使用CTE。这个想法是连接一个或多个列，形成一个重复的记录，然后删除你喜欢的:

;with cte as (
    select 
        min(PrimaryKey) as PrimaryKey
        UniqueColumn1,
        UniqueColumn2
    from dbo.DuplicatesTable 
    group by
        UniqueColumn1, UniqueColumn1
    having count(*) > 1
)
delete d
from dbo.DuplicatesTable d 
inner join cte on 
    d.PrimaryKey > cte.PrimaryKey and
    d.UniqueColumn1 = cte.UniqueColumn1 and 
    d.UniqueColumn2 = cte.UniqueColumn2;

SELECT  DISTINCT *
      INTO tempdb.dbo.tmpTable
FROM myTable

TRUNCATE TABLE myTable
INSERT INTO myTable SELECT * FROM tempdb.dbo.tmpTable
DROP TABLE tempdb.dbo.tmpTable

这个查询为我展示了非常好的性能:

DELETE tbl
FROM
    MyTable tbl
WHERE
    EXISTS (
        SELECT
            *
        FROM
            MyTable tbl2
        WHERE
            tbl2.SameValue = tbl.SameValue
        AND tbl.IdUniqueValue < tbl2.IdUniqueValue
    )

它在30秒多一点的时间内从2M的表中删除了1M行(50%重复)

下面的查询用于删除重复的行。本例中的表以ID作为标识列，具有重复数据的列是Column1、Column2和Column3。

DELETE FROM TableName
WHERE  ID NOT IN (SELECT MAX(ID)
                  FROM   TableName
                  GROUP  BY Column1,
                            Column2,
                            Column3
                  /*Even if ID is not null-able SQL Server treats MAX(ID) as potentially
                    nullable. Because of semantics of NOT IN (NULL) including the clause
                    below can simplify the plan*/
                  HAVING MAX(ID) IS NOT NULL) 

下面的脚本显示GROUP BY、HAVING、ORDER BY在一个查询中的用法，并返回带有重复列及其计数的结果。

SELECT YourColumnName,
       COUNT(*) TotalCount
FROM   YourTableName
GROUP  BY YourColumnName
HAVING COUNT(*) > 1
ORDER  BY COUNT(*) DESC 

对于表结构

MyTable

RowID int not null identity(1,1) primary key,
Col1 varchar(20) not null,
Col2 varchar(2048) not null,
Col3 tinyint not null

删除重复项的查询:

DELETE t1
FROM MyTable t1
INNER JOIN MyTable t2
WHERE t1.RowID > t2.RowID
  AND t1.Col1 = t2.Col1
  AND t1.Col2=t2.Col2
  AND t1.Col3=t2.Col3;

我假设RowID是一种自动递增，其余列有重复的值。

在postgresql中删除重复行的一个非常简单的方法。

DELETE FROM table1 a
USING table1 b
WHERE a.id < b.id
AND a.column1 = b.column1
AND a.column2 = b.column2;