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Gengliang Wang 02e9f93309 [SPARK-27384][SQL] File source V2: Prune unnecessary partition columns 
## What changes were proposed in this pull request?

When scanning file sources, we can prune unnecessary partition columns on constructing input partitions, so that:
1. Reduce the data transformation from Driver to Executors
2. Make it easier to implement columnar batch readers, since the partition columns are already pruned.
## How was this patch tested?

Existing unit tests.

Closes #24296 from gengliangwang/prunePartitionValue.

Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2019-04-08 15:14:02 +08:00
..
catalyst [SPARK-27390][CORE][SQL][TEST] Fix package name mismatch 2019-04-05 11:50:37 -07:00
core [SPARK-27384][SQL] File source V2: Prune unnecessary partition columns 2019-04-08 15:14:02 +08:00
hive [SPARK-27383][SQL][TEST] Avoid using hard-coded jar names in Hive tests 2019-04-06 18:06:52 -05:00
hive-thriftserver [SPARK-26992][STS] Fix STS scheduler pool correct delivery 2019-04-06 17:14:29 -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.