Uploaded image for project: 'Spark'
  1. Spark
  2. SPARK-19109

ORC metadata section can sometimes exceed protobuf message size limit

    XMLWordPrintableJSON

Details

    • Bug
    • Status: Resolved
    • Major
    • Resolution: Fixed
    • 1.6.3, 2.0.2, 2.1.0, 2.2.0
    • 2.3.0
    • SQL
    • None

    Description

      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

      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)
      

      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.

      Attachments

        1. InsertPic_.png
          21 kB
          sydt

        Issue Links

          Activity

            People

              Unassigned Unassigned
              nseggert Nic Eggert
              Votes:
              1 Vote for this issue
              Watchers:
              7 Start watching this issue

              Dates

                Created:
                Updated:
                Resolved: