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Maxim Gekk f982ca07e8 [SPARK-26178][SQL] Use java.time API for parsing timestamps and dates from CSV 
## What changes were proposed in this pull request?

In the PR, I propose to use **java.time API** for parsing timestamps and dates from CSV content with microseconds precision. The SQL config `spark.sql.legacy.timeParser.enabled` allow to switch back to previous behaviour with using `java.text.SimpleDateFormat`/`FastDateFormat` for parsing/generating timestamps/dates.

## How was this patch tested?

It was tested by `UnivocityParserSuite`, `CsvExpressionsSuite`, `CsvFunctionsSuite` and `CsvSuite`.

Closes #23150 from MaxGekk/time-parser.

Lead-authored-by: Maxim Gekk <max.gekk@gmail.com>
Co-authored-by: Maxim Gekk <maxim.gekk@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2018-12-04 08:36:33 -06:00
..
catalyst [SPARK-26178][SQL] Use java.time API for parsing timestamps and dates from CSV 2018-12-04 08:36:33 -06:00
core [SPARK-26178][SQL] Use java.time API for parsing timestamps and dates from CSV 2018-12-04 08:36:33 -06:00
hive [SPARK-25374][SQL] SafeProjection supports fallback to an interpreted mode 2018-12-04 20:20:29 +08:00
hive-thriftserver [SPARK-26090][CORE][SQL][ML] Resolve most miscellaneous deprecation and build warnings for Spark 3 2018-11-19 09:16:42 -06:00
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.