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From Aljoscha Krettek <aljos...@apache.org>
Subject Re: Help with Flink experimental Table API
Date Thu, 11 Jun 2015 06:01:30 GMT
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.ece@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
>
>
>
>

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