<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Flink on PlumePHP</title><link>https://plumephp.com/tags/flink/</link><description>Recent content in Flink on PlumePHP</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Tue, 01 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://plumephp.com/tags/flink/index.xml" rel="self" type="application/rss+xml"/><item><title>实时数仓架构实战：Kafka + Flink + ClickHouse 流批一体</title><link>https://plumephp.com/realtime-data-warehouse/</link><pubDate>Tue, 01 Sep 2026 00:00:00 +0000</pubDate><guid>https://plumephp.com/realtime-data-warehouse/</guid><description>&lt;p&gt;在数据驱动决策日益重要的今天，传统的 T+1 离线数仓已无法满足业务对实时性的苛刻要求。电商大促的秒级监控、金融风控的毫秒级拦截、物联网设备的实时告警，都要求数据在产生后的秒级甚至毫秒级内完成采集、处理与呈现。本文将带你从零构建一套基于 &lt;strong&gt;Kafka + Flink + ClickHouse&lt;/strong&gt; 的实时数仓架构，实现真正的流批一体（Streaming-Batch Unification）。&lt;/p&gt;</description></item><item><title>05. Apache Flink 实时计算详解</title><link>https://plumephp.com/apache-flink-streaming/</link><pubDate>Thu, 13 Aug 2026 16:05:00 +0800</pubDate><guid>https://plumephp.com/apache-flink-streaming/</guid><description>&lt;p&gt;Apache Flink 是业界领先的分布式流处理引擎，其基于事件时间的窗口计算和精确的 Checkpoint 机制使其成为实时数据处理的首选方案。本文从 DataStream API 出发，深入讲解 Flink 的核心原理与生产实践。&lt;/p&gt;</description></item></channel></rss>