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Wenchen Fan 0e80ecae30 [SPARK-21100][SQL][FOLLOWUP] cleanup code and add more comments for Dataset.summary 
## What changes were proposed in this pull request?

Some code cleanup and adding comments to make the code more readable. Changed the way to generate result rows, to be more clear.

## How was this patch tested?

existing tests

Author: Wenchen Fan <wenchen@databricks.com>

Closes #18570 from cloud-fan/summary.
2017-07-09 22:53:27 -07:00
..
catalyst [SPARK-18016][SQL][FOLLOWUP] merge declareAddedFunctions, initNestedClasses and declareNestedClasses 2017-07-09 16:30:35 -07:00
core [SPARK-21100][SQL][FOLLOWUP] cleanup code and add more comments for Dataset.summary 2017-07-09 22:53:27 -07:00
hive [SPARK-21083][SQL] Store zero size and row count when analyzing empty table 2017-07-08 20:44:12 +08:00
hive-thriftserver [SPARK-20345][SQL] Fix STS error handling logic on HiveSQLException 2017-06-12 14:05:03 -07:00
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.