[SPARK-22267][SQL][TEST] Spark SQL incorrectly reads ORC files when column order is different

[dongjoon-hyun]

What changes were proposed in this pull request?

Until 2.2.1, with the default configuration, Apache Spark returns incorrect results when ORC file schema is different from metastore schema order. This is due to Hive 1.2.1 library and some issues on convertMetastoreOrc option.

scala> Seq(1 -> 2).toDF("c1", "c2").write.format("orc").mode("overwrite").save("/tmp/o")
scala> sql("CREATE EXTERNAL TABLE o(c2 INT, c1 INT) STORED AS orc LOCATION '/tmp/o'")
scala> spark.table("o").show    // This is wrong.
+---+---+
| c2| c1|
+---+---+
|  1|  2|
+---+---+
scala> spark.read.orc("/tmp/o").show  // This is correct.
+---+---+
| c1| c2|
+---+---+
|  1|  2|
+---+---+

After SPARK-22279, the default configuration doesn't have this bug. Although Hive 1.2.1 library code path still has the problem, we had better have a test coverage on what we have now in order to prevent future regression on it.

How was this patch tested?

Pass the Jenkins with a newly added test test.

[SparkQA]

Test build #84653 has finished for PR 19928 at commit ea75bce.

• This patch passes all tests.
• This patch merges cleanly.
• This patch adds no public classes.

[HyukjinKwon]

cc @gatorsmile and @cloud-fan

[dongjoon-hyun]

Thank you for review and approval, @HyukjinKwon !

[cloud-fan]

thanks, merging to master!

[dongjoon-hyun]

Thank you, @HyukjinKwon and @cloud-fan !