Hi, yes, I think the problem is that the RowSerializer does not support null-values. I think we can add support for this, I will open a Jira issue.
Another problem I then see is that the aggregations can not properly deal with null-values. This would need separate support. Regards, Aljoscha On Thu, 11 Jun 2015 at 06:41 Shiti Saxena <ssaxena....@gmail.com> wrote: > Hi, > > In our project, we are using the Flink Table API and are facing the > following issues, > > We load data from a CSV file and create a DataSet[Row]. The CSV file can > also have invalid entries in some of the fields which we replace with null > when building the DataSet[Row]. > > This DataSet[Row] is later on transformed to Table whenever required and > specific operation such as select or aggregate, etc are performed. > > When a null value is encountered, we get a null pointer exception and the > whole job fails. (We can see this by calling collect on the resulting > DataSet). > > The error message is similar to, > > Job execution failed. > org.apache.flink.runtime.client.JobExecutionException: Job execution > failed. > at > org.apache.flink.runtime.jobmanager.JobManager$$anonfun$receiveWithLogMessages$1.applyOrElse(JobManager.scala:315) > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33) > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33) > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25) > at > org.apache.flink.runtime.ActorLogMessages$$anon$1.apply(ActorLogMessages.scala:43) > at > org.apache.flink.runtime.ActorLogMessages$$anon$1.apply(ActorLogMessages.scala:29) > at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118) > at > org.apache.flink.runtime.ActorLogMessages$$anon$1.applyOrElse(ActorLogMessages.scala:29) > at akka.actor.Actor$class.aroundReceive(Actor.scala:465) > at > org.apache.flink.runtime.jobmanager.JobManager.aroundReceive(JobManager.scala:94) > at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516) > at akka.actor.ActorCell.invoke(ActorCell.scala:487) > at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:254) > at akka.dispatch.Mailbox.run(Mailbox.scala:221) > at akka.dispatch.Mailbox.exec(Mailbox.scala:231) > at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) > at > scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) > at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) > at > scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) > Caused by: java.lang.NullPointerException > at > org.apache.flink.api.common.typeutils.base.IntSerializer.serialize(IntSerializer.java:63) > at > org.apache.flink.api.common.typeutils.base.IntSerializer.serialize(IntSerializer.java:27) > at > org.apache.flink.api.table.typeinfo.RowSerializer.serialize(RowSerializer.scala:80) > at > org.apache.flink.api.table.typeinfo.RowSerializer.serialize(RowSerializer.scala:28) > at > org.apache.flink.runtime.plugable.SerializationDelegate.write(SerializationDelegate.java:51) > at > org.apache.flink.runtime.io.network.api.serialization.SpanningRecordSerializer.addRecord(SpanningRecordSerializer.java:76) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:83) > at > org.apache.flink.runtime.operators.shipping.OutputCollector.collect(OutputCollector.java:65) > at > org.apache.flink.runtime.operators.chaining.ChainedMapDriver.collect(ChainedMapDriver.java:78) > at > org.apache.flink.runtime.operators.chaining.ChainedMapDriver.collect(ChainedMapDriver.java:78) > at > org.apache.flink.runtime.operators.DataSourceTask.invoke(DataSourceTask.java:177) > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:559) > at java.lang.Thread.run(Thread.java:724) > > Could this be because the RowSerializer does not support null values? > (Similar to Flink-629 <https://issues.apache.org/jira/browse/FLINK-629> ) > > Currently, to overcome this issue, we are ignoring all the rows which may > have null values. For example, we have a method cleanData defined as, > > def cleanData(table:Table, relevantColumns:Seq[String]):Table = { > val whereClause: String = relevantColumns.map{ > cName=> > s"$cName.isNotNull" > }.mkString(" && ") > > val result :Table = > table.select(relevantColumns.mkString(",")).where(whereClause) > result > } > > Before operating on any Table, we use this method and then continue with > task. > > Is this the right way to handle this? If not please let me know how to go > about it. > > > Thanks, > Shiti > > > >
