Can we use 0(false) and 1(true)?
On Tue, Jun 16, 2015 at 1:32 PM, Aljoscha Krettek <aljos...@apache.org>
wrote:
> One more thing, it would be good if the TupleSerializer didn't write a
> boolean for every field. A single integer could be used where one bit
> specifies if a given field is null or not. (Maybe we should also add this
> to the RowSerializer in the future.)
>
> On Tue, 16 Jun 2015 at 07:30 Aljoscha Krettek <aljos...@apache.org> wrote:
>
>> I think you can work on it. By the way, there are actually two
>> serializers. For Scala, CaseClassSerializer is responsible for tuples as
>> well. In Java, TupleSerializer is responsible for, well, Tuples.
>>
>> On Tue, 16 Jun 2015 at 06:25 Shiti Saxena <ssaxena....@gmail.com> wrote:
>>
>>> Hi,
>>>
>>> Can I work on the issue with TupleSerializer or is someone working on it?
>>>
>>> On Mon, Jun 15, 2015 at 11:20 AM, Aljoscha Krettek <aljos...@apache.org>
>>> wrote:
>>>
>>>> Hi,
>>>> the reason why this doesn't work is that the TupleSerializer cannot
>>>> deal with null values:
>>>>
>>>> @Test
>>>> def testAggregationWithNull(): Unit = {
>>>>
>>>> val env = ExecutionEnvironment.getExecutionEnvironment
>>>> val table = env.fromElements[(Integer, String)](
>>>> (123, "a"), (234, "b"), (345, "c"), (null, "d")).toTable
>>>>
>>>> val total = table.select('_1.sum).collect().head.productElement(0)
>>>> assertEquals(total, 702)
>>>> }
>>>>
>>>> it would have to modified in a similar way to the PojoSerializer and
>>>> RowSerializer. You could either leave the tests as they are now in you
>>>> pull request or also modify the TupleSerializer. Both seem fine to me.
>>>>
>>>> Cheers,
>>>>
>>>> Aljoscha
>>>>
>>>>
>>>> On Sun, 14 Jun 2015 at 20:28 Shiti Saxena <ssaxena....@gmail.com> wrote:
>>>>
>>>> Hi,
>>>>>
>>>>> Re-writing the test in the following manner works. But I am not sure
>>>>> if this is the correct way.
>>>>>
>>>>> def testAggregationWithNull(): Unit = {
>>>>>
>>>>> val env = ExecutionEnvironment.getExecutionEnvironment
>>>>> val dataSet = env.fromElements[(Integer, String)]((123, "a"),
>>>>> (234, "b"), (345, "c"), (0, "d"))
>>>>>
>>>>> implicit val rowInfo: TypeInformation[Row] = new RowTypeInfo(
>>>>> Seq(BasicTypeInfo.INT_TYPE_INFO,
>>>>> BasicTypeInfo.STRING_TYPE_INFO), Seq("id", "name"))
>>>>>
>>>>> val rowDataSet = dataSet.map {
>>>>> entry =>
>>>>> val row = new Row(2)
>>>>> val amount = if(entry._1<100) null else entry._1
>>>>> row.setField(0, amount)
>>>>> row.setField(1, entry._2)
>>>>> row
>>>>> }
>>>>>
>>>>> val total =
>>>>> rowDataSet.toTable.select('id.sum).collect().head.productElement(0)
>>>>> assertEquals(total, 702)
>>>>> }
>>>>>
>>>>>
>>>>>
>>>>> On Sun, Jun 14, 2015 at 11:42 PM, Shiti Saxena <ssaxena....@gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> For
>>>>>>
>>>>>> val table = env.fromElements[(Integer, String)]((123, "a"), (234,
>>>>>> "b"), (345, "c"), (null, "d")).toTable
>>>>>>
>>>>>> I get the following error,
>>>>>>
>>>>>> Error translating node 'Data Source "at
>>>>>> org.apache.flink.api.scala.ExecutionEnvironment.fromElements(ExecutionEnvironment.scala:505)
>>>>>> (org.apache.flink.api.java.io.CollectionInputFormat)" : NONE [[
>>>>>> GlobalProperties [partitioning=RANDOM_PARTITIONED] ]] [[ LocalProperties
>>>>>> [ordering=null, grouped=null, unique=null] ]]': null
>>>>>> org.apache.flink.optimizer.CompilerException: Error translating node
>>>>>> 'Data Source "at
>>>>>> org.apache.flink.api.scala.ExecutionEnvironment.fromElements(ExecutionEnvironment.scala:505)
>>>>>> (org.apache.flink.api.java.io.CollectionInputFormat)" : NONE [[
>>>>>> GlobalProperties [partitioning=RANDOM_PARTITIONED] ]] [[ LocalProperties
>>>>>> [ordering=null, grouped=null, unique=null] ]]': null
>>>>>> at
>>>>>> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.preVisit(JobGraphGenerator.java:360)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.preVisit(JobGraphGenerator.java:103)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plan.SourcePlanNode.accept(SourcePlanNode.java:87)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plan.OptimizedPlan.accept(OptimizedPlan.java:127)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.compileJobGraph(JobGraphGenerator.java:170)
>>>>>> at
