Apache Flink is an open source stream processing framework with powerful stream- and batch-processing capabilities.

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

• A streaming-first runtime that supports both batch processing and data streaming programs

• Elegant and fluent APIs in Java and Scala

• A runtime that supports very high throughput and low event latency at the same time

• Support for event time and out-of-order processing in the DataStream API, based on the Dataflow Model

• Flexible windowing (time, count, sessions, custom triggers) across different time semantics (event time, processing time)

• Fault-tolerance with exactly-once processing guarantees

• Natural back-pressure in streaming programs

• Libraries for Graph processing (batch), Machine Learning (batch), and Complex Event Processing (streaming)

• Built-in support for iterative programs (BSP) in the DataSet (batch) API

• Custom memory management for efficient and robust switching between in-memory and out-of-core data processing algorithms

• Compatibility layers for Apache Hadoop MapReduce

• Integration with YARN, HDFS, HBase, and other components of the Apache Hadoop ecosystem

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

val text = env.socketTextStream(host, port, '\n')

val windowCounts = text.flatMap { w => w.split("\\s") }
  .map { w => WordWithCount(w, 1) }
  .keyBy("word")
  .timeWindow(Time.seconds(5))
  .sum("count")

windowCounts.print()

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

val text = env.readTextFile(path)

val counts = text.flatMap { w => w.split("\\s") }
  .map { w => WordWithCount(w, 1) }
  .groupBy("word")
  .sum("count")

counts.writeAsCsv(outputPath)

Prerequisites for building Flink:

• Unix-like environment (we use Linux, Mac OS X, Cygwin)
• git
• Maven (we recommend version 3.2.5)
• Java 8 (Java 9 and 10 are not yet supported)

git clone https://github.com/apache/flink.git
cd flink
mvn clean package -DskipTests # this will take up to 10 minutes

Flink is now installed in build-target

NOTE: Maven 3.3.x can build Flink, but will not properly shade away certain dependencies. Maven 3.0.3 creates the libraries properly. To build unit tests with Java 8, use Java 8u51 or above to prevent failures in unit tests that use the PowerMock runner.

The Flink committers use IntelliJ IDEA to develop the Flink codebase. We recommend IntelliJ IDEA for developing projects that involve Scala code.

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: http://plugins.jetbrains.com/plugin/?id=1347

Check out our Setting up IntelliJ guide for details.

NOTE: From our experience, this setup does not work with Flink due to deficiencies of the old Eclipse version bundled with Scala IDE 3.0.3 or due to version incompatibilities with the bundled Scala version in Scala IDE 4.4.1.

We recommend to use IntelliJ instead (see above)

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: http://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.

我们的源码主要都封装在了Flink-runtime 和 Flink-streaming-java里（目前还是一个prototype），如果是看源码的话，我们有两个入口，Controller是从MorphlingController.java运行的，Metrics是从MetricsManager出发的。

用途上，我们expose了几个配置在flink-conf.yaml中，默认情况下，我们的实验是在一个single operator的word count上做的。 其中，可以替换config来跑对应的stream job。 model.vertex 可以设置需要做Scaling的operator，我们的prototype暂时只对一个operator做scaling。（有一些其他的config可以暂时不用管）

这里有一张我们以前的系统架构图，希望可以提供一定的参考，这里StreamSwitch可以替换成Morphling。