flink-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Shiti Saxena <ssaxena....@gmail.com>
Subject Re: Help with Flink experimental Table API
Date Thu, 11 Jun 2015 06:41:41 GMT
Hi Aljoscha,

Could you please point me to the JIRA tickets? If you could provide some
guidance on how to resolve these, I will work on them and raise a
pull-request.

Thanks,
Shiti

On Thu, Jun 11, 2015 at 11:31 AM, Aljoscha Krettek <aljoscha@apache.org>
wrote:

> 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
>>
>>
>>
>>

Mime
View raw message