You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "sydt (JIRA)" <ji...@apache.org> on 2017/08/09 08:05:00 UTC
[jira] [Commented] (SPARK-19109) ORC metadata section can sometimes
exceed protobuf message size limit
[ https://issues.apache.org/jira/browse/SPARK-19109?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16119546#comment-16119546 ]
sydt commented on SPARK-19109:
------------------------------
I meet this problem and resolved .I re-complie source code of hive-exec-1.2.1-spark2.jar of spark-2.1.0.
First download sourcecode of hive-exec-1.2.1-spark2.jar and the website is:
https://github.com/JoshRosen
Second: download the patch and put into ReaderImpl
https://issues.apache.org/jira/secure/attachment/12750949/HIVE-11592.1.patch
Third：recompile and package the hive-exec-1.2.1-spark2.jar
Last replace origin jar in spark-2.1.0/jars
> ORC metadata section can sometimes exceed protobuf message size limit
> ---------------------------------------------------------------------
>
> Key: SPARK-19109
> URL: https://issues.apache.org/jira/browse/SPARK-19109
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.3, 2.0.2, 2.1.0, 2.2.0
> Reporter: Nic Eggert
>
> Basically, Spark inherits HIVE-11592 from its Hive dependency. From that issue:
> If there are too many small stripes and with many columns, the overhead for storing metadata (column stats) can exceed the default protobuf message size of 64MB. Reading such files will throw the following exception
> {code}
> Exception in thread "main" com.google.protobuf.InvalidProtocolBufferException: Protocol message was too large. May be malicious. Use CodedInputStream.setSizeLimit() to increase the size limit.
> at com.google.protobuf.InvalidProtocolBufferException.sizeLimitExceeded(InvalidProtocolBufferException.java:110)
> at com.google.protobuf.CodedInputStream.refillBuffer(CodedInputStream.java:755)
> at com.google.protobuf.CodedInputStream.readRawBytes(CodedInputStream.java:811)
> at com.google.protobuf.CodedInputStream.readBytes(CodedInputStream.java:329)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$StringStatistics.<init>(OrcProto.java:1331)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$StringStatistics.<init>(OrcProto.java:1281)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$StringStatistics$1.parsePartialFrom(OrcProto.java:1374)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$StringStatistics$1.parsePartialFrom(OrcProto.java:1369)
> at com.google.protobuf.CodedInputStream.readMessage(CodedInputStream.java:309)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$ColumnStatistics.<init>(OrcProto.java:4887)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$ColumnStatistics.<init>(OrcProto.java:4803)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$ColumnStatistics$1.parsePartialFrom(OrcProto.java:4990)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$ColumnStatistics$1.parsePartialFrom(OrcProto.java:4985)
> at com.google.protobuf.CodedInputStream.readMessage(CodedInputStream.java:309)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$StripeStatistics.<init>(OrcProto.java:12925)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$StripeStatistics.<init>(OrcProto.java:12872)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$StripeStatistics$1.parsePartialFrom(OrcProto.java:12961)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$StripeStatistics$1.parsePartialFrom(OrcProto.java:12956)
> at com.google.protobuf.CodedInputStream.readMessage(CodedInputStream.java:309)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$Metadata.<init>(OrcProto.java:13599)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$Metadata.<init>(OrcProto.java:13546)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$Metadata$1.parsePartialFrom(OrcProto.java:13635)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$Metadata$1.parsePartialFrom(OrcProto.java:13630)
> at com.google.protobuf.AbstractParser.parsePartialFrom(AbstractParser.java:200)
> at com.google.protobuf.AbstractParser.parseFrom(AbstractParser.java:217)
> at com.google.protobuf.AbstractParser.parseFrom(AbstractParser.java:223)
> at com.google.protobuf.AbstractParser.parseFrom(AbstractParser.java:49)
> at org.apache.hadoop.hive.ql.io.orc.OrcProto$Metadata.parseFrom(OrcProto.java:13746)
> at org.apache.hadoop.hive.ql.io.orc.ReaderImpl$MetaInfoObjExtractor.<init>(ReaderImpl.java:468)
> at org.apache.hadoop.hive.ql.io.orc.ReaderImpl.<init>(ReaderImpl.java:314)
> at org.apache.hadoop.hive.ql.io.orc.OrcFile.createReader(OrcFile.java:228)
> at org.apache.hadoop.hive.ql.io.orc.FileDump.main(FileDump.java:67)
> 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.util.RunJar.run(RunJar.java:221)
> at org.apache.hadoop.util.RunJar.main(RunJar.java:136)
> {code}
> This is fixed in Hive 1.3, so it should be fairly straightforward to pick up the patch.
> As a side note: Spark's management of its Hive fork/dependency seems incredibly arcane to me. Surely there's a better way than publishing to central from developers' personal repos.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org