Herman van Hovell tot Westerflier created SPARK-8682: --------------------------------------------------------
Summary: Range Join for Spark SQL Key: SPARK-8682 URL: https://issues.apache.org/jira/browse/SPARK-8682 Project: Spark Issue Type: Improvement Components: SQL Reporter: Herman van Hovell tot Westerflier Currently Spark SQL uses a Broadcast Nested Loop join (or a filtered Cartesian Join) when it has to execute the following range query: {noformat} SELECT A.*, B.* FROM tableA A JOIN tableB B ON A.start <= B.end AND A.end > B.start {noformat} This is horribly inefficient. The performance of this query can be greatly improved, when one of the tables can be broadcasted, by creating a range index. A range index is basically a sorted map containing the rows of the smaller table, indexed by both the high and low keys. using this structure the complexity of the query would go from O(N * M) to O(N * 2 * LOG(M)), N = number of records in the larger table, M = number of records in the smaller (indexed) table. I have created a prototype for this. According to the [Spark SQL: Relational Data Processing in Spark|http://people.csail.mit.edu/matei/papers/2015/sigmod_spark_sql.pdf] paper similar work (page 11, section 7.2) has already been done by the ADAM project (cannot locate the code though). So before charging ahead, by creating a PR, I would like to know first if this is worth the effort. Any comments and/or feedback are greatly appreciated. -- 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