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Posted to dev@pig.apache.org by "Thejas M Nair (JIRA)" <ji...@apache.org> on 2010/07/16 01:56:51 UTC
[jira] Commented: (PIG-1442) java.lang.OutOfMemoryError: Java heap
space (Reopen of PIG-766)
[ https://issues.apache.org/jira/browse/PIG-1442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12888961#action_12888961 ]
Thejas M Nair commented on PIG-1442:
------------------------------------
I investigated the reason for OutOfMemory error in another query which also had a similar 'distinct + count() in a nested foreach statement'. The reason for failure there was the combiner was producing very large records with very large bag of distinct values, when the combiner (which does distinct) was run intermediate merge-sort results in reduce. And it hits runs out of memory because MapReduce framework merger loads key-value pair from all the merge streams. This is being fixed in HADOOP-5494 .
This issue with large records can happen if any of the groups that you are doing distinct on has very large number of values.
You can disable combiner using -Dpig.exec.nocombiner=true on the commandline. That is likely to get this query working. Please let us know if you are able to try it .
Fixing the missing detach in POCombiner and PODemux will certainly help in releasing the memory earlier. I will be submitting a patch for that.
> java.lang.OutOfMemoryError: Java heap space (Reopen of PIG-766)
> ---------------------------------------------------------------
>
> Key: PIG-1442
> URL: https://issues.apache.org/jira/browse/PIG-1442
> Project: Pig
> Issue Type: Bug
> Components: impl
> Affects Versions: 0.2.0, 0.7.0
> Environment: Apache-Hadoop 0.20.2 + Pig 0.7.0 and also for 0.8.0-dev (18/may)
> Hadoop-0.18.3 (cloudera RPMs) + PIG 0.2.0
> Reporter: Dirk Schmid
> Assignee: Thejas M Nair
> Fix For: 0.8.0
>
>
> As mentioned by Ashutosh this is a reopen of https://issues.apache.org/jira/browse/PIG-766 because there is still a problem which causes that PIG scales only by memory.
> For convenience here comes the last entry of the PIG-766-Jira-Ticket:
> {quote}1. Are you getting the exact same stack trace as mentioned in the jira?{quote} Yes the same and some similar traces:
> {noformat}
> java.lang.OutOfMemoryError: Java heap space
> at java.util.Arrays.copyOf(Arrays.java:2786)
> at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:94)
> at java.io.DataOutputStream.write(DataOutputStream.java:90)
> at java.io.FilterOutputStream.write(FilterOutputStream.java:80)
> at org.apache.pig.data.DataReaderWriter.writeDatum(DataReaderWriter.java:279)
> at org.apache.pig.data.DefaultTuple.write(DefaultTuple.java:264)
> at org.apache.pig.data.DefaultAbstractBag.write(DefaultAbstractBag.java:249)
> at org.apache.pig.data.DataReaderWriter.writeDatum(DataReaderWriter.java:214)
> at org.apache.pig.data.DefaultTuple.write(DefaultTuple.java:264)
> at org.apache.pig.data.DataReaderWriter.writeDatum(DataReaderWriter.java:209)
> at org.apache.pig.data.DefaultTuple.write(DefaultTuple.java:264)
> at org.apache.pig.impl.io.PigNullableWritable.write(PigNullableWritable.java:123)
> at org.apache.hadoop.io.serializer.WritableSerialization$WritableSerializer.serialize(WritableSerialization.java:90)
> at org.apache.hadoop.io.serializer.WritableSerialization$WritableSerializer.serialize(WritableSerialization.java:77)
> at org.apache.hadoop.mapred.IFile$Writer.append(IFile.java:179)
> at org.apache.hadoop.mapred.Task$CombineOutputCollector.collect(Task.java:880)
> at org.apache.hadoop.mapred.Task$NewCombinerRunner$OutputConverter.write(Task.java:1201)
> at org.apache.hadoop.mapreduce.TaskInputOutputContext.write(TaskInputOutputContext.java:80)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.processOnePackageOutput(PigCombiner.java:199)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.reduce(PigCombiner.java:161)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.reduce(PigCombiner.java:51)
> at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:176)
> at org.apache.hadoop.mapred.Task$NewCombinerRunner.combine(Task.java:1222)
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.doInMemMerge(ReduceTask.java:2563)
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.run(ReduceTask.java:2501)
> java.lang.OutOfMemoryError: Java heap space
> at org.apache.pig.data.DefaultTuple.(DefaultTuple.java:58)
> at org.apache.pig.data.DefaultTupleFactory.newTuple(DefaultTupleFactory.java:35)
> at org.apache.pig.data.DataReaderWriter.bytesToTuple(DataReaderWriter.java:61)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:142)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:136)
> at org.apache.pig.data.DefaultAbstractBag.readFields(DefaultAbstractBag.java:263)
> at org.apache.pig.data.DataReaderWriter.bytesToBag(DataReaderWriter.java:71)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:145)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:136)
> at org.apache.pig.data.DataReaderWriter.bytesToTuple(DataReaderWriter.java:63)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:142)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:136)
> at org.apache.pig.data.DefaultTuple.readFields(DefaultTuple.java:284)
> at org.apache.pig.impl.io.PigNullableWritable.readFields(PigNullableWritable.java:114)
> at org.apache.hadoop.io.serializer.WritableSerialization$WritableDeserializer.deserialize(WritableSerialization.java:67)
> at org.apache.hadoop.io.serializer.WritableSerialization$WritableDeserializer.deserialize(WritableSerialization.java:40)
> at org.apache.hadoop.mapreduce.ReduceContext.nextKeyValue(ReduceContext.java:116)
