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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/05/10 11:53:00 UTC

[jira] [Assigned] (SPARK-31672) Reading wrong timestamps from dictionary encoded columns in Parquet files

     [ https://issues.apache.org/jira/browse/SPARK-31672?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-31672:
------------------------------------

    Assignee: Apache Spark  (was: Maxim Gekk)

> Reading wrong timestamps from dictionary encoded columns in Parquet files
> -------------------------------------------------------------------------
>
>                 Key: SPARK-31672
>                 URL: https://issues.apache.org/jira/browse/SPARK-31672
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>    Affects Versions: 3.0.0, 3.1.0
>            Reporter: Maxim Gekk
>            Assignee: Apache Spark
>            Priority: Major
>             Fix For: 3.0.0
>
>
> Write dates with dictionary encoding enabled to parquet files:
> {code:scala}
> Welcome to
>       ____              __
>      / __/__  ___ _____/ /__
>     _\ \/ _ \/ _ `/ __/  '_/
>    /___/ .__/\_,_/_/ /_/\_\   version 3.1.0-SNAPSHOT
>       /_/
> Using Scala version 2.12.10 (OpenJDK 64-Bit Server VM, Java 1.8.0_242)
> Type in expressions to have them evaluated.
> Type :help for more information.
> scala> spark.conf.set("spark.sql.legacy.parquet.rebaseDateTimeInWrite.enabled", true)
> scala> spark.conf.set("spark.sql.parquet.outputTimestampType", "TIMESTAMP_MICROS")
> scala> :paste
> // Entering paste mode (ctrl-D to finish)
>                 Seq.tabulate(8)(_ => "1001-01-01 01:02:03.123").toDF("tsS")
>                   .select($"tsS".cast("timestamp").as("ts"))
>                   .repartition(1)
>                   .write
>                   .option("parquet.enable.dictionary", true)
>                   .mode("overwrite")
>                   .parquet("/Users/maximgekk/tmp/parquet-ts-dict")
> // Exiting paste mode, now interpreting.
> {code}
> Read them back:
> {code:scala}
> scala> spark.read.parquet("/Users/maximgekk/tmp/parquet-ts-dict").show(false)
> +-----------------------+
> |ts                     |
> +-----------------------+
> |1001-01-07 00:32:20.123|
> |1001-01-07 00:32:20.123|
> |1001-01-07 00:32:20.123|
> |1001-01-07 00:32:20.123|
> |1001-01-07 00:32:20.123|
> |1001-01-07 00:32:20.123|
> |1001-01-07 00:32:20.123|
> |1001-01-07 00:32:20.123|
> +-----------------------+
> {code}
> *Expected values must be 1001-01-01 01:02:03.123.*
> I checked that the timestamp column is encoded by dictionary via:
> {code}
> ➜  parquet-ts-dict java -jar ~/Downloads/parquet-tools-1.12.0.jar dump ./part-00000-2c6c89b1-d165-4528-9a9d-796baa07908e-c000.snappy.parquet
> row group 0
> --------------------------------------------------------------------------------
> ts:  INT64 SNAPPY DO:0 FPO:4 SZ:94/90/0.96 VC:8 ENC:BIT_PACKED,RLE,PLA [more]...
>     ts TV=8 RL=0 DL=1 DS: 1 DE:PLAIN_DICTIONARY
>     ----------------------------------------------------------------------------
>     page 0:                DLE:RLE RLE:BIT_PACKED VLE:PLAIN_DICTIONARY [more]... VC:8
> INT64 ts
> --------------------------------------------------------------------------------
> *** row group 1 of 1, values 1 to 8 ***
> value 1: R:0 D:1 V:1001-01-06T22:02:03.123000+0000
> value 2: R:0 D:1 V:1001-01-06T22:02:03.123000+0000
> value 3: R:0 D:1 V:1001-01-06T22:02:03.123000+0000
> value 4: R:0 D:1 V:1001-01-06T22:02:03.123000+0000
> value 5: R:0 D:1 V:1001-01-06T22:02:03.123000+0000
> value 6: R:0 D:1 V:1001-01-06T22:02:03.123000+0000
> value 7: R:0 D:1 V:1001-01-06T22:02:03.123000+0000
> value 8: R:0 D:1 V:1001-01-06T22:02:03.123000+0000
> {code}



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