Luis Felipe Sant Ana created SPARK-19711: --------------------------------------------
Summary: Bug in gapply function Key: SPARK-19711 URL: https://issues.apache.org/jira/browse/SPARK-19711 Project: Spark Issue Type: Bug Components: SparkR Affects Versions: 2.1.0 Environment: Using Databricks plataform. Reporter: Luis Felipe Sant Ana I have a dataframe in SparkR like CNPJ PID DATA N 1 10140281000131 10000000000021 2015-04-23 1 2 10140281000131 10000000000021 2015-04-27 1 3 10140281000131 10000000000021 2015-04-02 1 4 10140281000131 10000000000021 2015-11-10 1 5 10140281000131 10000000000021 2016-11-14 1 6 10140281000131 10000000000021 2015-04-03 1 And, I want to group by columns CNPJ and PID using gapply() function, filling in the column DATA with date The code: schema <- structType(structField("CNPJ", "string"), structField("PID", "string"), structField("DATA", "date"), structField("N", "double")) result <- gapply( ds_filtered, c("CNPJ", "PID"), function(key, x) { dts <- data.frame(key, DATA = seq(min(as.Date(x$DATA)), as.Date(e_date), "days")) colnames(dts)[c(1, 2)] <- c("CNPJ", "PID") y <- data.frame(key, DATA = as.Date(x$DATA), N = x$N) colnames(y)[c(1, 2)] <- c("CNPJ", "PID") y <- dplyr::left_join(dts, y, by = c("CNPJ", "PID", "DATA")) y[is.na(y$N), 4] <- 0 data.frame(CNPJ = as.character(y$CNPJ), PID = as.character(y$PID), DATA = y$DATA, N = y$N) }, schema) Error: Error in handleErrors(returnStatus, conn) : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 92.0 failed 4 times, most recent failure: Lost task 0.3 in stage 92.0 (TID 7032, 10.93.243.111, executor 0): org.apache.spark.SparkException: R computation failed with Error in writeType(con, serdeType) : Unsupported type for serialization factor Calls: outputResult ... serializeRow -> writeList -> writeObject -> writeType Execution halted at org.apache.spark.api.r.RRunner.compute(RRunner.scala:108) at org.apache.spark.sql.execution.FlatMapGroupsInRExec$$anonfun$12.apply(objects.scala:404) at org.apache.spark.sql.execution.FlatMapGroupsInRExec$$anonfun$12.apply(objects.scala:386) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:333) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:2784) at org.apache.spark.sql.Dataset$$anonfun$collect$1.apply(Dataset.scala:2354) at org.apache.spark.sql.Dataset$$anonfun$collect$1.apply(Dataset.scala:2354) at org.apache.spark.sql.Dataset$$anonfun$59.apply(Dataset.scala:2768) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2767) at org.apache.spark.sql.Dataset.collect(Dataset.scala:2354) at org.apache.spark.sql.api.r.SQLUtils$.dfToCols(SQLUtils.scala:208) at org.apache.spark.sql.api.r.SQLUtils.dfToCols(SQLUtils.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at org.apache.spark.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:167) at org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:108) at org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:40) at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) at io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:293) at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:267) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) at io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1294) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:911) at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131) at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:652) at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:575) at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:489) at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:451) at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140) at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144) at java.lang.Thread.run(Thread.java:745) Caused by: org.apache.spark.SparkException: R computation failed with Error in writeType(con, serdeType) : Unsupported type for serialization factor Calls: outputResult ... serializeRow -> writeList -> writeObject -> writeType Execution halted at org.apache.spark.api.r.RRunner.compute(RRunner.scala:108) at org.apache.spark.sql.execution.FlatMapGroupsInRExec$$anonfun$12.apply(objects.scala:404) at org.apache.spark.sql.execution.FlatMapGroupsInRExec$$anonfun$12.apply(objects.scala:386) at org.apache.spark.rdd.RDD$$an With gapplyCollect() function this work. 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