# 窗口函数 窗口函数与OVER语句一起使用。OVER语句用于对数据进行分组，并对组内元素进行排序。窗口函数用于给组内的值生成序号。 ![](https://support.huaweicloud.com/centralized-devg-v8-gaussdb/public_sys-resources/note_3.0-zh-cn.png) 窗口函数中的order by后面必须跟字段名，若order by后面跟数字，该数字会被按照常量处理，因此对目标列没有起到排序的作用。 当父查询中包含子查询中的窗口函数的过滤条件时，支持将父查询中的过滤条件下推到子查询中。 ![](https://support.huaweicloud.com/centralized-devg-v8-gaussdb/public_sys-resources/caution_3.0-zh-cn.png) 1. 只支持将父查询中关于窗口函数的\<、\<=、=过滤条件下推到子查询中。 2. 限制条件范围的上限可以是常量、常量表达式、参数、非VOLATILE类型的函数、非相关子链接。 3. 只支持[ROW_NUMBER()]、[RANK()]、[DENSE_RANK()]三个窗口函数。 示例： ``` --创建表。 gaussdb=# CREATE TABLE t2 (c1 INT, c2 INT); --导入数据。 gaussdb=# INSERT INTO t2 SELECT generate_series, generate_series FROM generate_series(1, 1000000); --执行查询，查询正常无报错，且执行结果正确。 gaussdb=# EXPLAIN ANALYZE SELECT nc1 FROM ( SELECT row_number() over() rid, t2.c1 nc1 FROM t2 ) WHERE rid BETWEEN 1 AND (1 + 10 - 1); QUERY PLAN -------------------------------------------------------------------------------------------------------------------- Subquery Scan on __unnamed_subquery__ (cost=0.00..0.42 rows=3 width=4) (actual time=0.201..0.228 rows=10 loops=1) Filter: (__unnamed_subquery__.rid >= 1) -> WindowAgg (cost=0.00..0.30 rows=10 width=4) (actual time=0.191..0.211 rows=10 loops=1) row_number_filter: (row_number() OVER () <= 10) -> Seq Scan on t2 (cost=0.00..11977.45 rows=817445 width=4) (actual time=0.150..0.153 rows=11 loops=1) Total runtime: 0.539 ms (6 rows) --环境清理，避免数据泄露。 gaussdb=# DROP TABLE t2; ``` #### RANK() 描述：RANK函数为各组内值生成跳跃排序序号，其中，相同的值具有相同序号。 返回值类型：BIGINT 示例： ``` gaussdb=# CREATE TABLE rank_t1(a int, b int); gaussdb=# INSERT INTO rank_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,RANK() OVER(PARTITION BY a ORDER BY b) FROM rank_t1; a | b | rank ---+---+------ 1 | 1 | 1 1 | 1 | 1 1 | 2 | 3 1 | 3 | 4 2 | 4 | 1 2 | 5 | 2 3 | 6 | 1 (7 rows) gaussdb=# DROP TABLE rank_t1; ``` #### ROW_NUMBER() 描述：ROW_NUMBER函数为各组内值生成连续排序序号，其中，相同的值其序号也不相同。 返回值类型：BIGINT 示例： ``` gaussdb=# CREATE TABLE row_number_t1(a int, b int); gaussdb=# INSERT INTO row_number_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,ROW_NUMBER() OVER(PARTITION BY a ORDER BY b) FROM row_number_t1; a | b | row_number ---+---+------------ 1 | 1 | 1 1 | 1 | 2 1 | 2 | 3 1 | 3 | 4 2 | 4 | 1 2 | 5 | 2 3 | 6 | 1 (7 rows) gaussdb=# DROP TABLE row_number_t1; ``` #### DENSE_RANK() 描述：DENSE_RANK函数为各组内值生成连续排序序号，其中，相同的值具有相同序号。 返回值类型：BIGINT 示例： ``` gaussdb=# CREATE TABLE dense_rank_t1(a int, b int); gaussdb=# INSERT INTO dense_rank_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,DENSE_RANK() OVER(PARTITION BY a ORDER BY b) FROM dense_rank_t1; a | b | dense_rank ---+---+------------ 1 | 1 | 1 1 | 1 | 1 1 | 2 | 2 1 | 3 | 3 2 | 4 | 1 2 | 5 | 2 3 | 6 | 1 (7 rows) gaussdb=# DROP TABLE dense_rank_t1; ``` #### PERCENT_RANK() 描述：PERCENT_RANK函数为各组内对应值生成相对序号，即根据公式 (rank - 1) / (totalrows - 1)计算所得的值。