有个开发写了不带参数的OVER()分析函数，类似如下：
SELECT categories_products.category_id,
COUNT(*) OVER() AS all_products
FROM categories_products;
经查，其用途相当于不带GROUP BY子句的聚合操作，只不过所有行都包含该结果。分析函数本质性就像标量列的行为一样，可以和聚合函数一起使用。
SELECT DISTINCT
categories.category_id,
categories.name,
COUNT(categories_products.product_id) OVER(PARTITION BY categories_products.category_id) AS products,
COUNT(categories_products.product_id) OVER() AS all_products
FROM categories
INNER JOIN categories_products
ON categories.category_id = categories_products.category_id
就带PARTITION BY子句的分析函数而言，其性能通常远比单独计算好。那不带选项的OVER()呢？
findptdis=# explain analyze select sjno_id,count(1) over() from sjno_local1;
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------
WindowAgg (cost=0.00..142400.00 rows=640000 width=32) (actual time=779.573..995.977 rows=2560000 loops=1)
-> Seq Scan on sjno_local1 (cost=0.00..134400.00 rows=640000 width=24) (actual time=0.009..359.622 rows=2560000 loops=1)
Planning Time: 0.047 ms
Execution Time: 1055.498 ms
(4 rows)
findptdis=# explain analyze select sjno_id,x from sjno_local1,(select count(1) x from sjno_local1) f;
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=136000.00..276800.02 rows=640000 width=32) (actual time=376.336..833.559 rows=2560000 loops=1)
-> Aggregate (cost=136000.00..136000.01 rows=1 width=8) (actual time=376.325..376.327 rows=1 loops=1)
-> Seq Scan on sjno_local1 sjno_local1_1 (cost=0.00..134400.00 rows=640000 width=0) (actual time=0.006..302.627 rows=2560000 loops=1)
-> Seq Scan on sjno_local1 (cost=0.00..134400.00 rows=640000 width=24) (actual time=0.007..300.224 rows=2560000 loops=1)
Planning Time: 0.105 ms
Execution Time: 879.682 ms
(6 rows)
