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FlareDB runs Apache Beam pipelines. You keep building your pipeline with the Beam SDK, and point it at FlareRunner, which submits the pipeline to a running FlareDB instance as a job.

Prerequisites

  • A running FlareDB instance. See the Quickstart.
  • JDK 17.
  • An Apache Beam project. The examples in this guide use Gradle and Beam 2.76.0; Maven is supported as well.

1. Add the runner dependency

Add the flaredb-runner artifact to your Beam project.
build.gradle

2. Configure the pipeline

Set FlareRunner as the runner and configure the FlareDB instance and applicatio JAR:
WordCount.java
The JAR is staged to FlareDB so your pipeline code is available when the job runs. Point setUberJar to the fat JAR produced by your build.

3. Build the pipeline

Build a self-contained (uber) JAR containing your pipeline and its dependencies.
Use the build output’s JAR path in setUberJar.

4. Run the pipeline

With FlareDB instance running, submit the pipeline:

Pipeline options

Define your options by extending FlarePipelineOptions, For Example:
WordCountPipelineOptions.java
These options can also be provided as command-line arguments:

Pipeline logs:

// ToDo flare up prints the instance ID. The <job-id> is generated when a job is submitted.

Next steps

  • FlareDB I/O — read from and write to FlareDB tables from a pipeline.
  • SQL shell — query the data your pipeline produces.