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Terry Kim f2ead4d0b5 [SPARK-28970][SQL] Implement USE CATALOG/NAMESPACE for Data Source V2 
### What changes were proposed in this pull request?
This PR exposes USE CATALOG/USE SQL commands as described in this [SPIP](https://docs.google.com/document/d/1jEcvomPiTc5GtB9F7d2RTVVpMY64Qy7INCA_rFEd9HQ/edit#)

It also exposes `currentCatalog` in `CatalogManager`.

Finally, it changes `SHOW NAMESPACES` and `SHOW TABLES` to use the current catalog if no catalog is specified (instead of default catalog).

### Why are the changes needed?
There is currently no mechanism to change current catalog/namespace thru SQL commands.

### Does this PR introduce any user-facing change?
Yes, you can perform the following:
```scala
// Sets the current catalog to 'testcat'
spark.sql("USE CATALOG testcat")

// Sets the current catalog to 'testcat' and current namespace to 'ns1.ns2'.
spark.sql("USE ns1.ns2 IN testcat")

// Now, the following will use 'testcat' as the current catalog and 'ns1.ns2' as the current namespace.
spark.sql("SHOW NAMESPACES")
```

### How was this patch tested?
Added new unit tests.

Closes #25771 from imback82/use_namespace.

Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2019-10-02 21:55:21 +08:00
..
catalyst [SPARK-28970][SQL] Implement USE CATALOG/NAMESPACE for Data Source V2 2019-10-02 21:55:21 +08:00
core [SPARK-28970][SQL] Implement USE CATALOG/NAMESPACE for Data Source V2 2019-10-02 21:55:21 +08:00
hive [SPARK-28970][SQL] Implement USE CATALOG/NAMESPACE for Data Source V2 2019-10-02 21:55:21 +08:00
hive-thriftserver [SPARK-29022][SQL] Fix SparkSQLCLI can not add jars by AddJarCommand 2019-10-01 10:09:29 -05:00
create-docs.sh
gen-sql-markdown.py [SPARK-27328][SQL] Add 'deprecated' in ExpressionDescription for extended usage and SQL doc 2019-04-09 13:49:42 +08:00
mkdocs.yml
README.md [SPARK-28980][CORE][SQL][STREAMING][MLLIB] Remove most items deprecated in Spark 2.2.0 or earlier, for Spark 3 2019-09-09 10:19:40 -05:00

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 extensions that allow users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow 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.

Running ./sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.