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{"id":1697,"date":"2021-09-24T06:00:00","date_gmt":"2021-09-24T11:00:00","guid":{"rendered":"https:\/\/www.bigdatainrealworld.com\/?p=1697"},"modified":"2023-02-19T07:31:05","modified_gmt":"2023-02-19T13:31:05","slug":"why-do-i-see-200-tasks-in-spark-execution","status":"publish","type":"post","link":"https:\/\/www.bigdatainrealworld.com\/why-do-i-see-200-tasks-in-spark-execution\/","title":{"rendered":"Why do I see 200 tasks in Spark execution?"},"content":{"rendered":"

It is quite common to see 200 tasks in one of your stages and more specifically at a stage which requires wide transformation. The reason for this is, wide transformations in Spark requires a shuffle. Operations like join, group by etc. are wide transform operations and they trigger a shuffle.<\/span><\/p>\n

By default, Spark creates 200 partitions whenever there is a need for shuffle. Each partition will be processed by a task. So, you will end up with 200 tasks during execution.<\/span>
\n