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Maxim Gekk 63e4bf42c2 [SPARK-27401][SQL] Refactoring conversion of Timestamp to/from java.sql.Timestamp 
## What changes were proposed in this pull request?

In the PR, I propose simpler implementation of `toJavaTimestamp()`/`fromJavaTimestamp()` by reusing existing functions of `DateTimeUtils`. This will allow to:
- Simply implementation of `toJavaTimestamp()`, and handle properly negative inputs.
- Detect `Long` overflow in conversion of milliseconds (`java.sql.Timestamp`) to microseconds (Catalyst's Timestamp).

## How was this patch tested?

By existing test suites `DateTimeUtilsSuite`, `DateFunctionsSuite`, `DateExpressionsSuite` and `CastSuite`. And by new benchmark for export/import timestamps added to `DateTimeBenchmark`:

Before:
```
To/from java.sql.Timestamp:               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------------------------------
From java.sql.Timestamp                             290            335          49         17.2          58.0       1.0X
Collect longs                                      1234           1681         487          4.1         246.8       0.2X
Collect timestamps                                 1718           1755          63          2.9         343.7       0.2X
```

After:
```
To/from java.sql.Timestamp:               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------------------------------
From java.sql.Timestamp                             283            301          19         17.7          56.6       1.0X
Collect longs                                      1048           1087          36          4.8         209.6       0.3X
Collect timestamps                                 1425           1479          56          3.5         285.1       0.2X
```

Closes #24311 from MaxGekk/conv-java-sql-date-timestamp.

Authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2019-04-09 15:42:27 -07:00
..
catalyst [SPARK-27401][SQL] Refactoring conversion of Timestamp to/from java.sql.Timestamp 2019-04-09 15:42:27 -07:00
core [SPARK-27401][SQL] Refactoring conversion of Timestamp to/from java.sql.Timestamp 2019-04-09 15:42:27 -07:00
hive [SPARK-27271][SQL] Migrate Text to File Data Source V2 2019-04-08 10:15:22 -07:00
hive-thriftserver [SPARK-26992][STS] Fix STS scheduler pool correct delivery 2019-04-06 17:14:29 -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-27328][SQL] Add 'deprecated' in ExpressionDescription for extended usage and SQL doc 2019-04-09 13:49:42 +08:00
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.