b5afff59fa
### What changes were proposed in this pull request? This pr pushdown limit through InnerLike when condition is empty(Origin pr: #23104). For example: ```sql CREATE TABLE t1 using parquet AS SELECT id AS a, id AS b FROM range(2); CREATE TABLE t2 using parquet AS SELECT id AS d FROM range(2); SELECT * FROM t1 CROSS JOIN t2 LIMIT 10; ``` Before this pr: ``` == Physical Plan == AdaptiveSparkPlan isFinalPlan=false +- CollectLimit 10 +- BroadcastNestedLoopJoin BuildRight, Cross :- FileScan parquet default.t1[a#5L,b#6L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/private/var/folders/tg/f5mz46090wg7swzgdc69f8q03965_0/T/warehous..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<a:bigint,b:bigint> +- BroadcastExchange IdentityBroadcastMode, [id=#43] +- FileScan parquet default.t2[d#7L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/private/var/folders/tg/f5mz46090wg7swzgdc69f8q03965_0/T/warehous..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<d:bigint> ``` After this pr: ``` == Physical Plan == AdaptiveSparkPlan isFinalPlan=false +- CollectLimit 10 +- BroadcastNestedLoopJoin BuildRight, Cross :- LocalLimit 10 : +- FileScan parquet default.t1[a#5L,b#6L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/private/var/folders/tg/f5mz46090wg7swzgdc69f8q03965_0/T/warehous..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<a:bigint,b:bigint> +- BroadcastExchange IdentityBroadcastMode, [id=#51] +- LocalLimit 10 +- FileScan parquet default.t2[d#7L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/private/var/folders/tg/f5mz46090wg7swzgdc69f8q03965_0/T/warehous..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<d:bigint> ``` ### Why are the changes needed? Improve query performance. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Unit test. Closes #31567 from wangyum/SPARK-26138. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Yuming Wang <yumwang@ebay.com> |
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.. | ||
catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
create-docs.sh | ||
gen-sql-api-docs.py | ||
gen-sql-config-docs.py | ||
gen-sql-functions-docs.py | ||
mkdocs.yml | ||
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.