ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
Xingbo Jiang 031910b0ec [SPARK-21608][SPARK-9221][SQL] Window rangeBetween() API should allow literal boundary 
## What changes were proposed in this pull request?

Window rangeBetween() API should allow literal boundary, that means, the window range frame can calculate frame of double/date/timestamp.

Example of the use case can be:
```
SELECT
	val_timestamp,
	cate,
	avg(val_timestamp) OVER(PARTITION BY cate ORDER BY val_timestamp RANGE BETWEEN CURRENT ROW AND interval 23 days 4 hours FOLLOWING)
FROM testData
```

This PR refactors the Window `rangeBetween` and `rowsBetween` API, while the legacy user code should still be valid.

## How was this patch tested?

Add new test cases both in `DataFrameWindowFunctionsSuite` and in `window.sql`.

Author: Xingbo Jiang <xingbo.jiang@databricks.com>

Closes #18814 from jiangxb1987/literal-boundary.
2017-08-09 13:23:49 +08:00
..
catalyst [SPARK-21608][SPARK-9221][SQL] Window rangeBetween() API should allow literal boundary 2017-08-09 13:23:49 +08:00
core [SPARK-21608][SPARK-9221][SQL] Window rangeBetween() API should allow literal boundary 2017-08-09 13:23:49 +08:00
hive [MINOR][BUILD] Remove duplicate test-jar:test spark-sql dependency from Hive module 2017-08-06 16:48:49 -07:00
hive-thriftserver [SPARK-21637][SPARK-21451][SQL] get spark.hadoop.* properties from sysProps to hiveconf 2017-08-05 17:30:47 -07:00
create-docs.sh [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
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 [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -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.

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