Google Cloud Dataflow SDK for Java

Google Cloud Dataflow provides a simple,
powerful programming model for building both batch and streaming parallel data
processing pipelines. This repository hosts the open-sourced Cloud Dataflow SDK
for Java, which can be used to run pipelines against the Google Cloud Dataflow
Service.

General usage of Google
Cloud Dataflow does not require use of this repository. Instead:

1. depend directly on a specific
   version of the SDK in
   the Maven Central Repository
   by adding the following dependency to development
   environments like Eclipse or Apache Maven:

    <dependency>
      <groupId>com.google.cloud.dataflow</groupId>
      <artifactId>google-cloud-dataflow-java-sdk-all</artifactId>
      <version>version_number</version>
    </dependency>
   

2. download the example pipelines from the separate
   DataflowJavaSDK-examples
   repository.

However, if you'd like to contribute to the SDK, write your own PipelineRunner,
or just dig in for the fun of it, please stay with us here!

Status

Both the SDK and the Dataflow Service are generally available, open to all
developers, and considered stable and fully qualified for production use.

Overview

The key concepts in this programming model are:

• PCollection:
  represents a collection of data, which could be bounded or unbounded in size.
• PTransform:
  represents a computation that transforms input PCollections into output
  PCollections.
• Pipeline:
  manages a directed acyclic graph of PTransforms and PCollections that is ready
  for execution.
• PipelineRunner:
  specifies where and how the pipeline should execute.

We provide three PipelineRunners:

1. The DirectPipelineRunner
   runs the pipeline on your local machine.
2. The DataflowPipelineRunner
   submits the pipeline to the Dataflow Service, where it runs using managed
   resources in the Google Cloud Platform (GCP).
3. The BlockingDataflowPipelineRunner
   submits the pipeline to the Dataflow Service via the DataflowPipelineRunner
   and then prints messages about the job status until the execution is complete.

The SDK is built to be extensible and support additional execution environments
beyond local execution and the Google Cloud Dataflow Service. In partnership
with Cloudera, you can run Dataflow pipelines on
an Apache Spark backend using the
SparkPipelineRunner.
Additionally, you can run Dataflow pipelines on an
Apache Flink backend using the
FlinkPipelineRunner.

Getting Started

This repository consists of the following parts:

• The sdk
  module provides a set of basic Java APIs to program against.
• The examples
  module provides a few samples to get started. We recommend starting with the
  WordCount example.
• The contrib
  directory hosts community-contributed Dataflow modules.

The following command will build both the sdk and example modules and
install them in your local Maven repository:

mvn clean install

You can speed up the build and install process by using the following options:

1. To skip execution of the unit tests, run:

   mvn install -DskipTests

2. While iterating on a specific module, use the following command to compile
   and reinstall it. For example, to reinstall the examples module, run:

   mvn install -pl examples

Be careful, however, as this command will use the most recently installed SDK
from the local repository (or Maven Central) even if you have changed it
locally.

If you are using Eclipse integrated development
environment (IDE), the
Cloud Dataflow Plugin for Eclipse
provides tools to create and execute Dataflow pipelines locally and on the
Dataflow Service.

After building and installing, you can execute the WordCount and other
example pipelines by following the instructions in this
README.

Contact Us

We welcome all usage-related questions on Stack Overflow
tagged with google-cloud-dataflow.

Please use issue tracker
on GitHub to report any bugs, comments or questions regarding SDK development.

More Information

• Google Cloud Dataflow
• Dataflow Concepts and Programming Model
• Java API Reference