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Liang-Chi Hsieh dd85eb5448 [SPARK-18107][SQL] Insert overwrite statement runs much slower in spark-sql than it does in hive-client 
## What changes were proposed in this pull request?

As reported on the jira, insert overwrite statement runs much slower in Spark, compared with hive-client.

It seems there is a patch [HIVE-11940](ba21806b77) which largely improves insert overwrite performance on Hive. HIVE-11940 is patched after Hive 2.0.0.

Because Spark SQL uses older Hive library, we can not benefit from such improvement.

The reporter verified that there is also a big performance gap between Hive 1.2.1 (520.037 secs) and Hive 2.0.1 (35.975 secs) on insert overwrite execution.

Instead of upgrading to Hive 2.0 in Spark SQL, which might not be a trivial task, this patch provides an approach to delete the partition before asking Hive to load data files into the partition.

Note: The case reported on the jira is insert overwrite to partition. Since `Hive.loadTable` also uses the function to replace files, insert overwrite to table should has the same issue. We can take the same approach to delete the table first. I will upgrade this to include this.
## How was this patch tested?

Jenkins tests.

There are existing tests using insert overwrite statement. Those tests should be passed. I added a new test to specially test insert overwrite into partition.

For performance issue, as I don't have Hive 2.0 environment, this needs the reporter to verify it. Please refer to the jira.

Please review https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark before opening a pull request.

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #15667 from viirya/improve-hive-insertoverwrite.
2016-11-01 00:24:08 -07:00
..
catalyst [SPARK-17970][SQL] store partition spec in metastore for data source table 2016-10-27 14:22:30 -07:00
core [SPARK-18024][SQL] Introduce an internal commit protocol API 2016-10-31 22:23:38 -07:00
hive [SPARK-18107][SQL] Insert overwrite statement runs much slower in spark-sql than it does in hive-client 2016-11-01 00:24:08 -07:00
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.