Flink

Website	http://flink.apache.org/
Supported versions	1.5.1 for Hadoop 2.8 and Scala 2.11
	1.5.1 for Hadoop 2.7 and Scala 2.11
	1.5.0 for Hadoop 2.8 and Scala 2.11
	1.5.0 for Hadoop 2.7 and Scala 2.11
	1.4.2 for Hadoop 2.8 and Scala 2.11
	1.4.2 for Hadoop 2.7 and Scala 2.11
	1.4.1 for Hadoop 2.8 and Scala 2.11
	1.4.1 for Hadoop 2.7 and Scala 2.11
	1.4.0 for Hadoop 2.8 and Scala 2.11
	1.4.0 for Hadoop 2.7 and Scala 2.11
	1.3.2 for Hadoop 2.7 and Scala 2.11
	1.3.1 for Hadoop 2.7 and Scala 2.11
	1.3.0 for Hadoop 2.7 and Scala 2.11
	1.2.1 for Hadoop 2.7 and Scala 2.11
	1.2.0 for Hadoop 2.7 and Scala 2.11
	1.1.4 for Hadoop 2.7 and Scala 2.11
	1.1.3 for Hadoop 2.7 and Scala 2.11
	0.10.2 for Hadoop 2.7 and Scala 2.11
	0.10.1 for Hadoop 2.7 and Scala 2.11
Current responsible(s)	Gezim Sejdiu @ UBO -- [email protected]
	Hajira Jabeen @ UBO -- [email protected]
	Ivan Ermilov @ InfAI -- [email protected]
Docker image(s)	bde2020/flink-master:latest
	bde2020/flink-worker:latest
	bde2020/flink-submit:latest
	bde2020/flink-maven-template:latest
	bde2020/flink-sbt-template:latest
More info	https://ci.apache.org/projects/flink/flink-docs-release-0.10/apis/programming_guide.html

Short description

Apache Flink is an open source platform for distributed stream and batch data processing.

Flink’s core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams.

Flink includes several APIs for creating applications that use the Flink engine:

• DataSet API for static data embedded in Java, Scala, and Python,
• DataStream API for unbounded streams embedded in Java and Scala, and
• Table API with a SQL-like expression language embedded in Java and Scala.

Flink also bundles libraries for domain-specific use cases:

• CEP, a complex event processing library,
• Machine Learning library, and
• Gelly, a graph processing API and library.

You can integrate Flink easily with other well-known open source systems both for data input and output as well as deployment.

Example usage

Building and running your Flink application on top of the Flink cluster can be done by extending a template Docker image. Check the template's README for further documentation.

• Maven template
• SBT template

Scaling

DataSet and DataStream are fault-tolerant collections of elements that can be operated on in parallel. As a consequence, Flink applications scale automatically when augmenting the number of Flink worker nodes in the cluster.