Getting Started with Flink
Install Apache Flink on your machine now and get started with Flink today.
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Introduction to Apache Flink
Flink Environment Setup- Ubuntu
Flink Environment Setup- Windows
Flink Environment Setup- Multinode Cluster
Why Apache Flink- its Features
A Comprehensive Guide- Flink History, Architecture, Features
Flink Ecosystem Components
Best Apache Flink Books
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Flink Shell Commands
Flink Streaming Windows
Setting up a Flink Cluster on CentOS
Complex Event Processing in Flink
Create a Flink Application in Java Eclipse
Flink Wordcount Program
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Apache Flink – A Big Data Processing Framework
Flink Use Cases: Real-life Case Studies
Big Data Use Cases: Hadoop, Spark, and Flink Case Studies
Flink Use Case- Crime Data Analysis- Part 1
Flink Use Case- Crime Data Analysis- Part 2
Hadoop + Flink Compatibility
Flink vs Spark
Flink vs Spark vs Hadoop
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Exploring the Framework
Let’s take a look at some facts about Flink and its philosophies.
The creators of Flink were on a university research project when they decided to turn it into a full-fledged company. They founded data Artisans in 2014 as an attempt to build a large-scale data processing technology which is both open-source and rooted in long-tested principles and architectures. Flink is an open-source stream-processing framework now under the Apache Software Foundation. It is built around a distributed streaming dataflow engine which is written in Java and Scala, and executes arbitrary dataflow programs in a way that is parallel and pipelined.
Programs in Java, Scala, Python, and SQL automatically compile and optimize into dataflow programs which we then execute in a cluster or cloud environment.
data Artisans