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https://issues.apache.org/jira/browse/SPARK-9735?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-9735:
------------------------------------
Target Version/s: 1.6.0 (was: 1.5.0)
> Auto infer partition schema of HadoopFsRelation should should respected the
> user specified one
> ----------------------------------------------------------------------------------------------
>
> Key: SPARK-9735
> URL: https://issues.apache.org/jira/browse/SPARK-9735
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: Cheng Hao
> Assignee: Cheng Lian
>
> This code is copied from the hadoopFsRelationSuite.scala
> {code}
> partitionedTestDF = (for {
> i <- 1 to 3
> p2 <- Seq("foo", "bar")
> } yield (i, s"val_$i", 1, p2)).toDF("a", "b", "p1", "p2")
> withTempPath { file =>
> val input = partitionedTestDF.select('a, 'b,
> 'p1.cast(StringType).as('ps), 'p2)
> input
> .write
> .format(dataSourceName)
> .mode(SaveMode.Overwrite)
> .partitionBy("ps", "p2")
> .saveAsTable("t")
> withTempTable("t") {
> checkAnswer(sqlContext.table("t"), input.collect())
> }
> }
> 11.521 ERROR org.apache.spark.executor.Executor: Exception in task 2.0 in
> stage 2.0 (TID 130)
> java.lang.ClassCastException: java.lang.Integer cannot be cast to
> org.apache.spark.unsafe.types.UTF8String
> at
> org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow$class.getUTF8String(rows.scala:45)
> at
> org.apache.spark.sql.catalyst.expressions.SpecificMutableRow.getUTF8String(SpecificMutableRow.scala:195)
> at
> org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toScalaImpl(CatalystTypeConverters.scala:297)
> at
> org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toScalaImpl(CatalystTypeConverters.scala:289)
> at
> org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toScala(CatalystTypeConverters.scala:110)
> at
> org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toScala(CatalystTypeConverters.scala:278)
> at
> org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toScala(CatalystTypeConverters.scala:245)
> at
> org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToScalaConverter$2.apply(CatalystTypeConverters.scala:406)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$3$$anonfun$apply$2.apply(SparkPlan.scala:194)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$3$$anonfun$apply$2.apply(SparkPlan.scala:194)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:905)
> at
> org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:905)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1836)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1836)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
> {code}
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