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Wenchen Fan a05cc425a0 [SPARK-18990][SQL] make DatasetBenchmark fairer for Dataset 
## What changes were proposed in this pull request?

Currently `DatasetBenchmark` use `case class Data(l: Long, s: String)` as the record type of `RDD` and `Dataset`, which introduce serialization overhead only to `Dataset` and is unfair.

This PR use `Long` as the record type, to be fairer for `Dataset`

## How was this patch tested?

existing tests

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16391 from cloud-fan/benchmark.
2016-12-27 22:42:28 +08:00
..
catalyst [SPARK-18999][SQL][MINOR] simplify Literal codegen 2016-12-27 06:22:12 -08:00
core [SPARK-18990][SQL] make DatasetBenchmark fairer for Dataset 2016-12-27 22:42:28 +08:00
hive [SPARK-18989][SQL] DESC TABLE should not fail with format class not found 2016-12-26 11:27:56 -08:00
hive-thriftserver [SPARK-17807][CORE] split test-tags into test-JAR 2016-12-21 16:37:20 -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.