Dima Zhiyanov created SPARK-6072: ------------------------------------ Summary: Enable hash joins for nullable columns Key: SPARK-6072 URL: https://issues.apache.org/jira/browse/SPARK-6072 Project: Spark Issue Type: Improvement Components: SQL Affects Versions: 1.2.1 Reporter: Dima Zhiyanov
Currently joins such as A join B on A.x = B.x AND A.y <=> B.y are evaluated as hash join on just x followed by filter on y. This causes a skew problem (very long join) when a particular value of x has a high cardinality even though (x, y) is evenly distributed Can we implement is as a hash join on (X, Option(Y))? This will eliminate the skew in this case Imagine a join: People as p1 join People as p2 on p1.name = p2.name and p1.address <=> p2.address (very small percentage of people has unknown address) This causes a skewed join on popular names such as "Mary Brown" if we hash on names alone, but will not cause a skew if we hash on (Name, Option(Address)) -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org