Apache Flink® — Stateful Computations over Data Streams

All streaming use cases
  • Event-driven Applications
  • Stream & Batch Analytics
  • Data Pipelines & ETL
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Guaranteed correctness
  • Exactly-once state consistency
  • Event-time processing
  • Sophisticated late data handling
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Layered APIs
  • SQL on Stream & Batch Data
  • DataStream API & DataSet API
  • ProcessFunction (Time & State)
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Operational Focus
  • Flexible deployment
  • High-availability setup
  • Savepoints
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Scales to any use case
  • Scale-out architecture
  • Support for very large state
  • Incremental checkpointing
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Excellent Performance
  • Low latency
  • High throughput
  • In-Memory computing
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Apache Flink 1.11.0 Release Announcement
The Apache Flink community is proud to announce the release of Flink 1.11.0! More than 200 contributors worked on over 1.3k issues to bring significant improvements to usability as well as new features to Flink users across the whole API stack. We're particularly excited about unaligned checkpoints to cope with high backpressure scenarios, a new source API that simplifies and unifies the implementation of (custom) sources, and support for Change Data Capture (CDC) and other common use cases in the Table API/SQL. Read on for all major new features and improvements, important changes to be aware of and what to expect moving forward!
Flink on Zeppelin Notebooks for Interactive Data Analysis - Part 2

In a previous post, we introduced the basics of Flink on Zeppelin and how to do Streaming ETL. In this second part of the “Flink on Zeppelin” series of posts, I will share how to perform streaming data visualization via Flink on Zeppelin and how to use Apache Flink UDFs in Zeppelin.

Flink on Zeppelin Notebooks for Interactive Data Analysis - Part 1

The latest release of Apache Zeppelin comes with a redesigned interpreter for Apache Flink (version Flink 1.10+ is only supported moving forward) that allows developers to use Flink directly on Zeppelin notebooks for interactive data analysis. I wrote 2 posts about how to use Flink in Zeppelin. This is part-1 where I explain how the Flink interpreter in Zeppelin works, and provide a tutorial for running Streaming ETL with Flink on Zeppelin.

Flink Community Update - June'20
And suddenly it’s June. The previous month has been calm on the surface, but quite hectic underneath — the final testing phase for Flink 1.11 is moving at full speed, Stateful Functions 2.1 is out in the wild and Flink has made it into Google Season of Docs 2020.
Stateful Functions 2.1.0 Release Announcement

The Apache Flink community is happy to announce the release of Stateful Functions (StateFun) 2.1.0! This release introduces new features around state expiration and performance improvements for co-located deployments, as well as other important changes that improve the stability and testability of the project. As the community around StateFun grows, the release cycle will follow this pattern of smaller and more frequent releases to incorporate user feedback and allow for faster iteration.