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Zhenhua Wang 11b60af737 [SPARK-17074][SQL] Generate equi-height histogram in column statistics 
## What changes were proposed in this pull request?

Equi-height histogram is effective in cardinality estimation, and more accurate than basic column stats (min, max, ndv, etc) especially in skew distribution. So we need to support it.

For equi-height histogram, all buckets (intervals) have the same height (frequency).
In this PR, we use a two-step method to generate an equi-height histogram:
1. use `ApproximatePercentile` to get percentiles `p(0), p(1/n), p(2/n) ... p((n-1)/n), p(1)`;
2. construct range values of buckets, e.g. `[p(0), p(1/n)], [p(1/n), p(2/n)] ... [p((n-1)/n), p(1)]`, and use `ApproxCountDistinctForIntervals` to count ndv in each bucket. Each bucket is of the form: `(lowerBound, higherBound, ndv)`.

## How was this patch tested?

Added new test cases and modified some existing test cases.

Author: Zhenhua Wang <wangzhenhua@huawei.com>
Author: Zhenhua Wang <wzh_zju@163.com>

Closes #19479 from wzhfy/generate_histogram.
2017-11-14 16:41:43 +01:00
..
catalyst [SPARK-17074][SQL] Generate equi-height histogram in column statistics 2017-11-14 16:41:43 +01:00
core [SPARK-17074][SQL] Generate equi-height histogram in column statistics 2017-11-14 16:41:43 +01:00
hive [SPARK-17074][SQL] Generate equi-height histogram in column statistics 2017-11-14 16:41:43 +01:00
hive-thriftserver [SPARK-22487][SQL][FOLLOWUP] still keep spark.sql.hive.version 2017-11-13 13:10:13 -08:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00

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 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.