postgresql如何找到表中重复数据的行并删除

postgresql删除重复数据删除表重复数据行 postgresql重复数据删除 2023-05-05 16:05:18 123人浏览独家记忆

摘要

目录postgresql找到表中重复数据的行并删除创建测试表并插入数据找到重复行并删除postgresql常用的删除重复数据方法最高效方法PG中三种删除重复数据方法总结postgresql找到表中重复数据的行并删除创建

postgresql找到表中重复数据的行并删除

创建测试表并插入数据

create table aaa(id bigserial,col1 varchar(255));

insert into aaa values(1,'b'),(2,'a'),(3,'b'),(4,'c');

select * from aaa;

找到重复行并删除

方法1：ctid表示数据行在它所处的表内的物理位置，ctid由两个数字组成，第一个数字表示物理块号，第二个数字表示在物理块中的行号。

select * from aaa where ctid not in(select max(ctid) from aaa group by col1);

删除重复行

delete from aaa where ctid not in(select max(ctid) from aaa group by col1);

方法2：利用exists

找到重复行

select * from aaa t1 where  exists (select 1 from aaa t2 where t1.col1=t2.col1 and t1.id<t2.id )----exists后的意思是同一列相等，但是自增id不相等且id小的那一个

删除重复行

delete from aaa t1 where  exists (select 1 from aaa t2 where t1.col1=t2.col1 and t1.id<t2.id )

postgresql常用的删除重复数据方法

最高效方法

测试环境验证，6600万行大表，删除2200万重复数据仅需3分钟

delete from deltest a where a.ctid = any(array (select ctid from (select row_number() over (partition by id), ctid from deltest) t where t.row_number > 1));

PG中三种删除重复数据方法

首先创建一张基础表，并插入一定量的重复数据。

create table deltest(id int, name varchar(255));
create table deltest_bk (like deltest);
insert into deltest select generate_series(1, 10000), 'ZhangSan';
insert into deltest select generate_series(1, 10000), 'ZhangSan';
insert into deltest_bk select * from deltest;

1. 常规删除方法

最容易想到的方法就是判断数据是否重复，对于重复的数据只保留ctid最小（或最大）的数据，删除其他的。

explain analyse delete from deltest a where a.ctid <> (select min(t.ctid) from deltest t where a.id=t.id);
-------------------------------------------------------------------------------------------
  Delete on deltest a (cost=0.00..195616.30 rows=1518 width=6) (actual time=67758.866..67758.866 rows=0 loops=1)
   -> Seq Scan on deltest a (cost=0.00..195616.30 rows=1518 width=6) (actual time=32896.517..67663.228 rows=10000 loops=1)
    Filter: (ctid <> (SubPlan 1))
    Rows Removed by Filter: 10000
    SubPlan 1
     -> Aggregate (cost=128.10..128.10 rows=1 width=6) (actual time=3.374..3.374 rows=1 loops=20000)
        -> Seq Scan on deltest t (cost=0.00..128.07 rows=8 width=6) (actual time=0.831..3.344 rows=2 loops=20000)
           Filter: (a.id = id)
           Rows Removed by Filter: 19998
Total runtime: 67758.931 ms
select count(*) from deltest;
count
-------
10000

可以看到，id相同的数据，保留ctid最小的，其他的删除。相当于把deltest表中的数据删掉一半，耗时达到67s多。相当慢。

2. group by删除方法

group by方法通过分组找到ctid最小的数据，然后删除其他数据。

explain analyse delete from deltest a where a.ctid not in (select min(ctid) from deltest group by id);
-------------------------------------------------------------------------------------------
  Delete on deltest a (cost=131.89..2930.46 rows=763 width=6) (actual time=30942.496..30942.496 rows=0 loops=1)
   -> Seq Scan on deltest a (cost=131.89..2930.46 rows=763 width=6) (actual time=10186.296..30814.366 rows=10000 loops=1)
    Filter: (NOT (SubPlan 1))
    Rows Removed by Filter: 10000
    SubPlan 1
     -> Materialize (cost=131.89..134.89 rows=200 width=10) (actual time=0.001..0.471 rows=7500 loops=20000)
        -> HashAggregate (cost=131.89..133.89 rows=200 width=10) (actual time=10.568..13.584 rows=10000 loops=1)
           -> Seq Scan on deltest (cost=0.00..124.26 rows=1526 width=10) (actual time=0.006..3.829 rows=20000 loops=1)
  Total runtime: 30942.819 ms
select count(*) from deltest;
count
-------
10000

可以看到同样是删除一半的数据，使用group by的方式，时间节省了一半。但仍含需要30s，下面试一下第三种删除操作。

3. 高效删除方法

explain analyze delete from deltest a where a.ctid = any(array (select ctid from (select row_number() over (partition by id), ctid from deltest) t where t.row_number > 1));
-----------------------------------------------------------------------------------------
  Delete on deltest a (cost=250.74..270.84 rows=10 width=6) (actual time=98.363..98.363 rows=0 loops=1)
  InitPlan 1 (returns 0)−>SubqueryScanont(cost=204.95..250.73rows=509width=6)(actualtime=29.446..47.867rows=10000loops=1)Filter:(t.rownumber>1)RowsRemovedbyFilter:10000−>WindowAgg(cost=204.95..231.66rows=1526width=10)(actualtime=29.436..44.790rows=20000loops=1)−>Sort(cost=204.95..208.77rows=1526width=10)(actualtime=12.466..13.754rows=20000loops=1)SorTKEy:deltest.idSortMethod:quicksortMemory:1294kB−>SeqScanondeltest(cost=0.00..124.26rows=1526width=10)(actualtime=0.021..5.110rows=20000loops=1)−>TidScanondeltesta(cost=0.01..20.11rows=10width=6)(actualtime=82.983..88.751rows=10000loops=1)TIDCond:(ctid=ANY(0)−>SubqueryScanont(cost=204.95..250.73rows=509width=6)(actualtime=29.446..47.867rows=10000loops=1)Filter:(t.rownumber>1)RowsRemovedbyFilter:10000−>WindowAgg(cost=204.95..231.66rows=1526width=10)(actualtime=29.436..44.790rows=20000loops=1)−>Sort(cost=204.95..208.77rows=1526width=10)(actualtime=12.466..13.754rows=20000loops=1)SortKey:deltest.idSortMethod:quicksortMemory:1294kB−>SeqScanondeltest(cost=0.00..124.26rows=1526width=10)(actualtime=0.021..5.110rows=20000loops=1)−>TidScanondeltesta(cost=0.01..20.11rows=10width=6)(actualtime=82.983..88.751rows=10000loops=1)TIDCond:(ctid=ANY(0))
  Total runtime: 98.912 ms
select count(*) from deltest;
count
-------
10000

可以看到，居然只要98ms