October 13, 2022 -
Jingsong Lee
The Apache Flink Community is pleased to announce the first bug fix release of the Flink Table Store 0.2 series.
This release includes 13 bug fixes, vulnerability fixes, and minor improvements for Flink Table Store 0.2. Below you will find a list of all bugfixes and improvements. For a complete list of all changes see: JIRA.
We highly recommend all users upgrade to Flink Table Store 0.2.1.
Release Artifacts # Binaries # You can find the binaries on the updated Downloads page.
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October 7, 2022 -
Gyula Fora
(@GyulaFora)
We are proud to announce the latest stable release of the operator. The 1.2.0 release adds support for the Standalone Kubernetes deployment mode and includes several improvements to the core logic.
Release Highlights # Standalone deployment mode support Improved upgrade flow Readiness and liveness probes Flexible job jar handling Standalone deployment mode support # Until now the operator relied exclusively on Flink’s built-in Native Kubernetes integration to deploy and manage Flink clusters.
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September 28, 2022 -
Xingbo Huang
The Apache Flink Community is pleased to announce another bug fix release for Flink 1.14.
This release includes 34 bug fixes, vulnerability fixes and minor improvements for Flink 1.14. Below you will find a list of all bugfixes and improvements (excluding improvements to the build infrastructure and build stability). For a complete list of all changes see: JIRA.
We highly recommend all users to upgrade to Flink 1.14.6.
Release Artifacts # Maven Dependencies # <dependency> <groupId>org.
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September 8, 2022 -
Chesnay Schepler
On September 7th Lightbend announced a license change for the Akka project, the TL;DR being that you will need a commercial license to use future versions of Akka (2.7+) in production if you exceed a certain revenue threshold.
Within a few hours of the announcement several people reached out to the Flink project, worrying about the impact this has on Flink, as we use Akka internally.
The purpose of this blogpost is to clarify our position on the matter.
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August 29, 2022 -
Jingsong Lee
The Apache Flink community is pleased to announce the release of the Apache Flink Table Store (0.2.0).
Please check out the full documentation for detailed information and user guides.
What is Flink Table Store # Flink Table Store is a data lake storage for streaming updates/deletes changelog ingestion and high-performance queries in real time.
As a new type of updatable data lake, Flink Table Store has the following features:
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August 24, 2022 -
Danny Cranmer
The Apache Flink Community is pleased to announce the second bug fix release of the Flink 1.15 series.
This release includes 30 bug fixes, vulnerability fixes, and minor improvements for Flink 1.15. Below you will find a list of all bugfixes and improvements (excluding improvements to the build infrastructure and build stability). For a complete list of all changes see: JIRA.
We highly recommend all users upgrade to Flink 1.15.2.
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July 25, 2022 -
Gyula Fora
(@GyulaFora)
Matyas Orhidi
The community has continued to work hard on improving the Flink Kubernetes Operator capabilities since our first production ready release we launched about two months ago.
With the release of Flink Kubernetes Operator 1.1.0 we are proud to announce a number of exciting new features improving the overall experience of managing Flink resources and the operator itself in production environments.
Release Highlights # A non-exhaustive list of some of the more exciting features added in the release:
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July 12, 2022 -
Zhipeng Zhang
Dong Lin
The Apache Flink community is excited to announce the release of Flink ML 2.1.0! This release focuses on improving Flink ML’s infrastructure, such as Python SDK, memory management, and benchmark framework, to facilitate the development of performant, memory-safe, and easy-to-use algorithm libraries. We validated the enhanced infrastructure by implementing, benchmarking, and optimizing 10 new algorithms in Flink ML, and confirmed that Flink ML can meet or exceed the performance of selected algorithms from alternative popular ML libraries.
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July 11, 2022 -
Yun Gao
Dawid Wysakowicz
Daisy Tsang
Motivation # Flink is a distributed processing engine for both unbounded and bounded streams of data. In recent versions, Flink has unified the DataStream API and the Table / SQL API to support both streaming and batch cases. Since most users require both types of data processing pipelines, the unification helps reduce the complexity of developing, operating, and maintaining consistency between streaming and batch backfilling jobs, like the case for Alibaba.
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July 11, 2022 -
Yun Gao
Dawid Wysakowicz
Daisy Tsang
In the first part of this blog, we have briefly introduced the work to support checkpoints after tasks get finished and revised the process of finishing. In this part we will present more details on the implementation, including how we support checkpoints with finished tasks and the revised protocol of the finish process.
Implementation of support Checkpointing with Finished Tasks # As described in part one, to support checkpoints after some tasks are finished, the core idea is to mark the finished operators in checkpoints and skip executing these operators after recovery.
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