Mohit created SPARK-18642:
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Summary: Spark SQL: Catalyst is scanning undesired columns
Key: SPARK-18642
URL: https://issues.apache.org/jira/browse/SPARK-18642
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.6.2
Environment: Ubuntu 14.04
Spark: Local Mode
Reporter: Mohit
When doing a left-join between two tables, say A and B, Catalyst has
information about the projection required for table B.
Code snippet below explains the scenario:
scala> val dfA = sqlContext.read.parquet("/home/mohit/ruleA")
dfA: org.apache.spark.sql.DataFrame = [aid: int, aVal: string]
scala> val dfB = sqlContext.read.parquet("/home/mohit/ruleB")
dfB: org.apache.spark.sql.DataFrame = [bid: int, bVal: string]
scala> dfA.registerTempTable("A")
scala> dfB.registerTempTable("B")
scala> sqlContext.sql("select A.aid, B.bid from A left join B on A.aid=B.bid
where B.bid<2").explain
== Physical Plan ==
Project [aid#15,bid#17]
+- Filter (bid#17 < 2)
+- BroadcastHashOuterJoin [aid#15], [bid#17], LeftOuter, None
:- Scan ParquetRelation[aid#15,aVal#16] InputPaths: file:/home/mohit/ruleA
+- Scan ParquetRelation[bid#17,bVal#18] InputPaths: file:/home/mohit/ruleB
This is a watered-down example from a production issue which has a huge
performance impact.
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