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From Patrick Duin <patd...@gmail.com>
Subject Re: ORC file split calculation problems
Date Fri, 26 Feb 2016 15:36:01 GMT
Hi Prasanth.

Thanks for the quick reply!

The logs don't show much more of the stacktrace I'm afraid:
java.lang.NullPointerException
        at
org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$SplitGenerator.run(OrcInputFormat.java:809)
        at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)


The stacktrace isn't really the issue though. The NullPointer is a symptom
caused by not being able to return any stripes, if you look at the line in
the code it is  because the 'stripes' field is null which should never
happen. This, we think, is caused by failing namenode network traffic. We
would have lots of IO warning in the logs saying block's cannot be found or
e.g.:
16/02/01 13:20:34 WARN hdfs.BlockReaderFactory: I/O error constructing
remote block reader.
java.io.IOException: java.lang.InterruptedException
        at org.apache.hadoop.ipc.Client.call(Client.java:1448)
        at org.apache.hadoop.ipc.Client.call(Client.java:1400)
        at
org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)
        at com.sun.proxy.$Proxy32.getServerDefaults(Unknown Source)
        at
org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getServerDefaults(ClientNamenodeProtocolTranslatorPB.java:268)
        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.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
        at
org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
        at com.sun.proxy.$Proxy33.getServerDefaults(Unknown Source)
        at
org.apache.hadoop.hdfs.DFSClient.getServerDefaults(DFSClient.java:1007)
        at
org.apache.hadoop.hdfs.DFSClient.shouldEncryptData(DFSClient.java:2062)
        at
org.apache.hadoop.hdfs.DFSClient.newDataEncryptionKey(DFSClient.java:2068)
        at
org.apache.hadoop.hdfs.protocol.datatransfer.sasl.SaslDataTransferClient.checkTrustAndSend(SaslDataTransferClient.java:208)
        at
org.apache.hadoop.hdfs.protocol.datatransfer.sasl.SaslDataTransferClient.peerSend(SaslDataTransferClient.java:159)
        at
org.apache.hadoop.hdfs.net.TcpPeerServer.peerFromSocketAndKey(TcpPeerServer.java:90)
        at
org.apache.hadoop.hdfs.DFSClient.newConnectedPeer(DFSClient.java:3123)
        at
org.apache.hadoop.hdfs.BlockReaderFactory.nextTcpPeer(BlockReaderFactory.java:755)
        at
org.apache.hadoop.hdfs.BlockReaderFactory.getRemoteBlockReaderFromTcp(BlockReaderFactory.java:670)
        at
org.apache.hadoop.hdfs.BlockReaderFactory.build(BlockReaderFactory.java:337)
        at
org.apache.hadoop.hdfs.DFSInputStream.blockSeekTo(DFSInputStream.java:576)
        at
org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy(DFSInputStream.java:800)
        at
org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:848)
        at java.io.DataInputStream.readFully(DataInputStream.java:195)
        at
org.apache.hadoop.hive.ql.io.orc.ReaderImpl.extractMetaInfoFromFooter(ReaderImpl.java:407)
        at
org.apache.hadoop.hive.ql.io.orc.ReaderImpl.<init>(ReaderImpl.java:311)
        at
org.apache.hadoop.hive.ql.io.orc.OrcFile.createReader(OrcFile.java:228)
        at
org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$SplitGenerator.populateAndCacheStripeDetails(OrcInputFormat.java:885)
        at
org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$SplitGenerator.run(OrcInputFormat.java:771)
        at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.InterruptedException
        at java.util.concurrent.FutureTask.awaitDone(FutureTask.java:400)
        at java.util.concurrent.FutureTask.get(FutureTask.java:187)
        at
org.apache.hadoop.ipc.Client$Connection.sendRpcRequest(Client.java:1047)
        at org.apache.hadoop.ipc.Client.call(Client.java:1442)
        ... 33 more

Our job doesn't always fail sometimes splits get calculated. We suspect
when the namenode is too busy our job maybe hits some time-outs and the
whole thing fails.

Our intuition has been the same as you suggest, bigger files is better. But
we see a degradation in performance as soon as our files get bigger than
the ORC block size. Keeping file size within ORC block size sounds silly
but when looking at the code (OrcInputFormat) we think  it cuts out a bunch
of code that is causing us problems. The code we are trying to hit is:
https://github.com/apache/hive/blob/release-0.14.0/ql/src/java/org/apache/hadoop/hive/ql/io/orc/OrcInputFormat.java#L656.
Avoiding the scheduling.

In our case we are not using any SARG but we do use column projection.

Any idea why if we query the data via Hive we don't have this issue?

Let me know if you need more information. Thanks for the insights, much
appreciated.

