4e861db5f1
## What changes were proposed in this pull request?
`LogicalPlan.resolve(...)` uses linear searches to find an attribute matching a name. This is fine in normal cases, but gets problematic when you try to resolve a large number of columns on a plan with a large number of attributes.
This PR adds an indexing structure to `resolve(...)` in order to find potential matches quicker. This PR improves the reference resolution time for the following code by 4x (11.8s -> 2.4s):
``` scala
val n = 4000
val values = (1 to n).map(_.toString).mkString(", ")
val columns = (1 to n).map("column" + _).mkString(", ")
val query =
s"""
|SELECT $columns
|FROM VALUES ($values) T($columns)
|WHERE 1=2 AND 1 IN ($columns)
|GROUP BY $columns
|ORDER BY $columns
|""".stripMargin
spark.time(sql(query))
```
## How was this patch tested?
Existing tests.
Author: Herman van Hovell <hvanhovell@databricks.com>
Closes #14083 from hvanhovell/SPARK-16406.
|
||
|---|---|---|
| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| create-docs.sh | ||
| gen-sql-markdown.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 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.