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Sean Owen 4ecbe1b92f
[SPARK-17810][SQL] Default spark.sql.warehouse.dir is relative to local FS but can resolve as HDFS path 
## What changes were proposed in this pull request?

Always resolve spark.sql.warehouse.dir as a local path, and as relative to working dir not home dir

## How was this patch tested?

Existing tests.

Author: Sean Owen <sowen@cloudera.com>

Closes #15382 from srowen/SPARK-17810.
2016-10-24 10:44:45 +01:00
..
catalyst [SPARK-18058][SQL] Comparing column types ignoring Nullability in Union and SetOperation 2016-10-23 19:42:11 +02:00
core [SPARK-17810][SQL] Default spark.sql.warehouse.dir is relative to local FS but can resolve as HDFS path 2016-10-24 10:44:45 +01:00
hive [SPARK-17810][SQL] Default spark.sql.warehouse.dir is relative to local FS but can resolve as HDFS path 2016-10-24 10:44:45 +01:00
hive-thriftserver [SPARK-17819][SQL] Support default database in connection URIs for Spark Thrift Server 2016-10-16 20:15:32 -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.