使用顺序扫描而不是索引扫描的SELECT

Question

我正在尝试使用explain analyze优化我的一些选择,我无法理解为什么postgresql使用序列扫描而不是索引扫描:

explain analyze SELECT SUM(a.deure)-SUM(a.haver) as Value FROM assentaments a
LEFT JOIN comptes c ON a.compte_id = c.id WHERE c.empresa_id=2 AND c.nivell=11 AND
(a.data >='2007-01-01' AND a.data <='2007-01-31')  AND c.codi_compte LIKE '6%';


------------------------------------------------------------------------------------------------------------------------------------------------
Aggregate  (cost=44250.26..44250.27 rows=1 width=12)
(actual time=334.054..334.054 rows=1 loops=1)
  ->  Nested Loop  (cost=0.00..44249.20 rows=211 width=12)
      (actual time=65.277..333.179 rows=713 loops=1)
    ->  Seq Scan on comptes c  (cost=0.00..8001.72 rows=118 width=4)
        (actual time=0.053..64.287 rows=236 loops=1)
        Filter: (((codi_compte)::text ~~ '6%'::text) AND
        (empresa_id = 2) AND (nivell = 11))
      ->  Index Scan using index_compte_id on assentaments a
          (cost=0.00..307.16 rows=2 width=16) (actual time=0.457..1.138 rows=3 loops=236)
           Index Cond: (a.compte_id = c.id)
           Filter: ((a.data >= '2007-01-01'::date) AND (a.data <= '2007-01-31'::date))

  Total runtime: 334.104 ms
  (8 rows)

我创建了一个自定义索引:

CREATE INDEX "index_multiple" ON "public"."comptes" USING btree(codi_compte ASC NULLS LAST,
empresa_id ASC NULLS LAST, nivell ASC NULLS LAST);

而且我在comptes表上为这三个字段创建了三个新索引,只是为了检查它是否需要索引扫描,但不是,结果是相同的:

CREATE INDEX "index_codi_compte" ON "public"."comptes" USING btree(codi_compte ASC NULLS LAST);
CREATE INDEX "index_comptes" ON "public"."comptes" USING btree(codi_compte ASC NULLS LAST);
CREATE INDEX "index_multiple" ON "public"."comptes" USING btree(codi_compte ASC NULLS LAST,     empresa_id ASC NULLS LAST, nivell ASC NULLS LAST);
CREATE INDEX "index_nivell" ON "public"."comptes" USING btree(nivell ASC NULLS LAST);

谢谢!

米

编辑:

assentaments.id和assentaments.data也有他们的索引

select count(*) FROM comptes => 148498
select count(*) from assentaments => 2128771

select count(distinct(codi_compte)) FROM comptes => 137008
select count(distinct(codi_compte)) FROM comptes WHERE codi_compte LIKE '6%' => 368
select count(distinct(codi_compte)) FROM comptes WHERE codi_compte LIKE '6%' AND empresa_id=2; => 303

Answer 1

如果您希望TEXT上的索引索引LIKE查询,则需要使用text_pattern_ops创建它,如下所示:

test=> CREATE TABLE t AS SELECT n::TEXT FROM generate_series( 1,100000 ) n;
test=> CREATE INDEX tn ON t(n);
test=> VACUUM ANALYZE t;
test=> EXPLAIN ANALYZE SELECT * FROM t WHERE n LIKE '123%';
                                            QUERY PLAN                                            
--------------------------------------------------------------------------------------------------
 Seq Scan on t  (cost=0.00..1693.00 rows=10 width=5) (actual time=0.027..14.631 rows=111 loops=1)
   Filter: (n ~~ '123%'::text)
 Total runtime: 14.664 ms

test=> CREATE INDEX tn2 ON t(n text_pattern_ops);
CREATE INDEX
Temps : 267,589 ms
test=> EXPLAIN ANALYZE SELECT * FROM t WHERE n LIKE '123%';
                                                  QUERY PLAN                                                   
---------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on t  (cost=5.25..244.79 rows=10 width=5) (actual time=0.089..0.121 rows=111 loops=1)
   Filter: (n ~~ '123%'::text)
   ->  Bitmap Index Scan on tn2  (cost=0.00..5.25 rows=99 width=0) (actual time=0.077..0.077 rows=111 loops=1)
         Index Cond: ((n ~>=~ '123'::text) AND (n ~<~ '124'::text))
 Total runtime: 0.158 ms

看这里的细节:

http://www.postgresql.org/docs/9.1/static/indexes-opclass.html

如果不希望创建一个附加的索引和列是文本,则可以通过将"孔特LIKE'6%’""孔特> ='6’和孔特<'7’",这是一个简单的索引范围条件.

test=> EXPLAIN ANALYZE SELECT * FROM t WHERE n >= '123' AND n < '124';
                                                QUERY PLAN                                                 
-----------------------------------------------------------------------------------------------------------
 Index Scan using tn on t  (cost=0.00..126.74 rows=99 width=5) (actual time=0.030..0.127 rows=111 loops=1)
   Index Cond: ((n >= '123'::text) AND (n < '124'::text))
 Total runtime: 0.153 ms

在你的情况下,这个解决方案可能更好.