[jira] [Created] (SPARK-21997) Spark shows different results on Hive char/varchar columns

["Dongjoon Hyun (JIRA)" <ji...@apache.org>]

Dongjoon Hyun created SPARK-21997:
-------------------------------------

             Summary: Spark shows different results on Hive char/varchar columns
                 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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