Quickstart Using Java and Apache Maven

This page shows you how to set up your Google Cloud Platform project to use Cloud Dataflow, create a Maven project with the Cloud Dataflow SDK and examples, and run an example pipeline using the Google Cloud Platform Console.

Before you begin

  1. Sign in to your Google account.

    If you don't already have one, sign up for a new account.

  2. Select or create a Cloud Platform project.

    Go to the Projects page

  3. Enable billing for your project.

    Enable billing

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

    Enable the APIs

  5. Install the Cloud SDK.
  6. Create a Cloud Storage bucket:
    1. In the Cloud Platform Console, go to the Cloud Storage browser.

      Go to the Cloud Storage browser

    2. Click Create bucket.
    3. In the Create bucket dialog, specify the following attributes:
      • Name: A unique bucket name. Do not include sensitive information in the bucket name, as the bucket namespace is global and publicly visible.
      • Storage class: Multi-Regional
      • Location: United States
    4. Click Create.
  7. Authenticate with the Cloud Platform. Run the following command to get Application Default Credentials.
        gcloud auth application-default login
  8. Download and install the Java Development Kit (JDK) version 1.7 or later. Verify that the JAVA_HOME environment variable is set and points to your JDK installation.
  9. Download and install Apache Maven by following Maven's installation guide for your specific operating system.

Create a Maven Project that contains the Cloud Dataflow SDK for Java and Examples

  1. Create a Maven project containing the Cloud Dataflow SDK for Java using the Maven Archetype Plugin. Run the mvn archetype:generate command in your shell or terminal as follows:
      mvn archetype:generate \
          -DarchetypeArtifactId=google-cloud-dataflow-java-archetypes-examples \
          -DarchetypeGroupId=com.google.cloud.dataflow \
          -DarchetypeVersion=1.9.0 \
          -DgroupId=com.example \
          -DartifactId=first-dataflow \
          -Dversion="0.1" \
          -DinteractiveMode=false \

    Note: If you would like to use the Dataflow SDK 2.0.0-beta-x version, you will need to change your pom.xml file as instructed in the Dataflow SDK 2.x for Java Release Notes page.

  2. After running the command, you should see a new directory called first-dataflow under your current directory. first-dataflow contains a Maven project that includes the Cloud Dataflow SDK for Java and example pipelines.

  3. Change to the first-dataflow/ directory.
  4. Build and run the example pipeline locally using the direct runner by using the mvn compile exec:java command in your shell or terminal window. For the --output arguments specify a local file path.
      mvn compile exec:java \
          -Dexec.mainClass=com.example.WordCount \

Run an Example Pipeline on the Cloud Dataflow Service

  1. Build and run the Cloud Dataflow example pipeline called WordCount on the Cloud Dataflow managed service by using the same command but different arguments. For the --project argument, you'll need to specify the Project ID for the Cloud Platform project that you created. For the --stagingLocation and --output arguments, you'll need to specify the name of the Cloud Storage bucket you created as part of the path.

    For example, if your Cloud Platform Project ID is my-cloud-project and your Cloud Storage bucket name is my-wordcount-storage-bucket, enter the following command to run the WordCount pipeline:

      mvn compile exec:java \
          -Dexec.mainClass=com.example.WordCount \
          -Dexec.args="--project=<my-cloud-project> \
          --stagingLocation=gs://<my-wordcount-storage-bucket>/staging/ \
          --output=gs://<my-wordcount-storage-bucket>/output \
  2. Check that your job succeeded:

    1. Open the Cloud Dataflow Monitoring UI in the Google Cloud Platform Console.
      Go to the Cloud Dataflow Monitoring UI

      You should see your wordcount job with a status of Running at first, and then Succeeded:

      Cloud Dataflow Jobs
    2. Open the Cloud Storage Browser in the Google Cloud Platform Console.
      Go to the Cloud Storage browser

      In your bucket, you should see the output files and staging files that your job created:

      Cloud Storage bucket

Clean up

To avoid incurring charges to your Google Cloud Platform account for the resources used in this quickstart:

  1. Open the Cloud Storage browser in the Google Cloud Platform Console.
  2. Select the checkbox next to the bucket that you created.
  3. Click Delete to permanently delete the bucket and its contents.

What's next

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Cloud Dataflow Documentation