其中rank为该值依据RANK函数所生成的对应序号，totalrows为该分组内的总元素个数。 返回值类型：DOUBLE PRECISION 示例： ``` gaussdb=# CREATE TABLE percent_rank_t1(a int, b int); gaussdb=# INSERT INTO percent_rank_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,PERCENT_RANK() OVER(PARTITION BY a ORDER BY b) FROM percent_rank_t1; a | b | percent_rank ---+---+------------------ 1 | 1 | 0 1 | 1 | 0 1 | 2 | .666666666666667 1 | 3 | 1 2 | 4 | 0 2 | 5 | 1 3 | 6 | 0 (7 rows) gaussdb=# DROP TABLE percent_rank_t1; ``` #### CUME_DIST() 描述：CUME_DIST函数为各组内对应值生成累积分布序号。即根据公式(小于等于当前值的数据行数)/(该分组总行数totalrows)计算所得的相对序号。 返回值类型：DOUBLE PRECISION 示例： ``` gaussdb=# CREATE TABLE cume_dist_t1(a int, b int); gaussdb=# INSERT INTO cume_dist_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,CUME_DIST() OVER(PARTITION BY a ORDER BY b) FROM cume_dist_t1; a | b | cume_dist ---+---+----------- 1 | 1 | .5 1 | 1 | .5 1 | 2 | .75 1 | 3 | 1 2 | 4 | .5 2 | 5 | 1 3 | 6 | 1 (7 rows) gaussdb=# DROP TABLE cume_dist_t1; ``` #### NTILE(num_buckets integer) 描述：NTILE函数根据num_buckets integer将有序的数据集合平均分配到num_buckets所指定数量的桶中，并将桶号分配给每一行。分配时应尽量做到平均分配。 返回值类型：INTEGER 示例： ``` gaussdb=# CREATE TABLE ntile_t1(a int, b int); gaussdb=# INSERT INTO ntile_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,NTILE(2) OVER(PARTITION BY a ORDER BY b) FROM ntile_t1; a | b | ntile ---+---+------- 1 | 1 | 1 1 | 1 | 1 1 | 2 | 2 1 | 3 | 2 2 | 4 | 1 2 | 5 | 2 3 | 6 | 1 (7 rows) gaussdb=# DROP TABLE ntile_t1; ``` #### LAG 描述：LAG函数为各组内对应值生成滞后值。即将当前值对应的行数向前偏移offset位后所得行的value值作为序号。若经过向前偏移后行数不存在，则对应结果取为default值。若无指定，在默认情况下，offset取值为1，default值取值为null。default值的类型需要与value值的类型保持一致。 语法： ``` LAG(value any [, offset integer [, default any ]]) LAG(value any ignore|respect nulls [, offset integer [, default any ]]) LAG(value any [, offset integer [, default any ]]) ignore|respect nulls ``` ![](https://support.huaweicloud.com/centralized-devg-v8-gaussdb/figure/zh-cn_image_0000002526899600.png "点击放大") ignore\|respect nulls表示是否将null包含在向前偏移值中。若无指定，则默认是respect nulls。若设置为ignore nulls，当value为null时，则将其不包含在向前偏移值中。如果开启了ignore nulls功能，则该函数会存在性能劣化。 返回值类型：与参数数据类型相同。 示例1：不开启ignore nulls功能，设置offset=3，default=null。 ``` -- 建表并插入数据 gaussdb=# CREATE TABLE ta1 (hire_date date, last_name varchar(20), department_id int); CREATE TABLE gaussdb=# INSERT INTO ta1 VALUES('07-DEC-02', 'Raphaely', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 VALUES('24-JUL-05', 'Tobias', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 VALUES('24-DEC-05', 'Baida', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 VALUES('18-MAY-03', 'Khoo', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('15-NOV-06', 'Himuro', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('10-AUG-07', 'Colmenares', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('10-MAY-07', 'yq', 11); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('10-MAY-08', 'zi', 11); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('', 'yq1', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values(null, 'yq2', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('10-DEC-07', 'yq3', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values(null, null, 11); INSERT 0 1 gaussdb=# INSERT INTO ta1 values(null, null, 11); INSERT 0 1 -- 调用LAG,指定offset=3, default=null gaussdb=# SELECT hire_date, last_name, department_id, lag(hire_date, 3, null) OVER (PARTITION BY department_id ORDER BY last_name) AS "NextHired" FROM ta1 ORDER BY department_id; hire_date | last_name | department_id | NextHired ---------------------+------------+---------------+--------------------- 2007-05-10 00:00:00 | yq | 11 | 2008-05-10 00:00:00 | zi | 11 | | | 11 | | | 11 | 2007-05-10 00:00:00 2005-12-24 00:00:00 | Baida | 30 | 2007-08-10 00:00:00 | Colmenares | 30 | 2006-11-15 00:00:00 | Himuro | 30 | 2003-05-18 00:00:00 | Khoo | 30 | 2005-12-24 00:00:00 2002-12-07 00:00:00 | Raphaely | 30 | 2007-08-10 00:00:00 2005-07-24 00:00:00 | Tobias | 30 | 2006-11-15 00:00:00 | yq1 | 30 | 2003-05-18 00:00:00 | yq2 | 30 | 2002-12-07 00:00:00 2007-12-10 00:00:00 | yq3 | 30 | 2005-07-24 00:00:00 (13 rows) ``` 示例2：开启ignore nulls功能，设置offset=3，default='01-JAN-00'。 ``` gaussdb=# SELECT hire_date, last_name, department_id, lag(hire_date, 3, '01-JAN-00') ignore nulls OVER (PARTITION BY department_id ORDER BY last_name) AS "NextHired" FROM ta1 ORDER BY department_id; hire_date | last_name | department_id | NextHired ---------------------+------------+---------------+--------------------- 2007-05-10 00:00:00 | yq | 11 | 2000-01-01 00:00:00 2008-05-10 00:00:00 | zi | 11 | 2000-01-01 00:00:00 | | 11 | 2000-01-01 00:00:00 | | 11 | 2000-01-01 00:00:00 2005-12-24 00:00:00 | Baida | 30 | 2000-01-01 00:00:00 2007-08-10 00:00:00 | Colmenares | 30 | 2000-01-01 00:00:00 2006-11-15 00:00:00 | Himuro | 30 | 2000-01-01 00:00:00 2003-05-18 00:00:00 | Khoo | 30 | 2005-12-24 00:00:00 2002-12-07 00:00:00 | Raphaely | 30 | 2007-08-10 00:00:00 2005-07-24 00:00:00 | Tobias | 30 | 2006-11-15 00:00:00 | yq1 | 30 | 2003-05-18 00:00:00 | yq2 | 30 | 2003-05-18 00:00:00 2007-12-10 00:00:00 | yq3 | 30 | 2003-05-18 00:00:00 (13 rows) -- 删除表 gaussdb=# DROP TABLE ta1; DROP TABLE ``` #### LEAD 描述：LEAD函数为各组内对应值生成提前值。即当前值对应的行数向后偏移offset位后所得行的value值作为序号。若经过向后偏移后行数超过当前组内的总行数，则对应结果取为default值。若无指定，在默认情况下，offset取为1，default值取为null。default值的类型需要与value值的类型保持一致。 