ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
Tejas Patil 9456688547 [SPARK-17495][SQL] Support date, timestamp and interval types in Hive hash 
## What changes were proposed in this pull request?

- Timestamp hashing is done as per [TimestampWritable.hashCode()](ff67cdda1c/serde/src/java/org/apache/hadoop/hive/serde2/io/TimestampWritable.java (L406)) in Hive
- Interval hashing is done as per [HiveIntervalDayTime.hashCode()](ff67cdda1c/storage-api/src/java/org/apache/hadoop/hive/common/type/HiveIntervalDayTime.java (L178)). Note that there are inherent differences in how Hive and Spark store intervals under the hood which limits the ability to be in completely sync with hive's hashing function. I have explained this in the method doc.
- Date type was already supported. This PR adds test for that.

## How was this patch tested?

Added unit tests

Author: Tejas Patil <tejasp@fb.com>

Closes #17062 from tejasapatil/SPARK-17495_time_related_types.
2017-03-12 20:08:44 -07:00
..
catalyst [SPARK-17495][SQL] Support date, timestamp and interval types in Hive hash 2017-03-12 20:08:44 -07:00
core [DOCS][SS] fix structured streaming python example 2017-03-12 08:29:37 +00:00
hive [SPARK-19723][SQL] create datasource table with an non-existent location should work 2017-03-10 20:59:32 -08:00
hive-thriftserver [SPARK-19673][SQL] "ThriftServer default app name is changed wrong" 2017-02-25 21:47:02 +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.