Apache Flink Community China
FollowPart 2 of this 5-part series explains how to realize Flink MongoDB CDC Connector through MongoDB Change Streams features based on Flink CDC.
Part 1 of this 5-part series explains how to use Flink CDC to simplify the entry of real-time data into the database.
This article is compiled from the topic "Exploration of Advanced Functions in Pravega Flink Connector Table API," shared by Zhou Yumin in Flink Forward Asia 2021.
This article mainly explains which dependencies need to be introduced and which need to be packaged into the job JAR during the job development.
Mowen discusses the future of Apache Flink regarding its core capabilities of stream computing and improving the processing standards of the entire industry.
This article is compiled from the presentation of JD search and recommendation algorithm engineers Zhang Ying and Liu Lu at Flink Forward Asia 2021.
This article introduces the research and development background and the design and use of Flink Remote Shuffle.
This tutorial explains how to quickly build streaming ETL for MySQL and Postgres with Flink CDC.
This article discusses scheduler performance improvements for large-scale jobs in Flink 1.13 and 1.14.
This article explains thoroughly how iQiyi (a Chinese online video platform) utilizes Apache Flink.
The article mainly introduces two applications of real-time big data based on Flink.
Part 2 of this 2-part series will give you insight into some core design considerations and implementation details of the sort-based blocking shuffle in Flink.
Part 1 of this 2-part series will introduce the sort-based blocking shuffle, present benchmark results, and provide guidelines on how to use this new feature.
This article introduces the real-time data warehouse architecture built by Kwai based on Flink and offers solutions to some difficult problems.
This article focuses on the optimization measures of Jingdong in Flink SQL tasks, focusing on the aspects of shuffle, join mode selection, object reuse, and UDF reuse.
This article introduces a PyFlink development environment tool that can help users solve various problems.
This article introduces the optimization and evolution of Flink Hudi's original mini-batch-based incremental computing model through stream computing.
This article gives a detailed interpretation of Flink Connector from the four aspects: connectors, Source API, Sink API, and the future development of collectors.
This article describes how Flink SQL connects to external systems and introduces commonly used Flink SQL Connectors.
This article introduces the objectives and the development of the PyFlink project as well as its current core features.
5444248861672821 Commented on Streaming ETL for MySQL and Postgres with Flink CDC
Arman Ali Commented on Flink: How to Optimize SQL Performance Using Multiple-input Operators
