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Dongjoon Hyun fc7554599a [SPARK-19970][SQL] Table owner should be USER instead of PRINCIPAL in kerberized clusters 
## What changes were proposed in this pull request?

In the kerberized hadoop cluster, when Spark creates tables, the owner of tables are filled with PRINCIPAL strings instead of USER names. This is inconsistent with Hive and causes problems when using [ROLE](https://cwiki.apache.org/confluence/display/Hive/SQL+Standard+Based+Hive+Authorization) in Hive. We had better to fix this.

**BEFORE**
```scala
scala> sql("create table t(a int)").show
scala> sql("desc formatted t").show(false)
...
|Owner:                      |sparkEXAMPLE.COM                                         |       |
```

**AFTER**
```scala
scala> sql("create table t(a int)").show
scala> sql("desc formatted t").show(false)
...
|Owner:                      |spark                                         |       |
```

## How was this patch tested?

Manually do `create table` and `desc formatted` because this happens in Kerberized clusters.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #17311 from dongjoon-hyun/SPARK-19970.
2017-03-20 10:07:31 -07:00
..
catalyst [SPARK-17791][SQL] Join reordering using star schema detection 2017-03-20 16:04:58 +08:00
core [SPARK-19990][SQL][TEST-MAVEN] create a temp file for file in test.jar's resource when run mvn test accross different modules 2017-03-20 21:36:00 +08:00
hive [SPARK-19970][SQL] Table owner should be USER instead of PRINCIPAL in kerberized clusters 2017-03-20 10:07:31 -07:00
hive-thriftserver [SPARK-19673][SQL] "ThriftServer default app name is changed wrong" 2017-02-25 21:47:02 +00:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

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.