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Eric Liang 294163ee93 [SPARK-18679][SQL] Fix regression in file listing performance for non-catalog tables 
## What changes were proposed in this pull request?

In Spark 2.1 ListingFileCatalog was significantly refactored (and renamed to InMemoryFileIndex). This introduced a regression where parallelism could only be introduced at the very top of the tree. However, in many cases (e.g. `spark.read.parquet(topLevelDir)`), the top of the tree is only a single directory.

This PR simplifies and fixes the parallel recursive listing code to allow parallelism to be introduced at any level during recursive descent (though note that once we decide to list a sub-tree in parallel, the sub-tree is listed in serial on executors).

cc mallman  cloud-fan

## How was this patch tested?

Checked metrics in unit tests.

Author: Eric Liang <ekl@databricks.com>

Closes #16112 from ericl/spark-18679.
2016-12-02 20:59:39 +08:00
..
catalyst [SPARK-18658][SQL] Write text records directly to a FileOutputStream 2016-12-01 21:40:49 -08:00
core [SPARK-18679][SQL] Fix regression in file listing performance for non-catalog tables 2016-12-02 20:59:39 +08:00
hive [SPARK-18658][SQL] Write text records directly to a FileOutputStream 2016-12-01 21:40:49 -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

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.