spark-instrumented-optimizer/sql
Ryan Blue 6e95325fc3 [SPARK-18387][SQL] Add serialization to checkEvaluation.
## What changes were proposed in this pull request?

This removes the serialization test from RegexpExpressionsSuite and
replaces it by serializing all expressions in checkEvaluation.

This also fixes math constant expressions by making LeafMathExpression
Serializable and fixes NumberFormat values that are null or invalid
after serialization.

## How was this patch tested?

This patch is to tests.

Author: Ryan Blue <blue@apache.org>

Closes #15847 from rdblue/SPARK-18387-fix-serializable-expressions.
2016-11-11 13:52:10 -08:00
..
catalyst [SPARK-18387][SQL] Add serialization to checkEvaluation. 2016-11-11 13:52:10 -08:00
core [SPARK-17982][SQL] SQLBuilder should wrap the generated SQL with parenthesis for LIMIT 2016-11-11 13:28:18 -08:00
hive [SPARK-17982][SQL] SQLBuilder should wrap the generated SQL with parenthesis for LIMIT 2016-11-11 13:28:18 -08:00
hive-thriftserver [SPARK-14914][CORE] Fix Resource not closed after using, for unit tests and example 2016-11-10 10:54:36 +00:00
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.