Apache Flink is an open source platform for distributed stream and batch data processing. Flink is a streaming data flow engine with several APIs to create data streams oriented application.
It is very common for Flink applications to use Apache Kafka for data input and output. This article will guide you into the steps to use Apache Flink with Kafka.
In this article you will learn how to create a MapR Streams Consumer that saves all the messages into a MapR-DB JSON Table.
You can find a new tutorial that explains how to deploy an Apache Kafka application to MapR Streams, the tutorial is available here:
MapR Streams is a new distributed messaging system for streaming event data at scale, and it’s integrated into the MapR converged platform. MapR Streams uses the Apache Kafka API, so if you’re already familiar with Kafka, you’ll find it particularly easy to get started with MapR Streams.
Ted Dunning and I have worked on a tutorial that explains how to write your first Kafka application. In this tutorial you will learn how to:
You can find the tutorial on the MapR blog:
