OSCL-LXR spark-3.0.0/​docs/​sql-ref-syntax-qry-select-window.md	Source navigation Diff markup Identifier search General search
	Version: spark-3.0.0 hadoop-3.2.0-src hadoop-3.3.0-src spark-2.4.7 linux-4.15.13 Revert   Change

 ---
 layout: global
 title: Window Functions
 displayTitle: Window Functions
 license: |
   Licensed to the Apache Software Foundation (ASF) under one or more
   contributor license agreements.  See the NOTICE file distributed with
   this work for additional information regarding copyright ownership.
   The ASF licenses this file to You under the Apache License, Version 2.0
   (the "License"); you may not use this file except in compliance with
   the License.  You may obtain a copy of the License at
  
      http://www.apache.org/licenses/LICENSE-2.0
  
   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.
 ---
 
 ### Description
 
 Window functions operate on a group of rows, referred to as a window, and calculate a return value for each row based on the group of rows. Window functions are useful for processing tasks such as calculating a moving average, computing a cumulative statistic, or accessing the value of rows given the relative position of the current row.
 
 ### Syntax
 
 ```sql
 window_function OVER
 ( [  { PARTITION | DISTRIBUTE } BY partition_col_name = partition_col_val ( [ , ... ] ) ]
   { ORDER | SORT } BY expression [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [ , ... ]
   [ window_frame ] )
 ```
 
 ### Parameters
 
 * **window_function**
 
     * Ranking Functions
 
       **Syntax:** `RANK | DENSE_RANK | PERCENT_RANK | NTILE | ROW_NUMBER`
 
     * Analytic Functions
 
       **Syntax:** `CUME_DIST | LAG | LEAD`
 
     * Aggregate Functions
 
       **Syntax:** `MAX | MIN | COUNT | SUM | AVG | ...`
 
       Please refer to the [Built-in Aggregation Functions](sql-ref-functions-builtin.html#aggregate-functions) document for a complete list of Spark aggregate functions.
 
 * **window_frame**
 
     Specifies which row to start the window on and where to end it.
 
     **Syntax:**
 
     `{ RANGE | ROWS } { frame_start | BETWEEN frame_start AND frame_end }`
 
     * `frame_start` and `frame_end` have the following syntax:
 
       **Syntax:**
 
       `UNBOUNDED PRECEDING | offset PRECEDING | CURRENT ROW | offset FOLLOWING | UNBOUNDED FOLLOWING`
 
       `offset:` specifies the `offset` from the position of the current row.
 