语法： ``` LEAD(value any [, offset integer [, default any ]]) LEAD(value any ignore|respect nulls [, offset integer [, default any ]]) LEAD(value any [, offset integer [, default any ]]) ignore|respect nulls ``` ![](https://support.huaweicloud.com/centralized-devg-v8-gaussdb/figure/zh-cn_image_0000002558059439.png "点击放大") ignore\|respect nulls表示是否将null包含在向后偏移值中。若无指定，则默认是respect nulls。若设置为ignore nulls，当value为null时，则将其不包含在向后偏移值中。如果开启了ignore nulls功能，则该函数会存在性能劣化。 返回值类型：与参数数据类型相同。 示例1：不开启ignore nulls功能，设置offset=2，不指定default。 ``` -- 建表并插入数据 gaussdb=# CREATE TABLE ta1 (hire_date date, last_name varchar(20), department_id int); CREATE TABLE gaussdb=# INSERT INTO ta1 values('07-DEC-02', 'Raphaely', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('24-JUL-05', 'Tobias', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('24-DEC-05', 'Baida', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('18-MAY-03', 'Khoo', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('15-NOV-06', 'Himuro', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('10-AUG-07', 'Colmenares', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('10-MAY-07', 'yq', 11); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('10-MAY-08', 'zi', 11); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('', 'yq1', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values(null, 'yq2', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values('10-DEC-07', 'yq3', 30); INSERT 0 1 gaussdb=# INSERT INTO ta1 values(null, null, 11); INSERT 0 1 gaussdb=# INSERT INTO ta1 values(null, null, 11); INSERT 0 1 -- 调用LEAD,指定offset=2 gaussdb=# SELECT hire_date, last_name, department_id, lead(hire_date, 2) OVER (PARTITION BY department_id ORDER BY last_name) AS "NextHired" FROM ta1 ORDER BY department_id; hire_date | last_name | department_id | NextHired ---------------------+------------+---------------+--------------------- 2007-05-10 00:00:00 | yq | 11 | 2008-05-10 00:00:00 | zi | 11 | | | 11 | | | 11 | 2005-12-24 00:00:00 | Baida | 30 | 2006-11-15 00:00:00 2007-08-10 00:00:00 | Colmenares | 30 | 2003-05-18 00:00:00 2006-11-15 00:00:00 | Himuro | 30 | 2002-12-07 00:00:00 2003-05-18 00:00:00 | Khoo | 30 | 2005-07-24 00:00:00 2002-12-07 00:00:00 | Raphaely | 30 | 2005-07-24 00:00:00 | Tobias | 30 | | yq1 | 30 | 2007-12-10 00:00:00 | yq2 | 30 | 2007-12-10 00:00:00 | yq3 | 30 | (13 rows) ``` 示例2：开启ignore nulls功能，设置offset=2，default='01-JAN-00'。 ``` gaussdb=# SELECT hire_date, last_name, department_id, lead(hire_date, 2, '01-JAN-00') ignore nulls OVER (PARTITION BY department_id ORDER BY last_name) AS "NextHired" FROM ta1 ORDER BY department_id; hire_date | last_name | department_id | NextHired ---------------------+------------+---------------+--------------------- 2007-05-10 00:00:00 | yq | 11 | 2000-01-01 00:00:00 2008-05-10 00:00:00 | zi | 11 | 2000-01-01 00:00:00 | | 11 | 2000-01-01 00:00:00 | | 11 | 2000-01-01 00:00:00 2005-12-24 00:00:00 | Baida | 30 | 2006-11-15 00:00:00 2007-08-10 00:00:00 | Colmenares | 30 | 2003-05-18 00:00:00 2006-11-15 00:00:00 | Himuro | 30 | 2002-12-07 00:00:00 2003-05-18 00:00:00 | Khoo | 30 | 2005-07-24 00:00:00 2002-12-07 00:00:00 | Raphaely | 30 | 2007-12-10 00:00:00 2005-07-24 00:00:00 | Tobias | 30 | 2000-01-01 00:00:00 | yq1 | 30 | 2000-01-01 00:00:00 | yq2 | 30 | 2000-01-01 00:00:00 2007-12-10 00:00:00 | yq3 | 30 | 2000-01-01 00:00:00 (13 rows) -- 删除表 gaussdb=# DROP TABLE ta1; DROP TABLE ``` #### FIRST_VALUE() 描述：FIRST_VALUE函数获取各组内的第一个值作为返回结果。 返回值类型：与参数数据类型相同。 语法： ``` FIRST_VALUE(value any) FIRST_VALUE(value any IGNORE|RESPECT NULLS) FIRST_VALUE(value any) IGNORE|RESPECT NULLS ``` IGNORE\|RESPECT NULLS：表示是否要忽略NULL值。其中RESPECT NULLS是缺省值。若开启IGNORE NULLS选项，当查找到的组内第一个值是NULL时，会继续向后查询，直到查询到一个非NULL值时进行返回；如果一直向后查询到当前组的结尾仍是NULL，则返回NULL。 示例1：不开启IGNORE NULLS，默认不忽略NULL值。 ``` gaussdb=# CREATE TABLE first_value_t1(a int, b int); gaussdb=# INSERT INTO first_value_t1 VALUES(1, NULL),(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,FIRST_VALUE(b) OVER(PARTITION BY a ORDER BY b) FROM first_value_t1; a | b | first_value ---+---+------------- 1 | 1 | 1 1 | 1 | 1 1 | 2 | 1 1 | 3 | 1 1 | | 1 2 | 4 | 4 2 | 5 | 4 3 | 6 | 6 (8 rows) gaussdb=# DROP TABLE first_value_t1; ``` 示例2：开启IGNORE NULLS。 ``` gaussdb=# CREATE TABLE first_value_t1(a int, b int); gaussdb=# INSERT INTO first_value_t1 VALUES(1, NULL),(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,FIRST_VALUE(b) IGNORE NULLS OVER(PARTITION BY a ORDER BY b DESC) FROM first_value_t1; a | b | first_value ---+---+------------- 1 | | 1 | 3 | 3 1 | 2 | 3 1 | 1 | 3 1 | 1 | 3 2 | 5 | 5 2 | 4 | 5 3 | 6 | 6 (8 rows) -- 对比不添加IGNORE NULLS gaussdb=# SELECT a,b,FIRST_VALUE(b) OVER(PARTITION BY a ORDER BY b DESC) FROM first_value_t1; a | b | first_value ---+---+------------- 1 | | 1 | 3 | 1 | 2 | 1 | 1 | 1 | 1 | 2 | 5 | 5 2 | 4 | 5 3 | 6 | 6 (8 rows) gaussdb=# DROP TABLE first_value_t1; ``` #### LAST_VALUE() 描述：LAST_VALUE函数获取各组内的最后一个值作为返回结果。 返回值类型：与参数数据类型相同。 语法： ``` LAST_VALUE(value any) LAST_VALUE(value any IGNORE|RESPECT NULLS) LAST_VALUE(value any) IGNORE|RESPECT NULLS ``` IGNORE\|RESPECT NULLS：表示是否要忽略NULL值。其中RESPECT NULLS是缺省值。若开启IGNORE NULLS选项，当查找到的组内最后一个值是NULL时，会继续向前查询，直到查询到一个非NULL值时进行返回；如果一直向前查询到当前组的开头仍是NULL值，则返回NULL。 示例1：不开启IGNORE NULLS，默认不忽略NULL值。 ``` gaussdb=# CREATE TABLE last_value_t1(a int, b int); gaussdb=# INSERT INTO last_value_t1 VALUES(1, NULL),(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,LAST_VALUE(b) OVER(PARTITION BY a ORDER BY b) FROM last_value_t1; a | b | last_value ---+---+------------ 1 | 1 | 1 1 | 1 | 1 1 | 2 | 2 1 | 3 | 3 1 | | 2 | 4 | 4 2 | 5 | 5 3 | 6 | 6 (8 rows) gaussdb=# DROP TABLE last_value_t1; ``` 示例2：开启IGNORE NULLS。 ``` gaussdb=# CREATE TABLE last_value_t1(a int, b int); gaussdb=# INSERT INTO last_value_t1 VALUES(1, NULL),(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,LAST_VALUE(b) IGNORE NULLS OVER(PARTITION BY a ORDER BY b) FROM last_value_t1; a | b | last_value ---+---+------------ 1 | 1 | 1 1 | 1 | 1 1 | 2 | 2 1 | 3 | 3 1 | | 3 2 | 4 | 4 2 | 5 | 5 3 | 6 | 6 (8 rows) gaussdb=# DROP TABLE last_value_t1; ``` #### DELTA 描述：返回当前行和前一行的差值。 参数：numeric 返回值类型：numeric #### RATIO_TO_REPORT(column_name) 描述：计算某一列的值占其所属分组中所有值总和的比例。 参数：数值类型，或任意可以隐式转换成数值类型的类型。 返回值类型：入参为float4和float8，返回值类型与入参一致；其余入参类型返回numeric类型。 ![](https://support.huaweicloud.com/centralized-devg-v8-gaussdb/public_sys-resources/note_3.0-zh-cn.png) RATIO_TO_REPORT(column_name)与OVER()一起使用时，OVER()中入参只支持PARTITION BY和NULL。 示例1： ``` gaussdb=# CREATE TABLE ratio_to_report_t1(a int, b int); gaussdb=# INSERT INTO ratio_to_report_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,RATIO_TO_REPORT(b) OVER(PARTITION BY a) FROM ratio_to_report_t1; a | b | ratio_to_report ---+---+------------------------ 1 | 1 | .14285714285714285714 1 | 1 | .14285714285714285714 1 | 2 | .28571428571428571429 1 | 3 | .42857142857142857143 2 | 4 | .44444444444444444444 2 | 5 | .55555555555555555556 3 | 6 | 1.00000000000000000000 (7 rows) gaussdb=# DROP TABLE ratio_to_report_t1; ``` 示例2：与其它函数嵌套使用。 ``` gaussdb=# CREATE TABLE ratio_to_report_t1(a int, b int); gaussdb=# INSERT INTO ratio_to_report_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,TO_CHAR(RATIO_TO_REPORT(b) OVER(PARTITION BY a), '$999eeee') FROM ratio_to_report_t1; a | b | to_char ---+---+--------- 1 | 1 | 1e-01 1 | 1 | 1e-01 1 | 2 | 3e-01 1 | 3 | 4e-01 2 | 4 | 4e-01 2 | 5 | 6e-01 3 | 6 | 1e+00 (7 rows) gaussdb=# DROP TABLE ratio_to_report_t1; ``` 示例3：存储过程调用。 ``` gaussdb=# CREATE TABLE ratio_to_report_t1(a int, b int); gaussdb=# INSERT INTO ratio_to_report_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# CREATE OR REPLACE PROCEDURE ratio_to_report_proc IS CURSOR cur_1 IS SELECT a,b,RATIO_TO_REPORT(b) OVER(PARTITION BY a) FROM ratio_to_report_t1; BEGIN FOR cur IN cur_1 LOOP RAISE INFO '%', cur.ratio_to_report; END LOOP; END; / gaussdb=# CALL RATIO_TO_REPORT_PROC(); INFO: .14285714285714285714 INFO: .14285714285714285714 INFO: .28571428571428571429 INFO: .42857142857142857143 INFO: .44444444444444444444 INFO: .55555555555555555556 INFO: 1.00000000000000000000 ratio_to_report_proc ---------------------- (1 row) gaussdb=# DROP PROCEDURE ratio_to_report_proc; gaussdb=# DROP TABLE ratio_to_report_t1; ``` #### NTH_VALUE() 描述：NTH_VALUE函数返回该组内的第nth行作为结果。