>>>>>> org.apache.flink.test.util.TestEnvironment.execute(TestEnvironment.java:52)
>>>>>> at
>>>>>> org.apache.flink.api.java.ExecutionEnvironment.execute(ExecutionEnvironment.java:789)
>>>>>> at
>>>>>> org.apache.flink.api.scala.ExecutionEnvironment.execute(ExecutionEnvironment.scala:576)
>>>>>> at org.apache.flink.api.scala.DataSet.collect(DataSet.scala:544)
>>>>>> 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 java.lang.reflect.Method.invoke(Method.java:606)
>>>>>> 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
>>>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>>>> at java.lang.reflect.Method.invoke(Method.java:606)
>>>>>> at
>>>>>> com.intellij.rt.execution.application.AppMain.main(AppMain.java:140)
>>>>>> 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.scala.typeutils.CaseClassSerializer.serialize(CaseClassSerializer.scala:89)
>>>>>> at
>>>>>> org.apache.flink.api.scala.typeutils.CaseClassSerializer.serialize(CaseClassSerializer.scala:29)
>>>>>> at org.apache.flink.api.java.io
>>>>>> .CollectionInputFormat.writeObject(CollectionInputFormat.java:88)
>>>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>>>> at
>>>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>>>>> at
>>>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>>>> at java.lang.reflect.Method.invoke(Method.java:606)
>>>>>> at
>>>>>> java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:988)
>>>>>> at
>>>>>> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1493)
>>>>>> at
>>>>>> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1429)
>>>>>> at
>>>>>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1175)
>>>>>> at
>>>>>> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1541)
>>>>>> at
>>>>>> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1506)
>>>>>> at
>>>>>> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1429)
>>>>>> at
>>>>>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1175)
>>>>>> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
>>>>>> at
>>>>>> org.apache.flink.util.InstantiationUtil.serializeObject(InstantiationUtil.java:314)
>>>>>> at
>>>>>> org.apache.flink.util.InstantiationUtil.writeObjectToConfig(InstantiationUtil.java:268)
>>>>>> at
>>>>>> org.apache.flink.runtime.operators.util.TaskConfig.setStubWrapper(TaskConfig.java:273)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.createDataSourceVertex(JobGraphGenerator.java:853)
>>>>>> at
>>>>>> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.preVisit(JobGraphGenerator.java:260)
>>>>>> ... 55 more
>>>>>>
>>>>>>
>>>>>> Does this mean that the collect method is being called before doing
>>>>>> the aggregation? Is this because base serializers do not handle null
>>>>>> values
>>>>>> like POJOSerializer? And is that why fromCollection does not support
>>>>>> collections with null values?
>>>>>>
>>>>>> Or I could write the test using a file load if thats alright.
>>>>>>
>>>>>>
>>>>>> On Sun, Jun 14, 2015 at 11:11 PM, Aljoscha Krettek <
>>>>>> aljos...@apache.org> wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>> sorry, my mail client sent before I was done.
>>>>>>>
>>>>>>> I think the problem is that the Scala compiler derives a wrong type
>>>>>>> for this statement:
>>>>>>> val table = env.fromElements((123, "a"), (234, "b"), (345, "c"),
>>>>>>> (null, "d")).toTable
>>>>>>>
>>>>>>> Because of the null value it derives (Any, String) as the type if
>>>>>>> you do it like this, I think it should work:
>>>>>>> val table = env.fromElements[(Integer, String)]((123, "a"), (234,
>>>>>>> "b"), (345, "c"), (null, "d")).toTable
>>>>>>>
>>>>>>> I used Integer instead of Int because Scala will complain that null
>>>>>>> is not a valid value for Int otherwise.
>>>>>>>
>>>>>>> Cheers,
>>>>>>> Aljoscha
>>>>>>>
>>>>>>>
>>>>>>> On Sun, 14 Jun 2015 at 19:34 Aljoscha Krettek <aljos...@apache.org>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Hi,
>>>>>>>> I think the problem is that the Scala compiler derives a wrong type
>>>>>>>> for this statement:
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> On Sun, 14 Jun 2015 at 18:28 Shiti Saxena <ssaxena....@gmail.com>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>> 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
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>
>>>>>>
>>>>>
>>>
