在某些场景可能会需要随机的从表中取出记录。方法比较多，简单的方法可能给数据库带来巨大的开销，下面开始举例说明，看看如何优化一个随机查询。 测试表: create table tbl_user(id serial8 primary key,firstname varchar(32),lastname varchar(32),corp varchar(32),age smallint); ID列被作为优化随机查询的选择列.唯一，有索引，非空是比较好的选择. 测试记录: insert into tbl_user select generate_series(1,999999),'zhou','digoal','sky-mobi',27; 随机查询方法举例: 方法 1. 最简单的随机查询，查询出1条记录。 digoal=> select * from tbl_user order by random() limit 1; id | firstname | lastname | corp | age --------+-----------+----------+----------+----- 809085 | zhou | digoal | sky-mobi | 27 (1 row) Time: 411.856 ms 执行计划: digoal=> explain select * from tbl_user order by random() limit 1; QUERY PLAN ------------------------------------------------------------------------------ Limit (cost=24852.98..24852.99 rows=1 width=31) -> Sort (cost=24852.98..27352.98 rows=999999 width=31) Sort Key: (random()) -> Seq Scan on tbl_user (cost=0.00..19852.99 rows=999999 width=31) (4 rows) 简单是简单，缺点也很明显，这种随机查询在大表上跑数据库肯定是吃不消的。 以下列举利用索引列进行优化的方法。 方法 2. 随机取出n条记录,以下取出5条随机记录 digoal=> select * from tbl_user digoal-> where id in digoal-> (select floor(random() * (max_id - min_id))::int digoal(> + min_id digoal(> from generate_series(1,5),digoal(> (select max(id) as max_id,digoal(> min(id) as min_id digoal(> from tbl_user) s1 digoal(> ) digoal-> limit 5; id | firstname | lastname | corp | age --------+-----------+----------+----------+----- 965638 | zhou | digoal | sky-mobi | 27 193491 | zhou | digoal | sky-mobi | 27 294286 | zhou | digoal | sky-mobi | 27 726263 | zhou | digoal | sky-mobi | 27 470713 | zhou | digoal | sky-mobi | 27 (5 rows) Time: 0.670 ms 执行计划: digoal=> explain select * from tbl_user digoal-> where id in digoal-> (select floor(random() * (max_id - min_id))::int digoal(> + min_id digoal(> from generate_series(1,digoal(> min(id) as min_id digoal(> from tbl_user) s1 digoal(> ) digoal-> limit 5; QUERY PLAN ------------------------------------------------------------------------------------------------------------------------------------ -- Limit (cost=50.08..69.63 rows=5 width=31) -> Nested Loop (cost=50.08..832.26 rows=200 width=31) -> HashAggregate (cost=50.08..52.08 rows=200 width=8) -> Nested Loop (cost=0.06..37.58 rows=1000 width=16) -> Result (cost=0.06..0.07 rows=1 width=0) InitPlan 1 (returns $0) -> Limit (cost=0.00..0.03 rows=1 width=8) -> Index Scan Backward using tbl_user_pkey on tbl_user (cost=0.00..27844.29 rows=999999 width=8 ) Index Cond: (id IS NOT NULL) InitPlan 2 (returns $1) -> Limit (cost=0.00..0.03 rows=1 width=8) -> Index Scan using tbl_user_pkey on tbl_user (cost=0.00..27844.29 rows=999999 width=8) Index Cond: (id IS NOT NULL) -> Function Scan on generate_series (cost=0.00..10.00 rows=1000 width=0) -> Index Scan using tbl_user_pkey on tbl_user (cost=0.00..3.89 rows=1 width=31) Index Cond: (digoal.tbl_user.id = (((floor((random() * ((($0) - ($1)))::double precision)))::integer + ($1)))) (16 rows) 方法 3. 取出N条连续的随机记录.