[SPARK-19109] ORC metadata section can sometimes exceed protobuf message size limit - ASF JIRA

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Details

Type: Bug
Status: Resolved
Priority: Major
Resolution: Fixed
Affects Version/s: 1.6.3, 2.0.2, 2.1.0, 2.2.0
Fix Version/s: 2.3.0
Component/s: SQL
Labels:
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.