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https://issues.apache.org/jira/browse/HIVE-26612?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17615977#comment-17615977
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Steve Carlin commented on HIVE-26612:
-------------------------------------
Whoops, sorry, I left out how to reproduce it.
Once the parquet file is created via the above technique through Spark, we do
the following on the Hive side
CREATE EXTERNAL TABLE ts_as_bigint_pq (dummy int, ts2 BIGINT)
STORED AS PARQUET
LOCATION '${system:test.tmp.dir}/parquet_format_ts_as_bigint';
This create statement should point to the location of the parquet file as
created in the description by Spark. The parquet file is for a timestamp
datatype but the native type is a legacy INT64 format.
Then a simple
SELECT * from ts_as_bigint_pq
will cause the exception int he description.
> Hive cannot read parquet files with int64 (TIMESTAMP_MILLIS)
> ------------------------------------------------------------
>
> Key: HIVE-26612
> URL: https://issues.apache.org/jira/browse/HIVE-26612
> Project: Hive
> Issue Type: Bug
> Components: Database/Schema
> Reporter: Steve Carlin
> Priority: Major
> Labels: pull-request-available
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
> If a parquet file has a Type of "int64 eventtime (TIMESTAMP(MILLIS,true))",
> the following error is produced:
> exec.Task: Failed with exception
> java.io.IOException:org.apache.parquet.io.ParquetDecodingException: Can not
> read value at 1 in block 0 in file
> file:/home/steve/upstream/hive/itests/qtest/target/tmp/parquet_format_ts_as_bigint/part-00000/timestamp_as_bigint.parquet
> java.io.IOException: org.apache.parquet.io.ParquetDecodingException: Can not
> read value at 1 in block 0 in file
> file:/home/steve/upstream/hive/itests/qtest/target/tmp/parquet_format_ts_as_bigint/part-00000/timestamp_as_bigint.parquet
> at
> org.apache.hadoop.hive.ql.exec.FetchOperator.getNextRow(FetchOperator.java:624)
> at
> org.apache.hadoop.hive.ql.exec.FetchOperator.pushRow(FetchOperator.java:531)
> at
> org.apache.hadoop.hive.ql.exec.FetchTask.executeInner(FetchTask.java:197)
> at org.apache.hadoop.hive.ql.exec.FetchTask.execute(FetchTask.java:98)
> The parquet file can be created with the following steps (through spark):
> spark.conf.set("spark.sql.parquet.outputTimestampType", "TIMESTAMP_MILLIS")
> spark.conf.set("spark.sql.legacy.parquet.int96RebaseModeInWrite", "LEGACY")
> spark.conf.set("spark.sql.legacy.parquet.datetimeRebaseModeInWrite", "LEGACY")
> spark.conf.set("spark.sql.legacy.parquet.int96RebaseModeInRead", "LEGACY")
> spark.conf.set("spark.sql.legacy.parquet.datetimeRebaseModeInRead", "LEGACY")
> [1]
> val df = Seq(
> (1, Timestamp.valueOf("2014-01-01 23:00:01")),
> (1, Timestamp.valueOf("2014-11-30 12:40:32")),
> (2, Timestamp.valueOf("2016-12-29 09:54:00")),
> (2, Timestamp.valueOf("2016-05-09 10:12:43"))
> ).toDF("typeid","eventtime")
> [2]
> [root@c4839-node3 test_parquet2]# parquet-tools schema
> part-00001-6c90b794-90b9-4cc0-afc5-2e49a4e96bad-c000.snappy.parquet
> message spark_schema {
> required int32 typeid;
> optional int64 eventtime (TIMESTAMP(MILLIS,true));
> }
> [3]
> [root@c4839-node3 test_parquet1]# parquet-tools schema
> part-00001-cb1aeebb-ec87-4273-82ec-911c4fb605b6-c000.snappy.parquet
> message spark_schema {
> required int32 typeid;
> optional int96 eventtime;
> }
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