ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
Bryan Cutler 209b9361ac [SPARK-20791][PYSPARK] Use Arrow to create Spark DataFrame from Pandas 
## What changes were proposed in this pull request?

This change uses Arrow to optimize the creation of a Spark DataFrame from a Pandas DataFrame. The input df is sliced according to the default parallelism. The optimization is enabled with the existing conf "spark.sql.execution.arrow.enabled" and is disabled by default.

## How was this patch tested?

Added new unit test to create DataFrame with and without the optimization enabled, then compare results.

Author: Bryan Cutler <cutlerb@gmail.com>
Author: Takuya UESHIN <ueshin@databricks.com>

Closes #19459 from BryanCutler/arrow-createDataFrame-from_pandas-SPARK-20791.
2017-11-13 13:16:01 +09:00
..
catalyst [SPARK-21720][SQL] Fix 64KB JVM bytecode limit problem with AND or OR 2017-11-12 22:44:47 +01:00
core [SPARK-20791][PYSPARK] Use Arrow to create Spark DataFrame from Pandas 2017-11-13 13:16:01 +09:00
hive [SPARK-22488][SQL] Fix the view resolution issue in the SparkSession internal table() API 2017-11-11 18:20:11 +01:00
hive-thriftserver [SPARK-22487][SQL][HIVE] Remove the unused HIVE_EXECUTION_VERSION property 2017-11-10 12:01:02 +01:00
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 [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00

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 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.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.