若该行不存在，则默认返回NULL。 返回值类型：与参数数据类型相同。 语法： ``` NTH_VALUE(value any, nth integer) NTH_VALUE(value any, nth integer) IGNORE|RESPECT NULLS ``` IGNORE\|RESPECT NULLS：表示是否要忽略NULL值。其中RESPECT NULLS是缺省值。若开启IGNORE NULLS选项，会在每个组从前往后查找非NULL值，直到查询第nth个非NULL值时进行返回；如果查找到当前组的结尾都没有nth个非NULL值，则返回NULL。 示例1：不开启IGNORE NULLS，默认不忽略NULL值。 ``` gaussdb=# CREATE TABLE nth_value_t1(a int, b int); gaussdb=# INSERT INTO nth_value_t1 VALUES(1, NULL),(1, NULL),(1, NULL),(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,NTH_VALUE(b, 2) OVER(PARTITION BY a ORDER BY b) FROM nth_value_t1; a | b | nth_value ---+---+----------- 1 | 1 | 1 1 | 1 | 1 1 | 2 | 1 1 | 3 | 1 1 | | 1 1 | | 1 1 | | 1 2 | 4 | 2 | 5 | 5 3 | 6 | (10 rows) gaussdb=# DROP TABLE nth_value_t1; ``` 示例2：开启IGNORE NULLS。 ``` gaussdb=# CREATE TABLE nth_value_t1(a int, b int); gaussdb=# INSERT INTO nth_value_t1 VALUES(1, NULL),(1, NULL),(1, NULL),(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6); gaussdb=# SELECT a,b,NTH_VALUE(b, 2) IGNORE NULLS OVER(PARTITION BY a ORDER BY b DESC) FROM nth_value_t1; a | b | nth_value ---+---+----------- 1 | | 1 | | 1 | | 1 | 3 | 1 | 2 | 2 1 | 1 | 2 1 | 1 | 2 2 | 5 | 2 | 4 | 4 3 | 6 | (10 rows) -- 对比不加IGNORE NULLS gaussdb=# SELECT a,b,NTH_VALUE(b, 2) OVER(PARTITION BY a ORDER BY b DESC) FROM nth_value_t1; a | b | nth_value ---+---+----------- 1 | | 1 | | 1 | | 1 | 3 | 1 | 2 | 1 | 1 | 1 | 1 | 2 | 5 | 2 | 4 | 4 3 | 6 | (10 rows) gaussdb=# DROP TABLE nth_value_t1; ``` #### KEEP( DENSE_RANK { FIRST \| LAST } ORDER BY expr) 描述：将查询结果的数据行按指定规则进行排序，返回第一组或者最后一组的值，可用于聚集函数或窗口函数。 语法： ``` aggregate_function KEEP ( DENSE_RANK { FIRST | LAST } ORDER BY expr [ DESC | ASC ] [ NULLS { FIRST | LAST } ] [, expr [ DESC | ASC ] [ NULLS { FIRST | LAST } ]]...) OVER ( [query_partition_clause] ) ] ``` 返回值类型：在aggregate_function中指定列的数据类型。 示例： ``` gaussdb=# CREATE TABLE keep_t1(a int, b int, c int, d int); gaussdb=# INSERT INTO keep_t1 values(2, 111, 333, 10), (2, 11, 33, 10), (2, 11, 3, 1), (1, 22, 55, 10), (1, 2, 5, 100); gaussdb=# SELECT MIN(d) KEEP(DENSE_RANK FIRST ORDER BY b) OVER (PARTITION BY a) MIN_FIRST, MIN(b) KEEP(DENSE_RANK LAST ORDER BY b) OVER (PARTITION BY a) MIN_LAST, MAX(b) KEEP(DENSE_RANK FIRST ORDER BY b) OVER (PARTITION BY a) MAX_FIRST, MAX(b) KEEP(DENSE_RANK LAST ORDER BY b) OVER (PARTITION BY a) MAX_LAST FROM keep_t1; min_first | min_last | max_first | max_last -----------+----------+-----------+---------- 100 | 22 | 2 | 22 100 | 22 | 2 | 22 1 | 111 | 11 | 111 1 | 111 | 11 | 111 1 | 111 | 11 | 111 (5 rows) gaussdb=# DROP TABLE keep_t1; ```