streaming实时计算 Flink版框架的相关内容

阿里云文档 2025-02-06

Flink SQL Streaming节点使用

DataWorks新版数据开发中的Flink SQL Streaming节点支持使用标准SQL语句定义实时任务处理逻辑。Flink SQL Streaming具有易用性、丰富的SQL支持、强大的状态管理及容错能力，兼容事件时间和处理时间，并可灵活扩展。该节点易于与Kafka、HDFS等系统集成，提供详尽的日志和性能监控工具。您只需在DataWorks项目中添加Flink SQL Streaming...

文章 2024-11-18 来自：开发者社区

Structured Streaming和Flink实时计算框架的对比

目前公司的业务代码大部分使用的还是Structured Streaming，但近期Flink的发展和社区活跃度明显高了很多，因此，借助这个机会对比一下Structured Streaming和Flink，分析两者的优劣势。 Structured Streaming和Flink都是现代流数据处理框架，它们在分布式计算、实时数据...

文章 2023-07-12 来自：开发者社区

Spark Streaming实时计算框架

Spark Streaming实时计算框架近年来，在Web应用、网络监控、传感监测、电信金融、生产制造等领域，增强了对数据实时处理的需求，而Spark中的Spark Streaming实时计算框架就是为实现对数据实时处理的需求而设计 1，什么是实时计算在传统的数据处理流程（==离线计算==）中，复杂的业务处理流程会造成结果数据密集，结果数据密集则存在数据反馈不及时，若是...

文章 2022-06-13 来自：开发者社区

Storm vs. Kafka Streams vs. Spark Streaming vs. Flink ，流式处理框架一网打尽！2

五、现有流处理框架介绍5.1 StormStorm是最老的流媒体框架，技术成熟可靠。社区也很活跃。ali还开发了jstorm，对storm进行了拓展完善。后续jstorm也融入到storm中，对于storm也是一个质的提升。比较适合于基于事件的一些简单用例场景。优点：极低的延迟，真正的流媒体，成熟和高吞吐量非常适合非复杂的流媒体用例缺点：不支持状态管理没有事件时间处理，聚合，窗口，会话，水印等高....

文章 2022-06-13 来自：开发者社区

Storm vs. Kafka Streams vs. Spark Streaming vs. Flink ，流式处理框架一网打尽！1

文章目录一、前言二、什么是流式处理三、流式处理的重点有哪些3.1 交付保障3.2 故障容错3.3 状态管理3.4 性能3.5 成熟四、流式处理的两种类型4.1 Native流4.2 小批量处理4.3 两种类型都有一些优点和缺点五、现有流处理框架介绍5.1 Storm5.2 Spark Streaming5.3 Flink5.4 Kafka Steams5.5 Kafka Streams vs. ....

文章 2022-06-13 来自：开发者社区

Spark Streaming，Flink，Storm，Kafka Streams，Samza：如何选择流处理框架

如今，有许多可用的开源流框架。有趣的是，几乎所有它们都是相当新的，仅在最近几年才开发出来。因此，对于新手来说，很容易混淆流框架之间的理解和区分。在本文中，我将首先大致讨论流处理的类型和方面，然后比较最受欢迎的开源流框架：Flink，SparkStreaming，Storm，KafkaStream。我将尝试（简要地）解释它们的工作原理，它们的用例，优势，局限性，异同。什么是流/流处理：流处理的最优....

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实时计算Flink版

阿里云实时计算Flink版(Alibaba Cloud Realtime Compute)，完全兼容开源的Apache Flink，比开源性能提升2～3倍，提供了完整的告警、监控、日志的解决方案、提升开发效率且无运维成本，并有社区专家提供技术支持。

立即开通

产品控制台

产品文档

实时同步

MySQL 到 Hologres

Kafka 到 Hologres

功能对比

开源Flink对比

成本优化

作业自动调优