197f9018a4
## What changes were proposed in this pull request? 1. add instructions of 'cast' function When using 'show functions' and 'desc function cast' command in spark-sql 2. Modify the instructions of functions,such as boolean,tinyint,smallint,int,bigint,float,double,decimal,date,timestamp,binary,string ## How was this patch tested? Before modification: spark-sql>desc function boolean; Function: boolean Class: org.apache.spark.sql.catalyst.expressions.Cast Usage: boolean(expr AS type) - Casts the value `expr` to the target data type `type`. After modification: spark-sql> desc function boolean; Function: boolean Class: org.apache.spark.sql.catalyst.expressions.Cast Usage: boolean(expr) - Casts the value `expr` to the target data type `boolean`. spark-sql> desc function cast Function: cast Class: org.apache.spark.sql.catalyst.expressions.Cast Usage: cast(expr AS type) - Casts the value `expr` to the target data type `type`. Author: liuxian <liu.xian3@zte.com.cn> Closes #17698 from 10110346/wip_lx_0418. |
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catalyst | ||
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hive | ||
hive-thriftserver | ||
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.