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{"id":1851,"date":"2021-01-15T06:00:51","date_gmt":"2021-01-15T12:00:51","guid":{"rendered":"https:\/\/www.bigdatainrealworld.com\/?p=1851"},"modified":"2023-02-19T07:31:58","modified_gmt":"2023-02-19T13:31:58","slug":"how-does-broadcast-hash-join-work-in-spark","status":"publish","type":"post","link":"https:\/\/www.bigdatainrealworld.com\/how-does-broadcast-hash-join-work-in-spark\/","title":{"rendered":"How does Broadcast Hash Join work in Spark?"},"content":{"rendered":"Broadcast Hash Join in Spark works by broadcasting the small dataset to all the executors and once the data is broadcasted a standard hash join is performed in all the executors. Broadcast Hash Join happens in 2 phases.<\/span><\/p>\nBroadcast phase<\/strong> – small dataset is broadcasted to all executors<\/span><\/p>\nHash Join phase<\/strong> – small dataset is hashed in all the executors and joined with the partitioned big dataset.<\/span><\/p>\nBroadcast Hash Join doesn\u2019t involve a sort operation and it is one of the reasons it is the\u00a0 fastest join algorithm. We will see in detail how it works with an example.<\/span>
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