Apache Flink is an open source platform for scalable batch and stream data processing. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

case class WordWithCount(word: String, count: Int)

val text = env.readTextFile(path)

val counts = text.flatMap { _.split("\\W+") }
  .map { WordWithCount(_, 1) }
  .groupBy("word")
  .sum("count")

counts.writeAsCsv(outputPath)

These are some of the unique features of Flink:

• Hybrid batch/streaming runtime that supports batch processing and data streaming programs.
• Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and out-of-core data processing algorithms.
• Flexible and expressive windowing semantics for data stream programs.
• Built-in program optimizer that chooses the proper runtime operations for each program.
• Custom type analysis and serialization stack for high performance.

Learn more about Flink at https://flink.apache.org/

Prerequisites for building Flink:

• Unix-like environment (We use Linux, Mac OS X, Cygwin)
• git
• Maven (at least version 3.0.4)
• Java 7 or 8

git clone https://github.com/apache/flink.git
cd flink
mvn clean package -DskipTests # this will take up to 5 minutes

Flink is now installed in build-target

The Flink committers use IntelliJ IDEA and Eclipse IDE to develop the Flink codebase.

Minimal requirements for an IDE are:

• Support for Java and Scala (also mixed projects)
• Support for Maven with Java and Scala

The IntelliJ IDE supports Maven out of the box and offers a plugin for Scala development.

• IntelliJ download: https://www.jetbrains.com/idea/
• IntelliJ Scala Plugin: https://plugins.jetbrains.com/plugin/?id=1347

Check out our Setting up IntelliJ guide for details.

For Eclipse users, we recommend using Scala IDE 3.0.3, based on Eclipse Kepler. While this is a slightly older version, we found it to be the version that works most robustly for a complex project like Flink.

Further details, and a guide to newer Scala IDE versions can be found in the How to setup Eclipse docs.

Note: Before following this setup, make sure to run the build from the command line once (mvn clean install -DskipTests, see above)

1. Download the Scala IDE (preferred) or install the plugin to Eclipse Kepler. See How to setup Eclipse for download links and instructions.
2. Add the "macroparadise" compiler plugin to the Scala compiler. Open "Window" -> "Preferences" -> "Scala" -> "Compiler" -> "Advanced" and put into the "Xplugin" field the path to the macroparadise jar file (typically "/home/-your-user-/.m2/repository/org/scalamacros/paradise_2.10.4/2.0.1/paradise_2.10.4-2.0.1.jar"). Note: If you do not have the jar file, you probably did not run the command line build.
3. Import the Flink Maven projects ("File" -> "Import" -> "Maven" -> "Existing Maven Projects")
4. During the import, Eclipse will ask to automatically install additional Maven build helper plugins.
5. Close the "flink-java8" project. Since Eclipse Kepler does not support Java 8, you cannot develop this project.

Don’t hesitate to ask!

Contact the developers and community on the mailing lists if you need any help.

Open an issue if you found a bug in Flink.

The documentation of Apache Flink is located on the website: https://flink.apache.org or in the docs/ directory of the source code.

This is an active open-source project. We are always open to people who want to use the system or contribute to it. Contact us if you are looking for implementation tasks that fit your skills. This article describes how to contribute to Apache Flink.

Apache Flink is an open source project of The Apache Software Foundation (ASF). The Apache Flink project originated from the Stratosphere research project.