Maciej Bryński created SPARK-11282: --------------------------------------
Summary: Very strange broadcast join behaviour Key: SPARK-11282 URL: https://issues.apache.org/jira/browse/SPARK-11282 Project: Spark Issue Type: Bug Components: PySpark, SQL Affects Versions: 1.5.1 Reporter: Maciej Bryński Priority: Critical Hi, I found very strange broadcast join behaviour. According to this Jira https://issues.apache.org/jira/browse/SPARK-10577 I'm using hint for broadcast join. (I patched 1.5.1 with https://github.com/apache/spark/pull/8801/files ) I found that working of this feature depends on Executor Memory. In my case broadcast join is working up to 31G. Example: spark1:~/ab$ ~/spark/bin/spark-submit --executor-memory 31G debug_broadcast_join.py true Creating test tables... Joining tables... Joined table schema: root |-- id: long (nullable = true) |-- val: long (nullable = true) |-- id2: long (nullable = true) |-- val2: long (nullable = true) Selecting data for id = 5... [Row(id=5, val=5, id2=5, val2=5)] spark$ ~/spark/bin/spark-submit --executor-memory 32G debug_broadcast_join.py true Creating test tables... Joining tables... Joined table schema: root |-- id: long (nullable = true) |-- val: long (nullable = true) |-- id2: long (nullable = true) |-- val2: long (nullable = true) Selecting data for id = 5... [Row(id=5, val=5, id2=None, val2=None)] Please find example code attached. -- 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