Quickstart using Java and Apache Maven

This document shows you how to set up your Google Cloud project, create a Maven project by using the Apache Beam SDK for Java, and run an example pipeline on the Dataflow service. The pipeline reads a text file from Cloud Storage, counts the number of unique words in the file, and then writes the word counts back to Cloud Storage.

This quickstart requires familiarity with installing and configuring both Java and Maven in your local production environment. If you prefer running a sample job without first installing the prerequisites in your local environment, try the Dataflow word count tutorial from the Google Cloud Console.

Go to the Dataflow tutorial

Before you begin

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud Console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Cloud project. Learn how to confirm that billing is enabled for your project.

  4. Enable the Dataflow, Compute Engine, Cloud Logging, Cloud Storage, Google Cloud Storage JSON, BigQuery, Cloud Pub/Sub, Cloud Datastore, and Cloud Resource Manager APIs.

    Enable the APIs

  5. Create a service account:

    1. In the Cloud Console, go to the Create service account page.

      Go to Create service account
    2. Select a project.
    3. In the Service account name field, enter a name. The Cloud Console fills in the Service account ID field based on this name.

      In the Service account description field, enter a description. For example, Service account for quickstart.

    4. Click Create and continue.
    5. Click the Select a role field.

      Under Quick access, click Basic, then click Owner.

    6. Click Continue.
    7. Click Done to finish creating the service account.

      Do not close your browser window. You will use it in the next step.

  6. Create a service account key:

    1. In the Cloud Console, click the email address for the service account that you created.
    2. Click Keys.
    3. Click Add key, then click Create new key.
    4. Click Create. A JSON key file is downloaded to your computer.
    5. Click Close.
  7. Set the environment variable GOOGLE_APPLICATION_CREDENTIALS to the path of the JSON file that contains your service account key. This variable only applies to your current shell session, so if you open a new session, set the variable again.

  8. In the Google Cloud Console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  9. Make sure that billing is enabled for your Cloud project. Learn how to confirm that billing is enabled for your project.

  10. Enable the Dataflow, Compute Engine, Cloud Logging, Cloud Storage, Google Cloud Storage JSON, BigQuery, Cloud Pub/Sub, Cloud Datastore, and Cloud Resource Manager APIs.

    Enable the APIs

  11. Create a service account:

    1. In the Cloud Console, go to the Create service account page.

      Go to Create service account
    2. Select a project.
    3. In the Service account name field, enter a name. The Cloud Console fills in the Service account ID field based on this name.

      In the Service account description field, enter a description. For example, Service account for quickstart.

    4. Click Create and continue.
    5. Click the Select a role field.

      Under Quick access, click Basic, then click Owner.

    6. Click Continue.
    7. Click Done to finish creating the service account.

      Do not close your browser window. You will use it in the next step.

  12. Create a service account key:

    1. In the Cloud Console, click the email address for the service account that you created.
    2. Click Keys.
    3. Click Add key, then click Create new key.
    4. Click Create. A JSON key file is downloaded to your computer.
    5. Click Close.
  13. Set the environment variable GOOGLE_APPLICATION_CREDENTIALS to the path of the JSON file that contains your service account key. This variable only applies to your current shell session, so if you open a new session, set the variable again.

  14. Create a Cloud Storage bucket:
    1. In the Cloud Console, go to the Cloud Storage Browser page.

      Go to Browser

    2. Click Create bucket.
    3. On the Create a bucket page, enter your bucket information. To go to the next step, click Continue.
      • For Name your bucket, enter a unique bucket name. Don't include sensitive information in the bucket name, because the bucket namespace is global and publicly visible.
      • For Choose where to store your data, do the following:
        • Select a Location type option.
        • Select a Location option.
      • For Choose a default storage class for your data, select the following: Standard.
      • For Choose how to control access to objects, select an Access control option.
      • For Advanced settings (optional), specify an encryption method, a retention policy, or bucket labels.
    4. Click Create.
  15. Copy the following, as you need them in a later section:
    • Your Cloud Storage bucket name.
    • Your Google Cloud project ID. To find this ID, see Identifying projects.
  16. Download and install the Java Development Kit (JDK) version 11. (Dataflow continues to support version 8.) Verify that the JAVA_HOME environment variable is set and points to your JDK installation.
  17. Download and install Apache Maven, following Maven's installation guide for your specific operating system.

