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Gengliang Wang a1213d5f96 [SPARK-28997][SQL] Add spark.sql.dialect 
### What changes were proposed in this pull request?

After https://github.com/apache/spark/pull/25158 and https://github.com/apache/spark/pull/25458, SQL features of PostgreSQL are introduced into Spark. AFAIK, both features are implementation-defined behaviors, which are not specified in ANSI SQL.
In such a case, this proposal is to add a configuration `spark.sql.dialect` for choosing a database dialect.
After this PR, Spark supports two database dialects, `Spark` and `PostgreSQL`. With `PostgreSQL` dialect, Spark will:
1. perform integral division with the / operator if both sides are integral types;
2. accept "true", "yes", "1", "false", "no", "0", and unique prefixes as input and trim input for the boolean data type.

### Why are the changes needed?

Unify the external database dialect with one configuration, instead of small flags.

### Does this PR introduce any user-facing change?

A new configuration `spark.sql.dialect` for choosing a database dialect.

### How was this patch tested?

Existing tests.

Closes #25697 from gengliangwang/dialect.

Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2019-09-26 21:00:27 +08:00
..
catalyst [SPARK-28997][SQL] Add spark.sql.dialect 2019-09-26 21:00:27 +08:00
core [SPARK-28997][SQL] Add spark.sql.dialect 2019-09-26 21:00:27 +08:00
hive [SPARK-28957][SQL] Copy any "spark.hive.foo=bar" spark properties into hadoop conf as "hive.foo=bar" 2019-09-25 15:54:44 +08:00
hive-thriftserver [SPARK-28997][SQL] Add spark.sql.dialect 2019-09-26 21:00:27 +08:00
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.