48e333af54
### What changes were proposed in this pull request? 1. Promote more string literal in subtractions. In the ANSI type coercion rule, we already promoted ``` string - timestamp => cast(string as timestamp) - timestamp ``` This PR is to promote the following string literals: ``` string - date => cast(string as date) - date date - string => date - cast(date as string) timestamp - string => timestamp ``` It is very straightforward to cast the string literal as the data type of the other side in the subtraction. 2. Merge the string promotion logic from the rule `StringLiteralCoercion`: ``` date_sub(date, string) => date_sub(date, cast(string as int)) date_add(date, string) => date_add(date, cast(string as int)) ``` ### Why are the changes needed? 1. Promote the string literal in the subtraction as the data type of the other side. This is straightforward and consistent with PostgreSQL 2. Certerize all the string literal promotion in the ANSI type coercion rule ### Does this PR introduce _any_ user-facing change? No, the new ANSI type coercion rules are not released yet. ### How was this patch tested? Existing UT Closes #33724 from gengliangwang/datetimeTypeCoercion. Authored-by: Gengliang Wang <gengliang@apache.org> Signed-off-by: Gengliang Wang <gengliang@apache.org> |
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.. | ||
catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
create-docs.sh | ||
gen-sql-api-docs.py | ||
gen-sql-config-docs.py | ||
gen-sql-functions-docs.py | ||
mkdocs.yml | ||
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
, and SQL configuration documentation that gets included as part of configuration.md
in the main docs
directory.