+1 on this SPIP. This is a more generalized version of bucketed tables and bucketed joins which can eliminate very expensive data shuffles when joins, and many users in the Apache Spark community have wanted this feature for a long time!
Thank you, Ryan and Chao, for working on this, and I look forward to it as a new feature in Spark 3.3 DB Tsai | https://www.dbtsai.com/ | PGP 42E5B25A8F7A82C1 On Fri, Oct 22, 2021 at 12:18 PM Chao Sun <sunc...@apache.org> wrote: > > Hi, > > Ryan and I drafted a design doc to support a new type of join: storage > partitioned join which covers bucket join support for DataSourceV2 but is > more general. The goal is to let Spark leverage distribution properties > reported by data sources and eliminate shuffle whenever possible. > > Design doc: > https://docs.google.com/document/d/1foTkDSM91VxKgkEcBMsuAvEjNybjja-uHk-r3vtXWFE > (includes a POC link at the end) > > We'd like to start a discussion on the doc and any feedback is welcome! > > Thanks, > Chao --------------------------------------------------------------------- To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
