Hello, I'm having an exception when trying to apply a new Scheme to RDD I'm reading an JSON with Databricks spark-csv v1.3.0
after applying some transformations I have RDD with Strings type columns Then I'm trying to apply Scheme where one of the field is Integer then this exception is riced 16/01/28 17:38:14 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 4, localhost): java.lang.ClassCastException: java.lang.String cannot be cast to java.lang.Integer at scala.runtime.BoxesRunTime.unboxToInt(BoxesRunTime.java:101) at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow$class.getInt(rows.scala:41) at org.apache.spark.sql.catalyst.expressions.GenericInternalRow.getInt(rows.scala:221) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source) at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:51) at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:49) at scala.collection.Iterator$$anon$11.next(Iterator.scala:370) at scala.collection.Iterator$$anon$11.next(Iterator.scala:370) at scala.collection.Iterator$$anon$11.next(Iterator.scala:370) at scala.collection.Iterator$$anon$10.next(Iterator.scala:354) at scala.collection.Iterator$class.foreach(Iterator.scala:742) at scala.collection.AbstractIterator.foreach(Iterator.scala:1194) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:308) at scala.collection.AbstractIterator.to(Iterator.scala:1194) at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:300) at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1194) at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:287) at scala.collection.AbstractIterator.toArray(Iterator.scala:1194) at org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212) at org.apache.spark.sql.execution.SparkPlan$$anonfun$5.apply(SparkPlan.scala:212) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) at org.apache.spark.scheduler.Task.run(Task.scala:89) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source) at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source) at java.lang.Thread.run(Unknown Source) The code I'm running is like var res=(df.explode("rows","r") { l: WrappedArray[ArrayBuffer[String]] => l.toList}).select("r") .map { m => m.getList[Row](0) } var u = res.map { m => Row.fromSeq(m.toSeq) } var df1 = df.sqlContext.createDataFrame(u, getScheme(df) ) //if df1.show -> the exception is riced getScheme return the scheme, the las column is IntegerType, if I change it to StringType and then apply the cast like this, its works df1.select(df1("ga:pageviews").cast(IntegerType)).show The order of the fields at the Structure seems to be ok. I read that in early versions of spark-csv was a similar issue. Any Ideas? Regards!!! Ing. Ivaldi Andres