fb0e07b08c
### What changes were proposed in this pull request?
This PR add support infer constraints from cast equality constraint. For example:
```scala
scala> spark.sql("create table spark_29231_1(c1 bigint, c2 bigint)")
res0: org.apache.spark.sql.DataFrame = []
scala> spark.sql("create table spark_29231_2(c1 int, c2 bigint)")
res1: org.apache.spark.sql.DataFrame = []
scala> spark.sql("select t1.* from spark_29231_1 t1 join spark_29231_2 t2 on (t1.c1 = t2.c1 and t1.c1 = 1)").explain
== Physical Plan ==
*(2) Project [c1#5L, c2#6L]
+- *(2) BroadcastHashJoin [c1#5L], [cast(c1#7 as bigint)], Inner, BuildRight
:- *(2) Project [c1#5L, c2#6L]
: +- *(2) Filter (isnotnull(c1#5L) AND (c1#5L = 1))
: +- *(2) ColumnarToRow
: +- FileScan parquet default.spark_29231_1[c1#5L,c2#6L] Batched: true, DataFilters: [isnotnull(c1#5L), (c1#5L = 1)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-preview2-bin-hadoop2.7/spark-warehouse/spark_29231_1], PartitionFilters: [], PushedFilters: [IsNotNull(c1), EqualTo(c1,1)], ReadSchema: struct<c1:bigint,c2:bigint>
+- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint))), [id=#209]
+- *(1) Project [c1#7]
+- *(1) Filter isnotnull(c1#7)
+- *(1) ColumnarToRow
+- FileScan parquet default.spark_29231_2[c1#7] Batched: true, DataFilters: [isnotnull(c1#7)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-preview2-bin-hadoop2.7/spark-warehouse/spark_29231_2], PartitionFilters: [], PushedFilters: [IsNotNull(c1)], ReadSchema: struct<c1:int>
```
After this PR:
```scala
scala> spark.sql("select t1.* from spark_29231_1 t1 join spark_29231_2 t2 on (t1.c1 = t2.c1 and t1.c1 = 1)").explain
== Physical Plan ==
*(2) Project [c1#0L, c2#1L]
+- *(2) BroadcastHashJoin [c1#0L], [cast(c1#2 as bigint)], Inner, BuildRight
:- *(2) Project [c1#0L, c2#1L]
: +- *(2) Filter (isnotnull(c1#0L) AND (c1#0L = 1))
: +- *(2) ColumnarToRow
: +- FileScan parquet default.spark_29231_1[c1#0L,c2#1L] Batched: true, DataFilters: [isnotnull(c1#0L), (c1#0L = 1)], Format: Parquet, Location: InMemoryFileIndex[file:/root/opensource/spark/spark-warehouse/spark_29231_1], PartitionFilters: [], PushedFilters: [IsNotNull(c1), EqualTo(c1,1)], ReadSchema: struct<c1:bigint,c2:bigint>
+- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint))), [id=#99]
+- *(1) Project [c1#2]
+- *(1) Filter ((cast(c1#2 as bigint) = 1) AND isnotnull(c1#2))
+- *(1) ColumnarToRow
+- FileScan parquet default.spark_29231_2[c1#2] Batched: true, DataFilters: [(cast(c1#2 as bigint) = 1), isnotnull(c1#2)], Format: Parquet, Location: InMemoryFileIndex[file:/root/opensource/spark/spark-warehouse/spark_29231_2], PartitionFilters: [], PushedFilters: [IsNotNull(c1)], ReadSchema: struct<c1:int>
```
### 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 #27252 from wangyum/SPARK-29231.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
|
||
|---|---|---|
| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| create-docs.sh | ||
| gen-sql-api-docs.py | ||
| gen-sql-config-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.