ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
petermaxlee 9812f7d538 [SPARK-17165][SQL] FileStreamSource should not track the list of seen files indefinitely 
## What changes were proposed in this pull request?
Before this change, FileStreamSource uses an in-memory hash set to track the list of files processed by the engine. The list can grow indefinitely, leading to OOM or overflow of the hash set.

This patch introduces a new user-defined option called "maxFileAge", default to 24 hours. If a file is older than this age, FileStreamSource will purge it from the in-memory map that was used to track the list of files that have been processed.

## How was this patch tested?
Added unit tests for the underlying utility, and also added an end-to-end test to validate the purge in FileStreamSourceSuite. Also verified the new test cases would fail when the timeout was set to a very large number.

Author: petermaxlee <petermaxlee@gmail.com>

Closes #14728 from petermaxlee/SPARK-17165.
2016-08-26 11:30:23 -07:00
..
catalyst [SPARK-17187][SQL][FOLLOW-UP] improve document of TypedImperativeAggregate 2016-08-26 10:56:57 -07:00
core [SPARK-17165][SQL] FileStreamSource should not track the list of seen files indefinitely 2016-08-26 11:30:23 -07:00
hive [SPARK-17250][SQL] Remove HiveClient and setCurrentDatabase from HiveSessionCatalog 2016-08-26 11:19:03 -07:00
hive-thriftserver [SPARK-17190][SQL] Removal of HiveSharedState 2016-08-25 12:50:03 +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.