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
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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
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分层 API
  • SQL on Stream & Batch Data
  • DataStream API & DataSet API
  • ProcessFunction (Time & State)
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聚焦运维
  • 灵活部署
  • 高可用
  • 保存点
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大规模计算
  • 水平扩展架构
  • 支持超大状态
  • 增量检查点机制
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性能卓越
  • 低延迟
  • 高吞吐
  • 内存计算
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Getting into Low-Latency Gears with Apache Flink - Part One
This multi-part series of blog post presents a collection of low-latency techniques in Flink. Part one starts with types of latency in Flink and the way we measure the end-to-end latency, followed by a few techniques that optimize latency directly.
Apache Flink Table Store 0.1.0 Release Announcement

The Apache Flink community is pleased to announce the preview release of the Apache Flink Table Store (0.1.0).

The Generic Asynchronous Base Sink
An overview of the new AsyncBaseSink and how to use it for building your own concrete sink
Exploring the thread mode in PyFlink
Flink 1.15 introduced a new Runtime Execution Mode named 'thread' mode in PyFlink. This post explains how it works and when to use it.
Improvements to Flink operations: Snapshots Ownership and Savepoint Formats
This post will outline the journey of improving snapshotting in past releases and the upcoming improvements in Flink 1.15, which includes making it possible to take savepoints in the native state backend specific format as well as clarifying snapshots ownership.