PostgreSQL:快速检查LTREE []< @LTREE []的所有元素

时间:2018-03-26 06:26:25

标签: postgresql query-optimization ltree

我有以下表格(简化):

CREATE TABLE groups
 ( id PRIMARY KEY, 
   path ltree,
   ... 
 );

CREATE TABLE items
 ( id bigserial, 
   path ltree,
   ... 
   PRIMARY KEY (id, path)
 );

对于每个项目,还有项目所属的组列表。一个组由其完整路径表示。可能有多达10M项目,每个项目属于约20个组。

我需要设计以下查询。给定(a)“父”组和(b)最多10个附加组的列表,找到“父”组的直接后代,其子树中至少有一个项目包含在每个组中。搜索条件。

例如,给定父组“NorthAmerica.USA”和其他组[“CandyLovers.ChocolateLovers”,“Athletes.Footballers”],那么“NorthAmerica.USA.CA”是一个结果,如果它存在像“乔治”就像[“NorthAmerica.USA.CA.LosAngeles”,“Athletes.Footballers”,“CandyLovers.ChocolateLovers.ChocolateDonutLovers”]

我尝试了几种不同的方式来编写查询,并且它们扩展得非常差:花几分钟时间将结果返回到一组1M项目和搜索条件中的3-4条路径。例如:

    EXPLAIN ANALYZE
    SELECT *
    FROM groups
    WHERE path ~ CAST ('1.2.22' || '.*{1}' AS lquery)
          AND EXISTS
          (SELECT 1
           FROM
             (SELECT array_agg(DISTINCT leaf_paths_sans_result_path.path) AS paths_of_a_match,
                     max(path_count) AS path_count
              FROM items,

                (SELECT path,
                   count(*) OVER() AS path_count
                 FROM (
                        VALUES (groups.path) , ('1.3'),('1.4')) t (path)) leaf_paths_sans_result_path
              WHERE 1 = 1
                    AND items.path <@ leaf_paths_sans_result_path.path
              GROUP BY id) items_by_id
           WHERE cardinality(paths_of_a_match) = path_count );

结果如下:

     Index Scan using idx_groups__path__gist on groups  (cost=0.28..37013.74 rows=38 width=469) (actual time=11.735..322285.421 rows=950 loops=1)
       Index Cond: (path ~ '1.2.22.*{1}'::lquery)
       Filter: (SubPlan 1)
       Rows Removed by Filter: 3
       SubPlan 1
         ->  Subquery Scan on items_by_id  (cost=0.55..1809359.86 rows=3752 width=0) (actual time=338.162..338.162 rows=1 loops=953)
               ->  GroupAggregate  (cost=0.55..1809322.34 rows=3752 width=65) (actual time=338.159..338.159 rows=1 loops=953)
                     Group Key: ibt.id
                     Filter: (cardinality(array_agg(DISTINCT "*VALUES*".column1)) >= max(3))
                     Rows Removed by Filter: 7845
                     ->  Nested Loop  (cost=0.55..1809228.54 rows=3752 width=65) (actual time=0.044..307.087 rows=20423 loops=953)
                           Join Filter: (ibt.path <@ "*VALUES*".column1)
                           Rows Removed by Join Filter: 651228
                           ->  Index Scan using idx_items__id on items  (cost=0.55..1752954.06 rows=1250543 width=193) (actual time=0.007..110.517 rows=223884 loops=953)
                           ->  Materialize  (cost=0.00..0.05 rows=3 width=32) (actual time=0.000..0.000 rows=3 loops=213361141)
                                 ->  Values Scan on "*VALUES*"  (cost=0.00..0.04 rows=3 width=32) (actual time=0.002..0.003 rows=3 loops=953)
     Planning time: 3.151 ms
     Execution time: 322286.404 ms
    (18 rows)

我可以根据需要更改数据模型,以便针对此查询进行优化。我正在运行PostgreSQL v9.5

非常感谢!对不起一个混乱的问题。

1 个答案:

答案 0 :(得分:0)

看起来你正在使用ltree module?以下查询避免使用中间array_agg数组:

select  *
from    items i
join    groups g
on      i.groups = g.id
where   g.path ~ '1.2.22.*' and
        (
             i.path ~ '*.1.3.*' or
             i.path ~ '*.1.4.*'
        )
group by
        g.id
having  count(distinct
        case
        when i.path ~ '*.1.3.*' then 1
        when i.path ~ '*.1.4.*' then 2
        end) = 2

count构造断言满足两个条件,而不仅仅是两个匹配相同模式的行。