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Date: Thu, 14 Sep 2017 16:28:00 +0000 (UTC)
From: "Dongjoon Hyun (JIRA)" <jira@apache.org>
To: issues@spark.apache.org
Message-ID: <JIRA.13102017.1505326490000.114050.1505406480379@Atlassian.JIRA>
In-Reply-To: <JIRA.13102017.1505326490000@Atlassian.JIRA>
References: <JIRA.13102017.1505326490000@Atlassian.JIRA> <JIRA.13102017.1505326490118@jira-lw-us.apache.org>
Subject: [jira] [Updated] (SPARK-21997) Spark shows different results on
 char/varchar columns on Parquet
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archived-at: Thu, 14 Sep 2017 16:28:05 -0000


     [ https://issues.apache.org/jira/browse/SPARK-21997?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Dongjoon Hyun updated SPARK-21997:
----------------------------------
    Summary: Spark shows different results on char/varchar columns on Parquet  (was: Spark shows different results on Hive char/varchar columns on Parquet)

> Spark shows different results on char/varchar columns on Parquet
> ----------------------------------------------------------------
>
>                 Key: SPARK-21997
>                 URL: https://issues.apache.org/jira/browse/SPARK-21997
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.2, 2.1.1, 2.2.0
>            Reporter: Dongjoon Hyun
>
> SPARK-19459 resolves CHAR/VARCHAR issues in general, but Spark shows different results according to the SQL configuration, *spark.sql.hive.convertMetastoreParquet*. We had better fix this. Actually, the default of `spark.sql.hive.convertMetastoreParquet` is true, so the result is wrong by default.
> For ORC, the default of `spark.sql.hive.convertMetastoreOrc` is false, so SPARK-19459 didn't resolve this together. For ORC, it will happen if we turn on it `true`.
> {code}
> scala> sql("CREATE TABLE t_char(a CHAR(10), b VARCHAR(10)) STORED AS parquet")
> scala> sql("INSERT INTO TABLE t_char SELECT 'a', 'b'")
> scala> sql("SELECT * FROM t_char").show
> +---+---+
> |  a|  b|
> +---+---+
> |  a|  b|
> +---+---+
> scala> sql("set spark.sql.hive.convertMetastoreParquet=false")
> scala> sql("SELECT * FROM t_char").show
> +----------+---+
> |         a|  b|
> +----------+---+
> |a         |  b|
> +----------+---+
> scala> spark.version
> res3: String = 2.2.0
> {code}


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