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Maxim Gekk 1882912cca [SPARK-27199][SQL] Replace TimeZone by ZoneId in TimestampFormatter API 
## What changes were proposed in this pull request?

In the PR, I propose to use `ZoneId` instead of `TimeZone` in:
- the `apply` and `getFractionFormatter ` methods of the `TimestampFormatter` object,
- and in implementations of the `TimestampFormatter` trait like `FractionTimestampFormatter`.

The reason of the changes is to avoid unnecessary conversion from `TimeZone` to `ZoneId` because `ZoneId` is used in `TimestampFormatter` implementations internally, and the conversion is performed via `String` which is not for free. Also taking into account that `TimeZone` instances are converted from `String` in some cases, the worse case looks like `String` -> `TimeZone` -> `String` -> `ZoneId`. The PR eliminates the unneeded conversions.

## How was this patch tested?

It was tested by `DateExpressionsSuite`, `DateTimeUtilsSuite` and `TimestampFormatterSuite`.

Closes #24141 from MaxGekk/zone-id.

Authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2019-03-20 21:28:11 +09:00
..
catalyst [SPARK-27199][SQL] Replace TimeZone by ZoneId in TimestampFormatter API 2019-03-20 21:28:11 +09:00
core [SPARK-27199][SQL] Replace TimeZone by ZoneId in TimestampFormatter API 2019-03-20 21:28:11 +09:00
hive [SPARK-26176][SQL] Verify column names for CTAS with STORED AS 2019-03-19 20:29:47 +08:00
hive-thriftserver [SPARK-27010][SQL] Find out the actual port number when hive.server2.thrift.port=0 2019-03-12 13:38:41 -05:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [MINOR][DOC] Fix some typos and grammar issues 2018-04-06 13:37:08 +08:00

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 allow 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.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.