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Bryan Cutler be08b415da [SPARK-27163][PYTHON] Cleanup and consolidate Pandas UDF functionality 
## What changes were proposed in this pull request?

This change is a cleanup and consolidation of 3 areas related to Pandas UDFs:

1) `ArrowStreamPandasSerializer` now inherits from `ArrowStreamSerializer` and uses the base class `dump_stream`, `load_stream` to create Arrow reader/writer and send Arrow record batches.  `ArrowStreamPandasSerializer` makes the conversions to/from Pandas and converts to Arrow record batch iterators. This change removed duplicated creation of Arrow readers/writers.

2) `createDataFrame` with Arrow now uses `ArrowStreamPandasSerializer` instead of doing its own conversions from Pandas to Arrow and sending record batches through `ArrowStreamSerializer`.

3) Grouped Map UDFs now reuse existing logic in `ArrowStreamPandasSerializer` to send Pandas DataFrame results as a `StructType` instead of separating each column from the DataFrame. This makes the code a little more consistent with the Python worker, but does require that the returned StructType column is flattened out in `FlatMapGroupsInPandasExec` in Scala.

## How was this patch tested?

Existing tests and ran tests with pyarrow 0.12.0

Closes #24095 from BryanCutler/arrow-refactor-cleanup-UDFs.

Authored-by: Bryan Cutler <cutlerb@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-21 17:44:51 +09:00
..
catalyst [SPARK-26894][SQL] Handle Alias as well in AggregateEstimation to propagate child stats 2019-03-21 11:21:56 +09:00
core [SPARK-27163][PYTHON] Cleanup and consolidate Pandas UDF functionality 2019-03-21 17:44:51 +09:00
hive [SPARK-26839][SQL] Work around classloader changes in Java 9 for Hive isolation 2019-03-20 09:12:52 -05:00
hive-thriftserver [SPARK-27010][SQL] Find out the actual port number when hive.server2.thrift.port=0 2019-03-12 13:38:41 -05:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [MINOR][DOC] Fix some typos and grammar issues 2018-04-06 13:37:08 +08:00

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 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.