     **Note:** If `frame_end` is omitted it defaults to `CURRENT ROW`.
 
 ### Examples
 
 ```sql
 CREATE TABLE employees (name STRING, dept STRING, salary INT, age INT);
 
 INSERT INTO employees VALUES ("Lisa", "Sales", 10000, 35);
 INSERT INTO employees VALUES ("Evan", "Sales", 32000, 38);
 INSERT INTO employees VALUES ("Fred", "Engineering", 21000, 28);
 INSERT INTO employees VALUES ("Alex", "Sales", 30000, 33);
 INSERT INTO employees VALUES ("Tom", "Engineering", 23000, 33);
 INSERT INTO employees VALUES ("Jane", "Marketing", 29000, 28);
 INSERT INTO employees VALUES ("Jeff", "Marketing", 35000, 38);
 INSERT INTO employees VALUES ("Paul", "Engineering", 29000, 23);
 INSERT INTO employees VALUES ("Chloe", "Engineering", 23000, 25);
 
 SELECT * FROM employees;
 +-----+-----------+------+-----+
 | name|       dept|salary|  age|
 +-----+-----------+------+-----+
 |Chloe|Engineering| 23000|   25|
 | Fred|Engineering| 21000|   28|
 | Paul|Engineering| 29000|   23|
 |Helen|  Marketing| 29000|   40|
 |  Tom|Engineering| 23000|   33|
 | Jane|  Marketing| 29000|   28|
 | Jeff|  Marketing| 35000|   38|
 | Evan|      Sales| 32000|   38|
 | Lisa|      Sales| 10000|   35|
 | Alex|      Sales| 30000|   33|
 +-----+-----------+------+-----+
 
 SELECT name, dept, RANK() OVER (PARTITION BY dept ORDER BY salary) AS rank FROM employees;
 +-----+-----------+------+----+
 | name|       dept|salary|rank|
 +-----+-----------+------+----+
 | Lisa|      Sales| 10000|   1|
 | Alex|      Sales| 30000|   2|
 | Evan|      Sales| 32000|   3|
 | Fred|Engineering| 21000|   1|
 |  Tom|Engineering| 23000|   2|
 |Chloe|Engineering| 23000|   2|
 | Paul|Engineering| 29000|   4|
 |Helen|  Marketing| 29000|   1|
 | Jane|  Marketing| 29000|   1|
 | Jeff|  Marketing| 35000|   3|
 +-----+-----------+------+----+
 
 SELECT name, dept, DENSE_RANK() OVER (PARTITION BY dept ORDER BY salary ROWS BETWEEN
     UNBOUNDED PRECEDING AND CURRENT ROW) AS dense_rank FROM employees;
 +-----+-----------+------+----------+
 | name|       dept|salary|dense_rank|
 +-----+-----------+------+----------+
 | Lisa|      Sales| 10000|         1|
 | Alex|      Sales| 30000|         2|
 | Evan|      Sales| 32000|         3|
 | Fred|Engineering| 21000|         1|
 |  Tom|Engineering| 23000|         2|
 |Chloe|Engineering| 23000|         2|
 | Paul|Engineering| 29000|         3|
 |Helen|  Marketing| 29000|         1|
 | Jane|  Marketing| 29000|         1|
 | Jeff|  Marketing| 35000|         2|
 +-----+-----------+------+----------+
 
 SELECT name, dept, age, CUME_DIST() OVER (PARTITION BY dept ORDER BY age
     RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS cume_dist FROM employees;
 +-----+-----------+------+------------------+
 | name|       dept|age   |         cume_dist|
 +-----+-----------+------+------------------+
 | Alex|      Sales|    33|0.3333333333333333|
 | Lisa|      Sales|    35|0.6666666666666666|
 | Evan|      Sales|    38|               1.0|
 | Paul|Engineering|    23|              0.25|
 |Chloe|Engineering|    25|              0.75|
 | Fred|Engineering|    28|              0.25|
 |  Tom|Engineering|    33|               1.0|
 | Jane|  Marketing|    28|0.3333333333333333|
 | Jeff|  Marketing|    38|0.6666666666666666|
 |Helen|  Marketing|    40|               1.0|
 +-----+-----------+------+------------------+
 
 SELECT name, dept, salary, MIN(salary) OVER (PARTITION BY dept ORDER BY salary) AS min
     FROM employees;
 +-----+-----------+------+-----+
 | name|       dept|salary|  min|
 +-----+-----------+------+-----+
 | Lisa|      Sales| 10000|10000|
 | Alex|      Sales| 30000|10000|
 | Evan|      Sales| 32000|10000|
 |Helen|  Marketing| 29000|29000|
 | Jane|  Marketing| 29000|29000|
 | Jeff|  Marketing| 35000|29000|
 | Fred|Engineering| 21000|21000|
 |  Tom|Engineering| 23000|21000|
 |Chloe|Engineering| 23000|21000|
 | Paul|Engineering| 29000|21000|
 +-----+-----------+------+-----+
 
 SELECT name, salary,
     LAG(salary) OVER (PARTITION BY dept ORDER BY salary) AS lag,
     LEAD(salary, 1, 0) OVER (PARTITION BY dept ORDER BY salary) AS lead
     FROM employees;
 +-----+-----------+------+-----+-----+
 | name|       dept|salary|  lag| lead|
 +-----+-----------+------+-----+-----+
 | Lisa|      Sales| 10000|NULL |30000|
 | Alex|      Sales| 30000|10000|32000|
 | Evan|      Sales| 32000|30000|    0|
 | Fred|Engineering| 21000| NULL|23000|
 |Chloe|Engineering| 23000|21000|23000|
 |  Tom|Engineering| 23000|23000|29000|
 | Paul|Engineering| 29000|23000|    0|
 |Helen|  Marketing| 29000| NULL|29000|
 | Jane|  Marketing| 29000|29000|35000|
 | Jeff|  Marketing| 35000|29000|    0|
 +-----+-----------+------+-----+-----+
 ```
 
 ### Related Statements
 
 * [SELECT](sql-ref-syntax-qry-select.html)

This page was automatically generated by the 2.1.0 LXR engine. The LXR team