InternalRow is an internal/developer API that might change overtime. Right now, the way to convert it to Row is to use `RowEncoder`, but you need to know the data schema: val encoder = RowEncoder(schema) val row = encoder.fromRow(internalRow)
On Fri, Nov 27, 2020 at 6:16 AM Jason Jun <jaes...@gmail.com> wrote: > Hi dev, > > i'm working on generating custom pipeline on the fly, which means I > generate SparkPlan along with each node in my pipeline. > > So, my pipeline end up with PipeLineRelation extending BaseRelation like: > > case class PipeLineRelation(schema: StructType, pipeLinePlan: > LogicalPlan)(@transient override val sqlContext: SQLContext) extends > BaseRelation with PrunedFilteredScan { > override def needConversion: Boolean = true > override def unhandledFilters(filters: Array[Filter]): Array[Filter] = > filters > > override def buildScan(requiredColumns: Array[String], filters: > Array[Filter]): RDD[Row] = { > ... > val sparkPlan = > sqlContext.sparkSession.sessionState.planner.plan(pipeLinePlan).next() > *sparkPlan.execute().mapPartitions* { itr => > itr.map { internalRow => > val values = prunedColumnWithIndex.map { case (index, columnType) > => > internalRow.get(index, columnType) > } > * Row.fromSeq(values) // Line 46* > } > } > } > } > > I'm getting InternalRow by executing subsequent Spark Plan, and converting > it into Row using Row.fromSeq(). i saw values at Line 46 are what i exactly > want : > ------ > values = {Object[5]@14277} > 0 = {UTF8String@14280} "Thin" > 1 = {UTF8String@14281} "Cell phone" > 2 = {Integer@14282} 6000 > 3 = {Integer@14283} 2 > 4 = {Integer@14284} 12000 > > but execution of Line 46 ended up with this error : > ------ > Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most > recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost, executor > driver): java.lang.IllegalArgumentException: The value (2) of the type > (java.lang.Integer) cannot be converted to the string type > at > org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:290) > at > org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:285) > at > org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:103) > at > org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToCatalystConverter$2.apply(CatalystTypeConverters.scala:396) > at > org.apache.spark.sql.execution.RDDConversions$$anonfun$rowToRowRdd$1$$anonfun$apply$3.apply(ExistingRDD.scala:60) > at > org.apache.spark.sql.execution.RDDConversions$$anonfun$rowToRowRdd$1$$anonfun$apply$3.apply(ExistingRDD.scala:57) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:370) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:619) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) > at org.apache.spark.scheduler.Task.run(Task.scala:121) > at > org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:748) > ---- > > Is it existing bug? otherwise how do I convert InternalRow to Row? > > Thanks in advance. > Jason >