Overview
In this post, I will go through 12 core Apache Flink concepts to better understand what it does and how it works. This article could perfectly serve as a beginner's overview of Flink and Streaming engine terminology.
1.
What is Apache
Flink?
At first glance, the origins of Apache Flink can be traced back to
June 2008 as a researching project of the Database Systems and Information
Management (DIMA) Group at the Technische Universität (TU) Berlin in Germany.
Apache Flink is an open source platform for distributed stream and
batch data processing, initially it was designed as an alternative to MapReduce
and the Hadoop Distributed File System (HFDS) in Hadoop origins.
According to the Apache Flink project, it 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 also builds batch processing on top of the streaming
engine, overlaying native iteration support, managed memory, and program
optimization.”
