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Posted to issues@spark.apache.org by "Davies Liu (JIRA)" <ji...@apache.org> on 2016/09/06 21:52:20 UTC
[jira] [Closed] (SPARK-17384) SQL - Running query with outer join
from 1.6 fails
[ https://issues.apache.org/jira/browse/SPARK-17384?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Davies Liu closed SPARK-17384.
------------------------------
Resolution: Duplicate
Assignee: Herman van Hovell
> SQL - Running query with outer join from 1.6 fails
> --------------------------------------------------
>
> Key: SPARK-17384
> URL: https://issues.apache.org/jira/browse/SPARK-17384
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Don Drake
> Assignee: Herman van Hovell
>
> I have some complex (10-table joins) SQL queries that utilize outer joins that work fine in Spark 1.6.2, but fail under Spark 2.0. I was able to duplicate the problem using a simple test case.
> Here's the code for Spark 2.0 that doesn't run (this runs fine in Spark 1.6.2):
> {code}
> case class C1(f1: String, f2: String, f3: String, f4: String)
> case class C2(g1: String, g2: String, g3: String, g4: String)
> case class C3(h1: String, h2: String, h3: String, h4: String)
> val sqlContext = spark.sqlContext
> val c1 = sc.parallelize(Seq(
> C1("h1", "c1a1", "c1b1", "c1c1"),
> C1("h2", "c1a2", "c1b2", "c1c2"),
> C1(null, "c1a3", "c1b3", "c1c3")
> )).toDF
> c1.createOrReplaceTempView("c1")
> val c2 = sc.parallelize(Seq(
> C2("h1", "c2a1", "c2b1", "c2c1"),
> C2("h2", "c2a2", "c2b2", "c2c2"),
> C2(null, "c2a3", "c2b3", "c2c3"),
> C2(null, "c2a4", "c2b4", "c2c4"),
> C2("h333", "c2a333", "c2b333", "c2c333")
> )).toDF
> c2.createOrReplaceTempView("c2")
> val c3 = sc.parallelize(Seq(
> C3("h1", "c3a1", "c3b1", "c3c1"),
> C3("h2", "c3a2", "c3b2", "c3c2"),
> C3(null, "c3a3", "c3b3", "c3c3")
> )).toDF
> c3.createOrReplaceTempView("c3")
> // doesn't work in Spark 2.0, works in Spark 1.6
> val bad_df = sqlContext.sql("""
> select *
> from c1, c3
> left outer join c2 on (c1.f1 = c2.g1)
> where c1.f1 = c3.h1
> """).show()
> // works in both
> val works_df = sqlContext.sql("""
> select *
> from c1
> left outer join c2 on (c1.f1 = c2.g1),
> c3
> where c1.f1 = c3.h1
> """).show()
> {code}
> Here's the output after running bad_df in Spark 2.0:
> {code}
> scala> val bad_df = sqlContext.sql("""
> | select *
> | from c1, c3
> | left outer join c2 on (c1.f1 = c2.g1)
> | where c1.f1 = c3.h1
> | """).show()
> org.apache.spark.sql.AnalysisException: cannot resolve '`c1.f1`' given input columns: [h3, g3, h4, g2, g4, h2, h1, g1]; line 4 pos 25
> at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:77)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:74)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:301)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:301)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:300)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:298)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:298)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:321)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:179)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:319)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:298)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionUp$1(QueryPlan.scala:190)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:201)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$5.apply(QueryPlan.scala:209)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:179)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:209)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:74)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:67)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:126)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:125)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:125)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:125)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:125)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:125)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:125)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:125)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:125)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:125)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:67)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:58)
> at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:582)
> at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:682)
> ... 53 elided
> scala>
> {code}
> I confirmed this fails on the Spark 2.0 nightly build as well. This runs just fine in Spark 1.6.2.
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