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Yuming Wang b08cf6e822 [SPARK-35203][SQL] Improve Repartition statistics estimation 
### What changes were proposed in this pull request?

This PR improves `Repartition` and `RepartitionByExpr` statistics estimation using child statistics.

### Why are the changes needed?

The current implementation will missing column stat. For example:
```sql
CREATE TABLE t1 USING parquet AS SELECT id % 10 AS key FROM range(100);
ANALYZE TABLE t1 COMPUTE STATISTICS FOR ALL COLUMNS;
set spark.sql.cbo.enabled=true;
EXPLAIN COST SELECT key FROM (SELECT key FROM t1 DISTRIBUTE BY key) t GROUP BY key;
```
Before this PR:
```
== Optimized Logical Plan ==
Aggregate [key#2950L], [key#2950L], Statistics(sizeInBytes=1600.0 B)
+- RepartitionByExpression [key#2950L], Statistics(sizeInBytes=1600.0 B, rowCount=100)
   +- Relation default.t1[key#2950L] parquet, Statistics(sizeInBytes=1600.0 B, rowCount=100)
```
After this PR:
```
== Optimized Logical Plan ==
Aggregate [key#2950L], [key#2950L], Statistics(sizeInBytes=160.0 B, rowCount=10)
+- RepartitionByExpression [key#2950L], Statistics(sizeInBytes=1600.0 B, rowCount=100)
   +- Relation default.t1[key#2950L] parquet, Statistics(sizeInBytes=1600.0 B, rowCount=100)
```

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Unit test.

Closes #32309 from wangyum/SPARK-35203.

Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
2021-06-16 10:20:13 +09:00
..
catalyst [SPARK-35203][SQL] Improve Repartition statistics estimation 2021-06-16 10:20:13 +09:00
core [SPARK-35669][SQL] Quote the pushed column name only when nested column predicate pushdown is enabled 2021-06-16 09:43:28 +09:00
hive [SPARK-35429][CORE] Remove commons-httpclient from Hadoop-3.2 profile due to EOL and CVEs 2021-06-15 14:43:30 -07:00
hive-thriftserver [SPARK-35680][SQL] Add fields to YearMonthIntervalType 2021-06-15 23:08:12 +03:00
create-docs.sh [SPARK-34010][SQL][DODCS] Use python3 instead of python in SQL documentation build 2021-01-05 19:48:10 +09:00
gen-sql-api-docs.py [SPARK-34747][SQL][DOCS] Add virtual operators to the built-in function document 2021-03-19 10:19:26 +09:00
gen-sql-config-docs.py [SPARK-32194][PYTHON] Use proper exception classes instead of plain Exception 2021-05-26 11:54:40 +09:00
gen-sql-functions-docs.py [SPARK-31562][SQL] Update ExpressionDescription for substring, current_date, and current_timestamp 2020-04-26 11:46:52 -07:00
mkdocs.yml [SPARK-30731] Update deprecated Mkdocs option 2020-02-19 17:28:58 +09:00
README.md [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00

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 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.