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gatorsmile 07f32c2283 [SPARK-18594][SQL] Name Validation of Databases/Tables 
### What changes were proposed in this pull request?
Currently, the name validation checks are limited to table creation. It is enfored by Analyzer rule: `PreWriteCheck`.

However, table renaming and database creation have the same issues. It makes more sense to do the checks in `SessionCatalog`. This PR is to add it into `SessionCatalog`.

### How was this patch tested?
Added test cases

Author: gatorsmile <gatorsmile@gmail.com>

Closes #16018 from gatorsmile/nameValidate.
2016-11-27 19:43:24 -08:00
..
catalyst [SPARK-18594][SQL] Name Validation of Databases/Tables 2016-11-27 19:43:24 -08:00
core [SPARK-18594][SQL] Name Validation of Databases/Tables 2016-11-27 19:43:24 -08:00
hive [SPARK-18594][SQL] Name Validation of Databases/Tables 2016-11-27 19:43:24 -08:00
hive-thriftserver [SPARK-14914][CORE] Fix Resource not closed after using, for unit tests and example 2016-11-10 10:54:36 +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.