * formatted word counts.
   */
  public static class CountWords extends PTransform<PCollection<String>,
        PCollection<KV<String, Long>>> {
    @Override
    public PCollection<KV<String, Long>> expand(PCollection<String> lines) {

      // Convert lines of text into individual words.
      PCollection<String> words = lines.apply(
          ParDo.of(new ExtractWordsFn()));

      // Count the number of times each word occurs.
      PCollection<KV<String, Long>> wordCounts =
          words.apply(Count.<String>perElement());

      return wordCounts;
    }
  }

  /**
   * Options supported by {@link com.google.cloud.teleport.templates.WordCount}.
   *
   * <p>Inherits standard configuration options.
   */
  public interface WordCountOptions extends PipelineOptions {
    @Description("Path of the file to read from")
    ValueProvider<String> getInputFile();
    void setInputFile(ValueProvider<String> value);

    @Description("Path of the file to write to")
    ValueProvider<String> getOutput();
    void setOutput(ValueProvider<String> value);
  }

  public static void main(String[] args) {
    WordCountOptions options = PipelineOptionsFactory.fromArgs(args).withValidation()
      .as(WordCountOptions.class);
    Pipeline p = Pipeline.create(options);
    p.apply("ReadLines", TextIO.read().from(options.getInputFile()))
     .apply(new CountWords())
     .apply(MapElements.via(new FormatAsTextFn()))
     .apply("WriteCounts", TextIO.write().to(options.getOutput()));

    p.run();
  }
}