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https://issues.apache.org/jira/browse/SPARK-6231?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14372282#comment-14372282
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Michael Armbrust commented on SPARK-6231:
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[~davies] I think this might be related to [SPARK-6247], which has now been
fixed. Would you be able to test this again with branch-1.3 or provide me with
the data so I can test?
> Join on two tables (generated from same one) is broken
> ------------------------------------------------------
>
> Key: SPARK-6231
> URL: https://issues.apache.org/jira/browse/SPARK-6231
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.3.0, 1.4.0
> Reporter: Davies Liu
> Assignee: Michael Armbrust
> Priority: Blocker
> Labels: DataFrame
>
> If the two column used in joinExpr come from the same table, they have the
> same id, then the joniExpr is explained in wrong way.
> {code}
> val df = sqlContext.load(path, "parquet")
> val txns = df.groupBy("cust_id").agg($"cust_id",
> countDistinct($"day_num").as("txns"))
> val spend = df.groupBy("cust_id").agg($"cust_id",
> sum($"extended_price").as("spend"))
> val rmJoin = txns.join(spend, txns("cust_id") === spend("cust_id"), "inner")
> scala> rmJoin.explain
> == Physical Plan ==
> CartesianProduct
> Filter (cust_id#0 = cust_id#0)
> Aggregate false, [cust_id#0], [cust_id#0,CombineAndCount(partialSets#25) AS
> txns#7L]
> Exchange (HashPartitioning [cust_id#0], 200)
> Aggregate true, [cust_id#0], [cust_id#0,AddToHashSet(day_num#2L) AS
> partialSets#25]
> PhysicalRDD [cust_id#0,day_num#2L], MapPartitionsRDD[1] at map at
> newParquet.scala:542
> Aggregate false, [cust_id#17], [cust_id#17,SUM(PartialSum#38) AS spend#8]
> Exchange (HashPartitioning [cust_id#17], 200)
> Aggregate true, [cust_id#17], [cust_id#17,SUM(extended_price#20) AS
> PartialSum#38]
> PhysicalRDD [cust_id#17,extended_price#20], MapPartitionsRDD[3] at map at
> newParquet.scala:542
> {code}
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