Kind regards,
 Patrick


2016-02-25 22:20 GMT+01:00 Prasanth Jayachandran <
pjayachandran@hortonworks.com>:

>
> > On Feb 25, 2016, at 3:15 PM, Prasanth Jayachandran <
> pjayachandran@hortonworks.com> wrote:
> >
> > Hi Patrick
> >
> > Can you paste entire stacktrace? Looks like NPE happened during split
> generation but stack trace is incomplete to know what caused it.
> >
> > In Hive 0.14.0, the stripe size is changed to 64MB. The default block
> size for ORC files is 256MB. 4 stripes can fit a block. ORC does padding to
> avoid stripes straddling HDFS blocks. During split calculation, ORC footer
> which contains stripe level column statistics is read to perform split
> pruning based on predicate condition specified via SARG(Search Argument).
> >
> > For example: Assume column ‘state’ is sorted and the predicate condition
> is ‘state’=“CA"
> > Stripe 1: min = AZ max = FL
> > Stripe 2: min = GA max = MN
> > Stripe 3: min = MS max = SC
> > Stripe 4: min = SD max = WY
> >
> > In this case, only stripe 1 satisfies the above predicate condition. So
> only 1 split with stripe 1 will be created.
> > So if there are huge number of small files, then footers from all files
> has to be read to do split pruning. If there are few number of large files
> then only few footers have to be read. Also the minimum splittable position
> is stripe boundary. So having fewer large files has the advantage of
> reading less data during split pruning.
> >
> > If you can send me the full stacktrace, I can tell what is causing the
> exception here. I will also let you know of any workaround/next hive
> version with the fix.
> >
> > In more recent hive versions, hive 1.2.0 onwards. OrcInputFormat is has
> strategies to decided when to read footers and when not to read footers
> automatically. You can configure the strategy that you want based on the
> workload. In case of many small files, footers will not be read and with
> large files footers will be read for split pruning.
>
> The default strategy does it automatically (choosing between when to read
> and when not to footers). It is configurable as well.
>
> >
> > Thanks
> > Prasanth
> >
> >> On Feb 25, 2016, at 7:08 AM, Patrick Duin <patduin@gmail.com> wrote:
> >>
> >> Hi,
> >>
> >> We've recently moved one of our datasets to ORC and we use Cascading
> and Hive to read this data. We've had problems reading the data via
> Cascading, because of the generation of splits.
> >> We read in a large number of files (thousands) and they are about 1GB
> each. We found that the split calculation took minutes on our cluster and
> often didn't succeed at all (when our namenode was busy).
> >> When digging through the code of the
> 'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.class' we figured out that
> if we make the files less then the ORC block size (256MB) the code would
> avoid lots of namenode calls. We applied this solution and made our files
> smaller and that solved the problem. Split calculation in our job went from
> 10+ mins to a couple of seconds and always succeeds.
> >> We feel it is counterintuitive as bigger files are usually better in
> HDFS. We've also seen that doing a hive query on the data does not present
> this problem. Internally Hive seem to take a completely different execution
> path and is not using the OrcInputFormat but uses
> 'org.apache.hadoop.hive.ql.io.CombineHiveInputFormat.class'.
> >>
> >> Can someone explain the reason for this difference or shed some light
> on the behaviour we are seeing? Any help will be greatly appreciated. We
> are using hive-0.14.0.
> >>
> >> Kind regards,
> >> Patrick
> >>
> >> Here is the stack-trace that we would see when our Cascading job failed
> to calculate the splits:
> >> Caused by: java.lang.RuntimeException: serious problem
> >>        at
> org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$Context.waitForTasks(OrcInputFormat.java:478)
> >>        at
> org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.generateSplitsInfo(OrcInputFormat.java:949)
> >>        at
> org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.getSplits(OrcInputFormat.java:974)
> >>        at
> com.hotels.corc.mapred.CorcInputFormat.getSplits(CorcInputFormat.java:201)
> >>        at
> cascading.tap.hadoop.io.MultiInputFormat.getSplits(MultiInputFormat.java:200)
> >>        at
> cascading.tap.hadoop.io.MultiInputFormat.getSplits(MultiInputFormat.java:142)
> >>        at
> org.apache.hadoop.mapreduce.JobSubmitter.writeOldSplits(JobSubmitter.java:624)
> >>        at
> org.apache.hadoop.mapreduce.JobSubmitter.writeSplits(JobSubmitter.java:616)
> >>        at
> org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:492)
> >>        at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1296)
> >>        at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1293)
> >>        at java.security.AccessController.doPrivileged(Native Method)
> >>        at javax.security.auth.Subject.doAs(Subject.java:415)
> >>        at
> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1628)
> >>        at org.apache.hadoop.mapreduce.Job.submit(Job.java:1293)
> >>        at org.apache.hadoop.mapred.JobClient$1.run(JobClient.java:585)
> >>        at org.apache.hadoop.mapred.JobClient$1.run(JobClient.java:580)
> >>        at java.security.AccessController.doPrivileged(Native Method)
> >>        at javax.security.auth.Subject.doAs(Subject.java:415)
> >>        at
> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1628)
> >>        at
> org.apache.hadoop.mapred.JobClient.submitJobInternal(JobClient.java:580)
> >>        at
> org.apache.hadoop.mapred.JobClient.submitJob(JobClient.java:571)
> >>        at
> cascading.flow.hadoop.planner.HadoopFlowStepJob.internalNonBlockingStart(HadoopFlowStepJob.java:106)
> >>        at
> cascading.flow.planner.FlowStepJob.blockOnJob(FlowStepJob.java:265)
> >>        at cascading.flow.planner.FlowStepJob.start(FlowStepJob.java:184)
> >>        at cascading.flow.planner.FlowStepJob.call(FlowStepJob.java:146)
> >>        at cascading.flow.planner.FlowStepJob.call(FlowStepJob.java:48)
> >>        ... 4 more
> >> Caused by: java.lang.NullPointerException
> >>        at
> org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$SplitGenerator.run(OrcInputFormat.java:809)
> >
>
>

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