spark提示Caused by: java.lang.ClassCastException: scala.collection.mutable.WrappedArray$ofRef cannot be cast to [Lscala.collection.immutable.Map;
spark提示Caused by: java.lang.ClassCastException: scala.collection.mutable.WrappedArray$ofRef cannot be cast to [Lscala.collection.immutable.Map;
起因
编写了一个处理两列是否相等的UDF，这两列的数据结构是一样的，但是结构比较复杂，如下：
|-- list: array (nullable = true)
| |-- element: map (containsNull = true)
| | |-- key: string
| | |-- value: array (valueContainsNull = true)
| | | |-- element: struct (containsNull = true)
| | | | |-- Date: integer (nullable = true)
| | | | |-- Name: string (nullable = true)
|-- list2: array (nullable = true)
| |-- element: map (containsNull = true)
| | |-- key: string
| | |-- value: array (valueContainsNull = true)
| | | |-- element: struct (containsNull = true)
| | | | |-- Date: integer (nullable = true)
| | | | |-- Name: string (nullable = true)
也就是说Array里嵌着Map，Map里还嵌着一个Array，只能依次去比较，编写的UDF如下：
case class AppList(Date: Int, versionCode: Int, Name:String)
def isMapEqual(map1: Map[String, Array[AppList]], map2:Map[String, Array[AppList]]): Boolean = {
try{
if (map1.size != map2.size){
return false
} else{
for ( x <- map1.keys){
if (map1(x) != map2(x)){
return false
}
}
return true
}
} catch {
case e: Exception => false
}
}
def isListEqual(list1: Array[Map[String, Array[AppList]]], list2:Seq[Map[String, Seq[AppList]]]): Boolean = {
try {
if (list1.length != list2.length){
return false
} else if (list1.length == 0 || list2.length == 0){
return false
} else {
return isMapEqual(list1(0), list2(0))
}
} catch {
case e: Exception => false
}
}
val isColumnEqual = udf((list1: Array[Map[String, Array[AppList]]], list2:Array[Map[String, Array[AppList]]]) => {
isListEqual(list1, list2)
})
然后我就贴到spark-shell里去执行了下面语句：
val dat = df.withColumn("equal", isColumnEqual($"list1", $"list2"))
dat.show()
此时就出现了如下错误：
Caused by: org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (array<map<string,array<struct<Date:int,Name:string>>>>, array<map<string,array<struct<Date:int,Name:string>>>>) => boolean)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ClassCastException: scala.collection.mutable.WrappedArray$ofRef cannot be cast to [Lscala.collection.immutable.Map;
at $anonfun$1.apply(<console>:42)
... 16 more
解决办法
所谓的解决办法，自然是去谷歌了…
在这里看到，说把Array改成Seq就好了，囧，尝试了一下，果然就好了
原因
这里说：
So it looks like the ArrayType on Dataframe "idDF" is really a WrappedArray and not an Array - So the function call to "filterMapKeysWithSet" failed as it expected an Array but got a WrappedArray/ Seq instead (which doesn't implicitly convert to Array in Scala 2.8 and above).
意思是，此Array非Scala中的原生Array，而是封装了一下的Array（有错的一定指出来，我都没写过Scala，慌
