Apache Flink® - 数据流上的有状态计算 #

所有流式场景

事件驱动应用
流批分析
数据管道 & ETL

了解更多

正确性保证

Exactly-once 状态一致性
事件时间处理
成熟的迟到数据处理

了解更多

分层 API

SQL on Stream & Batch Data
DataStream API & DataSet API
ProcessFunction (Time & State)

了解更多

聚焦运维

灵活部署
高可用
保存点

了解更多

大规模计算

水平扩展架构
支持超大状态
增量检查点机制

了解更多

性能卓越

低延迟
高吞吐
内存计算

了解更多

最新博客列表 #

Announcing the Release of Apache Flink 1.17
The Apache Flink PMC is pleased to announce Apache Flink release 1.17.0. Apache Flink is the leading stream processing standard, and the concept of unified stream and batch data processing is being successfully adopted in more and more companies. Thanks to our excellent community and contributors, Apache Flink continues to grow as a technology and remains one of the most active projects in the Apache Software Foundation. Flink 1.17 had 172 contributors enthusiastically participating and saw the completion of 7 FLIPs and 600+ issues, bringing many exciting new features and improvements to the community.

Apache Flink 1.15.4 Release Announcement
The Apache Flink Community is pleased to announce the fourth bug fix release of the Flink 1.15 series. This release includes 53 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 1.15.4.

Apache Flink Kubernetes Operator 1.4.0 Release Announcement
We are proud to announce the latest stable release of the operator. In addition to the expected stability improvements and fixes, the 1.4.0 release introduces the first version of the long-awaited autoscaler module. Flink Streaming Job Autoscaler # A highly requested feature for Flink applications is the ability to scale the pipeline based on incoming data load and the utilization of the dataflow. While Flink has already provided some of the required building blocks, this feature has not yet been realized in the open source ecosystem.