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Michael Allman 772ddbeaa6 [SPARK-18572][SQL] Add a method listPartitionNames to ExternalCatalog 
(Link to Jira issue: https://issues.apache.org/jira/browse/SPARK-18572)

## What changes were proposed in this pull request?

Currently Spark answers the `SHOW PARTITIONS` command by fetching all of the table's partition metadata from the external catalog and constructing partition names therefrom. The Hive client has a `getPartitionNames` method which is many times faster for this purpose, with the performance improvement scaling with the number of partitions in a table.

To test the performance impact of this PR, I ran the `SHOW PARTITIONS` command on two Hive tables with large numbers of partitions. One table has ~17,800 partitions, and the other has ~95,000 partitions. For the purposes of this PR, I'll call the former table `table1` and the latter table `table2`. I ran 5 trials for each table with before-and-after versions of this PR. The results are as follows:

Spark at bdc8153, `SHOW PARTITIONS table1`, times in seconds:
7.901
3.983
4.018
4.331
4.261

Spark at bdc8153, `SHOW PARTITIONS table2`
(Timed out after 10 minutes with a `SocketTimeoutException`.)

Spark at this PR, `SHOW PARTITIONS table1`, times in seconds:
3.801
0.449
0.395
0.348
0.336

Spark at this PR, `SHOW PARTITIONS table2`, times in seconds:
5.184
1.63
1.474
1.519
1.41

Taking the best times from each trial, we get a 12x performance improvement for a table with ~17,800 partitions and at least a 426x improvement for a table with ~95,000 partitions. More significantly, the latter command doesn't even complete with the current code in master.

This is actually a patch we've been using in-house at VideoAmp since Spark 1.1. It's made all the difference in the practical usability of our largest tables. Even with tables with about 1,000 partitions there's a performance improvement of about 2-3x.

## How was this patch tested?

I added a unit test to `VersionsSuite` which tests that the Hive client's `getPartitionNames` method returns the correct number of partitions.

Author: Michael Allman <michael@videoamp.com>

Closes #15998 from mallman/spark-18572-list_partition_names.
2016-12-06 11:33:35 +08:00
..
catalyst [SPARK-18572][SQL] Add a method listPartitionNames to ExternalCatalog 2016-12-06 11:33:35 +08:00
core [SPARK-18572][SQL] Add a method listPartitionNames to ExternalCatalog 2016-12-06 11:33:35 +08:00
hive [SPARK-18572][SQL] Add a method listPartitionNames to ExternalCatalog 2016-12-06 11:33:35 +08:00
hive-thriftserver [SPARK-18695] Bump master branch version to 2.2.0-SNAPSHOT 2016-12-02 21:09:37 -08:00
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.