Part 17 of this series introduces several possible Shuffle methods and their adoption in MapReduce and Spark.
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 explains the core ideas and design of DAG.
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.
