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yi.wu 587266f887 [SPARK-31010][SQL][FOLLOW-UP] Deprecate untyped scala UDF 
### What changes were proposed in this pull request?

Use scala annotation deprecate to deprecate untyped scala UDF.

### Why are the changes needed?

After #27488, it's weird to see the untyped scala UDF will fail by default without deprecation.

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

Yes, user will see the warning:
```
<console>:26: warning: method udf in object functions is deprecated (since 3.0.0): Untyped Scala UDF API is deprecated, please use typed Scala UDF API such as 'def udf[RT: TypeTag](f: Function0[RT]): UserDefinedFunction' instead.
       val myudf = udf(() => Math.random(), DoubleType)
                   ^
```

### How was this patch tested?

Tested manually.

Closes #27794 from Ngone51/deprecate_untyped_scala_udf.

Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-03-06 13:00:04 +08:00
..
catalyst [SPARK-31020][SPARK-31023][SPARK-31025][SPARK-31044][SQL] Support foldable args by from_csv/json and schema_of_csv/json 2020-03-06 12:29:35 +08:00
core [SPARK-31010][SQL][FOLLOW-UP] Deprecate untyped scala UDF 2020-03-06 13:00:04 +08:00
hive [SPARK-31024][SQL] Allow specifying session catalog name spark_catalog in qualified column names for v1 tables 2020-03-05 18:33:59 +08:00
hive-thriftserver [SPARK-30049][SQL] SQL fails to parse when comment contains an unmatched quote character 2020-03-03 09:55:15 -06:00
create-docs.sh [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00
gen-sql-api-docs.py [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00
gen-sql-config-docs.py [SPARK-30840][CORE][SQL] Add version property for ConfigEntry and ConfigBuilder 2020-02-22 09:46:42 +09:00
mkdocs.yml [SPARK-30731] Update deprecated Mkdocs option 2020-02-19 17:28:58 +09:00
README.md [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00

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, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.