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[SPARK-19775][SQL] Remove an obsolete `partitionBy().insertInto()` test case
Dongjoon Hyun authored 
## What changes were proposed in this pull request?

This issue removes [a test case](https://github.com/apache/spark/blame/master/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala#L287-L298) which was introduced by [SPARK-14459](https://github.com/apache/spark/commit/652bbb1bf62722b08a062c7a2bf72019f85e179e) and was superseded by [SPARK-16033](https://github.com/apache/spark/blame/master/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala#L365-L371). Basically, we cannot use `partitionBy` and `insertInto` together.

```scala
  test("Reject partitioning that does not match table") {
    withSQLConf(("hive.exec.dynamic.partition.mode", "nonstrict")) {
      sql("CREATE TABLE partitioned (id bigint, data string) PARTITIONED BY (part string)")
      val data = (1 to 10).map(i => (i, s"data-$i", if ((i % 2) == 0) "even" else "odd"))
          .toDF("id", "data", "part")

      intercept[AnalysisException] {
        // cannot partition by 2 fields when there is only one in the table definition
        data.write.partitionBy("part", "data").insertInto("partitioned")
      }
    }
  }
```

## How was this patch tested?

This only removes a test case. Pass the existing Jenkins test.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #17106 from dongjoon-hyun/SPARK-19775.
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README.md
README.md

Spark SQL

This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.

Spark SQL is broken up into four subprojects:

  • Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
  • Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
  • Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
  • HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.