571aa27554
## What changes were proposed in this pull request? Equi-height histogram is one of the state-of-the-art statistics for cardinality estimation, which can provide better estimation accuracy, and good at cases with skew data. This PR is to improve join estimation based on equi-height histogram. The difference from basic estimation (based on ndv) is the logic for computing join cardinality and the new ndv after join. The main idea is as follows: 1. find overlapped ranges between two histograms from two join keys; 2. apply the formula `T(A IJ B) = T(A) * T(B) / max(V(A.k1), V(B.k1))` in each overlapped range. ## How was this patch tested? Added new test cases. Author: Zhenhua Wang <wangzhenhua@huawei.com> Closes #19594 from wzhfy/join_estimation_histogram. |
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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 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
.