Get the pipeline code

The Apache Beam SDK is an open source programming model for data processing pipelines. You define these pipelines with an Apache Beam program and can choose a runner, such as Dataflow, to run your pipeline.

  1. In your shell or terminal, use the Maven Archetype Plugin to create a Maven project on your computer that contains the Apache Beam SDK's WordCount examples:
    mvn archetype:generate \
        -DarchetypeGroupId=org.apache.beam \
        -DarchetypeArtifactId=beam-sdks-java-maven-archetypes-examples \
        -DarchetypeVersion=2.33.0 \
        -DgroupId=org.example \
        -DartifactId=word-count-beam \
        -Dversion="0.1" \
        -Dpackage=org.apache.beam.examples \
        -DinteractiveMode=false
    

    The command creates a new directory called word-count-beam under your current directory. The word-count-beam directory contains a simple pom.xml file and a series of example pipelines that count words in text files.

  2. Verify that your word-count-beam directory contains the pom.xml file:

    Linux or macOS

    cd word-count-beam/
    ls

    The output is the following:

    pom.xml   src

    Windows

    cd word-count-beam/
    dir

    The output is the following:

    pom.xml   src
  3. Verify that your Maven project contains the example pipelines:

    Linux or macOS

    ls src/main/java/org/apache/beam/examples/

    The output is the following:

    DebuggingWordCount.java   WindowedWordCount.java   common
    MinimalWordCount.java   WordCount.java

    Windows

    dir src/main/java/org/apache/beam/examples/

    The output is the following:

    DebuggingWordCount.java   WindowedWordCount.java   common
    MinimalWordCount.java   WordCount.java

For a detailed introduction to the Apache Beam concepts that are used in these examples, see the Apache Beam WordCount Example. The instructions in the next sections use WordCount.java.

Run the pipeline locally

  • In your shell or terminal, run the WordCount pipeline locally from your word-count-beam directory:
    mvn compile exec:java \
        -Dexec.mainClass=org.apache.beam.examples.WordCount \
        -Dexec.args="--output=counts"
    

    The output files have the prefix counts and are written to the word-count-beam directory. They contain unique words from the input text and the number of occurrences of each word.

Run the pipeline on the Dataflow service

  • In your shell or terminal, build and run the WordCount pipeline on the Dataflow service from your word-count-beam directory:
    mvn -Pdataflow-runner compile exec:java \
        -Dexec.mainClass=org.apache.beam.examples.WordCount \
        -Dexec.args="--project=PROJECT_ID \
        --gcpTempLocation=gs://BUCKET_NAME/temp/ \
        --output=gs://BUCKET_NAME/output \
        --runner=DataflowRunner \
        --region=REGION"
    

    Replace the following:

    • PROJECT_ID: your Cloud project ID
    • BUCKET_NAME: the name of your Cloud Storage bucket
    • REGION: a Dataflow regional endpoint, like us-central1

View your results

  1. In the Cloud Console, go to the Dataflow Jobs page.
    Go to Jobs

    The Jobs page shows the details of all the available jobs, including the status. The wordcount job's Status is Running at first, and then updates to Succeeded.

  2. In the Cloud Console, go to the Cloud Storage Browser page.
    Go to Browser

    The Browser page displays the list of all the storage buckets in your project.

  3. Click the storage bucket that you created.

    The Bucket details page shows the output files and staging files that your Dataflow job created.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used in this page, follow these steps.

Delete the project

The easiest way to eliminate billing is to delete the Google Cloud project that you created for the quickstart.

  1. In the Cloud Console, go to the Manage resources page.

    Go to Manage resources

  2. In the project list, select the project that you want to delete, and then click Delete.
  3. In the dialog, type the project ID, and then click Shut down to delete the project.

Delete the individual resources

If you want to keep the Google Cloud project that you used in this quickstart, then delete the individual resources:

  1. In the Cloud Console, go to the Cloud Storage Browser page.

    Go to Browser

  2. Click the checkbox for the bucket that you want to delete.
  3. To delete the bucket, click Delete, and then follow the instructions.

What's next