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Posted to issues@spark.apache.org by "Xiao Li (JIRA)" <ji...@apache.org> on 2016/10/09 15:30:20 UTC
[jira] [Closed] (SPARK-10838) Repeat to join one DataFrame twice，there will be AnalysisException.
[ https://issues.apache.org/jira/browse/SPARK-10838?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiao Li closed SPARK-10838.
---------------------------
Resolution: Duplicate
> Repeat to join one DataFrame twice，there will be AnalysisException.
> -------------------------------------------------------------------
>
> Key: SPARK-10838
> URL: https://issues.apache.org/jira/browse/SPARK-10838
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.1
> Reporter: Yun Zhao
>
> The detail of exception is:
> {quote}
> Exception in thread "main" org.apache.spark.sql.AnalysisException: resolved attribute(s) col_a#1 missing from col_a#0,col_b#2,col_a#3,col_b#4 in operator !Join Inner, Some((col_b#2 = col_a#1));
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:37)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:44)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:154)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:49)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:103)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:49)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:44)
> at org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:908)
> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:132)
> at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$logicalPlanToDataFrame(DataFrame.scala:154)
> at org.apache.spark.sql.DataFrame.join(DataFrame.scala:554)
> at org.apache.spark.sql.DataFrame.join(DataFrame.scala:521)
> {quote}
> The related codes are：
> {quote}
> import org.apache.spark.sql.SQLContext
> import org.apache.spark.\{SparkContext, SparkConf}
> object DFJoinTest extends App \{
> case class Foo(col_a: String)
> case class Bar(col_a: String, col_b: String)
> val sc = new SparkContext(new SparkConf().setMaster("local").setAppName("DFJoinTest"))
> val sqlContext = new SQLContext(sc)
> import sqlContext.implicits._
> val df1 = sc.parallelize(Array("1")).map(_.split(",")).map(p => Foo(p(0))).toDF()
> val df2 = sc.parallelize(Array("1,1")).map(_.split(",")).map(p => Bar(p(0), p(1))).toDF()
> val df3 = df1.join(df2, df1("col_a") === df2("col_a")).select(df1("col_a"), $"col_b")
> df3.join(df2, df3("col_b") === df2("col_a")).show()
> // val df4 = df2.as("df4")
> // df3.join(df4, df3("col_b") === df4("col_a")).show()
> // df3.join(df2.as("df4"), df3("col_b") === $"df4.col_a").show()
> sc.stop()
> }
> {quote}
> When uses
> {quote}
> val df4 = df2.as("df4")
> df3.join(df4, df3("col_b") === df4("col_a")).show()
> {quote}
> there's errors,but when uses
> {quote}
> df3.join(df2.as("df4"), df3("col_b") === $"df4.col_a").show()
> {quote}
> it's normal.
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