spark-instrumented-optimizer/sql
Wenchen Fan 52e00f7066 [SPARK-23280][SQL] add map type support to ColumnVector
## What changes were proposed in this pull request?

Fill the last missing piece of `ColumnVector`: the map type support.

The idea is similar to the array type support. A map is basically 2 arrays: keys and values. We ask the implementations to provide a key array, a value array, and an offset and length to specify the range of this map in the key/value array.

In `WritableColumnVector`, we put the key array in first child vector, and value array in second child vector, and offsets and lengths in the current vector, which is very similar to how array type is implemented here.

## How was this patch tested?

a new test

Author: Wenchen Fan <wenchen@databricks.com>

Closes #20450 from cloud-fan/map.
2018-02-01 11:56:06 +08:00
..
catalyst [SPARK-23281][SQL] Query produces results in incorrect order when a composite order by clause refers to both original columns and aliases 2018-01-31 13:52:47 -08:00
core [SPARK-23280][SQL] add map type support to ColumnVector 2018-02-01 11:56:06 +08:00
hive [SPARK-23276][SQL][TEST] Enable UDT tests in (Hive)OrcHadoopFsRelationSuite 2018-01-30 17:14:17 -08:00
hive-thriftserver [SPARK-22837][SQL] Session timeout checker does not work in SessionManager. 2018-01-24 10:07:24 -08:00
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

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.