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jiangxingbo 344dcad701 [SPARK-17868][SQL] Do not use bitmasks during parsing and analysis of CUBE/ROLLUP/GROUPING SETS 
## What changes were proposed in this pull request?

We generate bitmasks for grouping sets during the parsing process, and use these during analysis. These bitmasks are difficult to work with in practice and have lead to numerous bugs. This PR removes these and use actual sets instead, however we still need to generate these offsets for the grouping_id.

This PR does the following works:
1. Replace bitmasks by actual grouping sets durning Parsing/Analysis stage of CUBE/ROLLUP/GROUPING SETS;
2. Add new testsuite `ResolveGroupingAnalyticsSuite` to test the `Analyzer.ResolveGroupingAnalytics` rule directly;
3. Fix a minor bug in `ResolveGroupingAnalytics`.
## How was this patch tested?

By existing test cases, and add new testsuite `ResolveGroupingAnalyticsSuite` to test directly.

Author: jiangxingbo <jiangxb1987@gmail.com>

Closes #15484 from jiangxb1987/group-set.
2016-11-08 15:11:03 +01:00
..
catalyst [SPARK-17868][SQL] Do not use bitmasks during parsing and analysis of CUBE/ROLLUP/GROUPING SETS 2016-11-08 15:11:03 +01:00
core [SPARK-18217][SQL] Disallow creating permanent views based on temporary views or UDFs 2016-11-07 18:34:21 -08:00
hive [SPARK-18137][SQL] Fix RewriteDistinctAggregates UnresolvedException when a UDAF has a foldable TypeCheck 2016-11-08 12:09:32 +01:00
hive-thriftserver [SPARK-18086] Add support for Hive session vars. 2016-11-07 17:36:15 -08:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -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.