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https://issues.apache.org/jira/browse/SPARK-21997?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dongjoon Hyun updated SPARK-21997:
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Summary: Spark shows different results on Hive char/varchar columns on
Parquet/ORC (was: Spark shows different results on Hive char/varchar columns
on Parquet)
> Spark shows different results on Hive char/varchar columns on Parquet/ORC
> -------------------------------------------------------------------------
>
> Key: SPARK-21997
> URL: https://issues.apache.org/jira/browse/SPARK-21997
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 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.convertMetastoreParquet` is false, so SPARK-19459 didn't
> resolve this together.
> {code}
> hive> CREATE TABLE t_char(a CHAR(10), b VARCHAR(10)) STORED AS parquet;
> hive> INSERT INTO TABLE t_char SELECT 'a', 'b' FROM (SELECT 1) t;
> 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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