[jira] [Created] (SPARK-19109) ORC metadata section can sometimes exceed protobuf message size limit

["Nic Eggert (JIRA)" <ji...@apache.org>]

Nic Eggert created SPARK-19109:
----------------------------------

             Summary: 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: 2.1.0, 2.0.2, 1.6.3, 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.



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