spark-instrumented-optimizer/sql
Wenchen Fan 25c2edf6f9 [SPARK-21229][SQL] remove QueryPlan.preCanonicalized
## What changes were proposed in this pull request?

`QueryPlan.preCanonicalized` is only overridden in a few places, and it does introduce an extra concept to `QueryPlan` which may confuse people.

This PR removes it and override `canonicalized` in these places

## How was this patch tested?

existing tests

Author: Wenchen Fan <wenchen@databricks.com>

Closes #18440 from cloud-fan/minor.
2017-06-29 11:21:50 +08:00
..
catalyst [SPARK-21229][SQL] remove QueryPlan.preCanonicalized 2017-06-29 11:21:50 +08:00
core [SPARK-21229][SQL] remove QueryPlan.preCanonicalized 2017-06-29 11:21:50 +08:00
hive [SPARK-21216][SS] Hive strategies missed in Structured Streaming IncrementalExecution 2017-06-28 10:45:45 -07:00
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

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.