Hi Aljoscha,
I created the issue FLINK-2210
<https://issues.apache.org/jira/browse/FLINK-2210> for aggregate on null. I
made changes to ExpressionAggregateFunction to handle ignore null values.
But I am unable to create a Table with null values in tests.
The code I used is,
def testAggregationWithNull(): Unit = {
val env = ExecutionEnvironment.getExecutionEnvironment
val table = env.fromElements((123, "a"), (234, "b"), (345, "c"), (null,
"d")).toTable
val total = table.select('_1.sum).collect().head.productElement(0)
assertEquals(total, 702)
}
and the error i get is,
org.apache.flink.api.table.ExpressionException: Invalid expression
"('_1).sum": Unsupported type GenericType<java.lang.Object> for aggregation
('_1).sum. Only numeric data types supported.
at
org.apache.flink.api.table.expressions.analysis.TypeCheck.apply(TypeCheck.scala:50)
at
org.apache.flink.api.table.expressions.analysis.TypeCheck.apply(TypeCheck.scala:31)
at
org.apache.flink.api.table.trees.Analyzer$$anonfun$analyze$1.apply(Analyzer.scala:34)
at
org.apache.flink.api.table.trees.Analyzer$$anonfun$analyze$1.apply(Analyzer.scala:31)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.flink.api.table.trees.Analyzer.analyze(Analyzer.scala:31)
at org.apache.flink.api.table.Table$$anonfun$1.apply(Table.scala:59)
at org.apache.flink.api.table.Table$$anonfun$1.apply(Table.scala:59)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:34)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.AbstractTraversable.map(Traversable.scala:105)
at org.apache.flink.api.table.Table.select(Table.scala:59)
at
org.apache.flink.api.scala.table.test.AggregationsITCase.testAggregationWithNull(AggregationsITCase.scala:135)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at
org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:47)
at
org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
at
org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:44)
at
org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
at
org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
at
org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
at org.junit.rules.ExternalResource$1.evaluate(ExternalResource.java:48)
at org.junit.rules.RunRules.evaluate(RunRules.java:20)
at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:271)
at
org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:70)
at
org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:50)
at org.junit.runners.ParentRunner$3.run(ParentRunner.java:238)
at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:63)
at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:236)
at org.junit.runners.ParentRunner.access$000(ParentRunner.java:53)
at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:229)
at org.junit.runners.ParentRunner.run(ParentRunner.java:309)
at org.junit.runners.Suite.runChild(Suite.java:127)
at org.junit.runners.Suite.runChild(Suite.java:26)
at org.junit.runners.ParentRunner$3.run(ParentRunner.java:238)
at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:63)
at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:236)
at org.junit.runners.ParentRunner.access$000(ParentRunner.java:53)
at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:229)
at
org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
at
org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
at org.junit.runners.ParentRunner.run(ParentRunner.java:309)
at org.junit.runner.JUnitCore.run(JUnitCore.java:160)
at
com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:78)
at
com.intellij.rt.execution.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:212)
at com.intellij.rt.execution.junit.JUnitStarter.main(JUnitStarter.java:68)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:140)
The ExecutionEnvironment.fromCollection method also throws an error when
the collection contains a null.
Could you please point out what I am doing wrong? How do we create a Table
with null values?
In our application, we load a file and transform each line into a Row
resulting in a DataSet[Row]. This DataSet[Row] is then converted into
Table. Should I use the same approach for the test case?
Thanks,
Shiti
On Sun, Jun 14, 2015 at 4:10 PM, Shiti Saxena <ssaxena....@gmail.com> wrote:
> I'll do the fix
>
> On Sun, Jun 14, 2015 at 12:42 AM, Aljoscha Krettek <aljos...@apache.org>
> wrote:
>
>> I merged your PR for the RowSerializer. Teaching the aggregators to deal
>> with null values should be a very simple fix in
>> ExpressionAggregateFunction.scala. There it is simply always aggregating
>> the values without checking whether they are null. If you want you can also
>> fix that or I can quickly fix it.
>>
>> On Thu, 11 Jun 2015 at 10:40 Aljoscha Krettek <aljos...@apache.org>
>> wrote:
>>
>>> Cool, good to hear.
>>>
>>> The PojoSerializer already handles null fields. The RowSerializer can be
>>> modified in pretty much the same way. So you should start by looking at the
>>> copy()/serialize()/deserialize() methods of PojoSerializer and then modify
>>> RowSerializer in a similar way.
>>>
>>> You can also send me a private mail if you want more in-depth
>>> explanations.
>>>
>>> On Thu, 11 Jun 2015 at 09:33 Till Rohrmann <trohrm...@apache.org> wrote:
>>>
>>>> Hi Shiti,
>>>>
>>>> here is the issue [1].
>>>>
>>>> Cheers,
>>>> Till
>>>>
>>>> [1] https://issues.apache.org/jira/browse/FLINK-2203
>>>>
>>>> On Thu, Jun 11, 2015 at 8:42 AM Shiti Saxena <ssaxena....@gmail.com>
>>>> wrote:
>>>>
>>>>> 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 <
>>>>> aljos...@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....@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
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>
>