(此处用到函数) digoal=> create or replace function f_get_random (i_range int) returns setof record as $BODY$ digoal$> declare digoal$> v_result record; digoal$> v_max_id int; digoal$> v_min_id int; digoal$> v_random numeric; digoal$> begin digoal$> select random() into v_random; digoal$> select max(id),min(id) into v_max_id,v_min_id from tbl_user; digoal$> for v_result in select * from tbl_user where id between (v_min_id+(v_random*(v_max_id-v_min_id))::int) and (v_min_id+(v_random*(v_max_id-v_min_id))::int+i_range) digoal$> loop digoal$> return next v_result; digoal$> end loop; digoal$> return; digoal$> end digoal$> $BODY$ language plpgsql; CREATE FUNCTION 以下举例取出10条连续的随机记录 digoal=> select * from f_get_random(9) as (id bigint,age smallint); id | firstname | lastname | corp | age --------+-----------+----------+----------+----- 694686 | zhou | digoal | sky-mobi | 27 694687 | zhou | digoal | sky-mobi | 27 694688 | zhou | digoal | sky-mobi | 27 694689 | zhou | digoal | sky-mobi | 27 694690 | zhou | digoal | sky-mobi | 27 694691 | zhou | digoal | sky-mobi | 27 694692 | zhou | digoal | sky-mobi | 27 694693 | zhou | digoal | sky-mobi | 27 694694 | zhou | digoal | sky-mobi | 27 694695 | zhou | digoal | sky-mobi | 27 (10 rows) Time: 0.418 ms 执行计划: digoal=> explain select * from tbl_user where id between 694686 and 694695; QUERY PLAN ------------------------------------------------------------------------------- Index Scan using tbl_user_pkey on tbl_user (cost=0.00..4.48 rows=9 width=31) Index Cond: ((id >= 694686) AND (id <= 694695)) (2 rows) digoal=> explain select max(id),min(id) from tbl_user; QUERY PLAN -------------------------------------------------------------------------------------------------------------- Result (cost=0.06..0.07 rows=1 width=0) InitPlan 1 (returns $0) -> Limit (cost=0.00..0.03 rows=1 width=8) -> Index Scan Backward using tbl_user_pkey on tbl_user (cost=0.00..27844.29 rows=999999 width=8) Index Cond: (id IS NOT NULL) InitPlan 2 (returns $1) -> Limit (cost=0.00..0.03 rows=1 width=8) -> Index Scan using tbl_user_pkey on tbl_user (cost=0.00..27844.29 rows=999999 width=8) Index Cond: (id IS NOT NULL) (9 rows) 其他的方法不再一一列举，方法2和方法3可以满足大多数的需求了。开销和运行时间均比方法1下降1000倍以上. 注意事项: 1. 索引列的类型和查询条件的类型必须匹配. 2. random() 取值范围 0.0 到 1.0 3. id between x and y 的写法等同于 id>= x and id<=y . id BETWEEN SYMMETRIC x and y 的写法等同于 (id >= x and id <= y) or (id >= y and id <= x) 因此两者的执行计划是完全不一样的,如下: digoal=> explain select * from tbl_user where id BETWEEN SYMMETRIC 3 and 2; QUERY PLAN ---------------------------------------------------------------------------------- Bitmap Heap Scan on tbl_user (cost=4.63..6.65 rows=1 width=31) Recheck Cond: (((id >= 3) AND (id <= 2)) OR ((id >= 2) AND (id <= 3))) -> BitmapOr (cost=4.63..4.63 rows=1 width=0) -> Bitmap Index Scan on tbl_user_pkey (cost=0.00..2.31 rows=1 width=0) Index Cond: ((id >= 3) AND (id <= 2)) -> Bitmap Index Scan on tbl_user_pkey (cost=0.00..2.31 rows=1 width=0) Index Cond: ((id >= 2) AND (id <= 3)) (7 rows) digoal=> explain select * from tbl_user where id BETWEEN 2 and 3; QUERY PLAN ------------------------------------------------------------------------------- Index Scan using tbl_user_pkey on tbl_user (cost=0.00..4.32 rows=1 width=31) Index Cond: ((id >= 2) AND (id <= 3)) (2 rows)