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Ruben Berenguel Montoro 427359f077 [SPARK-13947][SQL] The error message from using an invalid column reference is not clear 
## What changes were proposed in this pull request?

 Rewritten error message for clarity. Added extra information in case of attribute name collision, hinting the user to double-check referencing two different tables

## How was this patch tested?

No functional changes, only final message has changed. It has been tested manually against the situation proposed in the JIRA ticket. Automated tests in repository pass.

This PR is original work from me and I license this work to the Spark project

Author: Ruben Berenguel Montoro <ruben@mostlymaths.net>
Author: Ruben Berenguel Montoro <ruben@dreamattic.com>
Author: Ruben Berenguel <ruben@mostlymaths.net>

Closes #17100 from rberenguel/SPARK-13947-error-message.
2017-10-24 23:02:11 -07:00
..
catalyst [SPARK-13947][SQL] The error message from using an invalid column reference is not clear 2017-10-24 23:02:11 -07:00
core [SPARK-13947][SQL] The error message from using an invalid column reference is not clear 2017-10-24 23:02:11 -07:00
hive [SPARK-21101][SQL] Catch IllegalStateException when CREATE TEMPORARY FUNCTION 2017-10-24 22:59:46 -07:00
hive-thriftserver [SPARK-22087][SPARK-14650][WIP][BUILD][REPL][CORE] Compile Spark REPL for Scala 2.12 + other 2.12 fixes 2017-09-24 09:40:13 +01:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -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.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.