> at org.apache.hadoop.mapreduce.ReduceContext$ValueIterator.next(ReduceContext.java:163)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POCombinerPackage.getNext(POCombinerPackage.java:155)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POMultiQueryPackage.getNext(POMultiQueryPackage.java:242)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.processOnePackageOutput(PigCombiner.java:170)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.reduce(PigCombiner.java:161)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.reduce(PigCombiner.java:51)
> at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:176)
> at org.apache.hadoop.mapred.Task$NewCombinerRunner.combine(Task.java:1222)
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.doInMemMerge(ReduceTask.java:2563)
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.run(ReduceTask.java:2501)
> java.lang.OutOfMemoryError: Java heap space
> at java.util.ArrayList.(ArrayList.java:112)
> at org.apache.pig.data.DefaultTuple.(DefaultTuple.java:58)
> at org.apache.pig.data.DefaultTupleFactory.newTuple(DefaultTupleFactory.java:35)
> at org.apache.pig.data.DataReaderWriter.bytesToTuple(DataReaderWriter.java:61)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:142)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:136)
> at org.apache.pig.data.DefaultAbstractBag.readFields(DefaultAbstractBag.java:263)
> at org.apache.pig.data.DataReaderWriter.bytesToBag(DataReaderWriter.java:71)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:145)
> at org.apache.pig.data.DataReaderWriter.readDatum(DataReaderWriter.java:136)
> at org.apache.pig.data.DefaultTuple.readFields(DefaultTuple.java:284)
> at org.apache.pig.data.InternalCachedBag$CachedBagIterator.hasNext(InternalCachedBag.java:221)
> at org.apache.pig.builtin.Distinct.getDistinctFromNestedBags(Distinct.java:138)
> at org.apache.pig.builtin.Distinct.access$200(Distinct.java:40)
> at org.apache.pig.builtin.Distinct$Intermediate.exec(Distinct.java:103)
> at org.apache.pig.builtin.Distinct$Intermediate.exec(Distinct.java:96)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.getNext(POUserFunc.java:209)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.getNext(POUserFunc.java:250)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POForEach.processPlan(POForEach.java:341)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POForEach.getNext(POForEach.java:289)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.PhysicalOperator.processInput(PhysicalOperator.java:276)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POLocalRearrange.getNext(POLocalRearrange.java:259)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.PODemux.runPipeline(PODemux.java:217)
> at org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.PODemux.getNext(PODemux.java:207)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.processOnePackageOutput(PigCombiner.java:183)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.reduce(PigCombiner.java:161)
> at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine.reduce(PigCombiner.java:51)
> at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:176)
> at org.apache.hadoop.mapred.Task$NewCombinerRunner.combine(Task.java:1222)
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.doInMemMerge(ReduceTask.java:2563)
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.run(ReduceTask.java:2501)
> {noformat}
> {quote}
> 2. Which operations are you doing in your query - join, group-by, any other ?
> 3. What load/store func are you using to read and write data? PigStorage or your own ?
> 4. What is your data size and memory available to your tasks?
> 5. Do you have very large records in your dataset, like hundreds of MB for one record ?
> It would be great if you can paste here the script from which you get this exception.
> {quote}
> As we started to test the transformation (see below) the OutOfMemory-Error first occured at input-datasets of about 150MB.
> Increasing the Memory for the child-vms by setting {{mapred.child.java.opts}} to {{600m}} fixed it for a while.
> When using larger input-dataset the problem reappears.
> *Input-Data:*
> A CSV-File, ~14GB Dataset, ~100,000,000 Records per Dataset, ~145 Byte per Record
> *Example:*
> {noformat}
> USER_ID REQUEST_DATE SESSION COMPANY SERVICENAME SECTION_1 SECTION_2 SECTION_3 SECTION_4 SECTION_5 SECTION_6 SECTION SECTION_NEW
> ac14263e-22082-2263455080-9 2010-03-02 ac14263e-22082-2263455080-9-1273015305 ABC (NULL) main (NULL) (NULL) (NULL) (NULL) abc/main/mail /main/mail
> ...
> ...
> {noformat}
> *The Pig-Script*
> {code}
> A = LOAD 'full_load' USING PigStorage('\t');
> B = FOREACH A GENERATE $4 AS servicename, $3 AS company, $2 AS session, $0 as user_id
> , $5 AS section_1, $6 AS section_2, $7 AS section_3, $8 as section_4
> , $9 as section_5, $10 as section_6, $11 AS section;
>
> /* 1st aggregation */
> S0 = GROUP B BY (servicename, company);
> S0_A = FOREACH S0 {
> unique_clients = DISTINCT B.user_id;
> visits = DISTINCT B.session;
> GENERATE FLATTEN(group), COUNT(B) AS pi_count, COUNT(unique_clients) AS unique_clients_count, COUNT(visits) AS visit_count;
> }
> S0_B = FOREACH S0_A GENERATE servicename, company, '' as section_1, '' as section_2, '' as section_3, '' as section_4
> , '' as section_5, '' as section_6, '' as section, pi_count, unique_clients_count
> , visit_count, 0 as level;
> /* 2nd aggregation */
> S1 = GROUP B BY (servicename, company, section_1); S1_A = FOREACH S1 {
> unique_clients = DISTINCT B.user_id;
> visits = DISTINCT B.session;
> GENERATE FLATTEN(group), COUNT(B) AS pi_count, COUNT(unique_clients) AS unique_clients_count, COUNT(visits) AS visit_count;
> }
> S1_B = FOREACH S1_A GENERATE servicename, company, section_1, '' as section_2, '' as section_3, '' as section_4
> , '' as section_5, '' as section_6, '' as section, pi_count, unique_clients_count
> , visit_count, 1 as level;
> /* 3rd - 7th aggregation may follow here */
> /* build result*/
> X = UNION S0_B, S1_B;
> STORE X INTO 'result' USING PigStorage ('\t'); {code}
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