使用一个字段很容易找到重复项:

SELECT email, COUNT(email) 
FROM users
GROUP BY email
HAVING COUNT(email) > 1

所以如果我们有一张桌子

ID   NAME   EMAIL
1    John   asd@asd.com
2    Sam    asd@asd.com
3    Tom    asd@asd.com
4    Bob    bob@asd.com
5    Tom    asd@asd.com

这个查询将告诉我们John、Sam、Tom和Tom,因为他们都有相同的电子邮件。

然而,我想要的是获得相同电子邮件和名称的副本。

也就是说,我想得到“汤姆”,“汤姆”。

我需要这个的原因是:我犯了一个错误,允许插入重复的名称和电子邮件值。现在我需要删除/更改重复项,所以我需要先找到它们。


当前回答

试试看:

declare @YourTable table (id int, name varchar(10), email varchar(50))

INSERT @YourTable VALUES (1,'John','John-email')
INSERT @YourTable VALUES (2,'John','John-email')
INSERT @YourTable VALUES (3,'fred','John-email')
INSERT @YourTable VALUES (4,'fred','fred-email')
INSERT @YourTable VALUES (5,'sam','sam-email')
INSERT @YourTable VALUES (6,'sam','sam-email')

SELECT
    name,email, COUNT(*) AS CountOf
    FROM @YourTable
    GROUP BY name,email
    HAVING COUNT(*)>1

输出:

name       email       CountOf
---------- ----------- -----------
John       John-email  2
sam        sam-email   2

(2 row(s) affected)

如果您想要重复数据集的ID,请使用以下命令:

SELECT
    y.id,y.name,y.email
    FROM @YourTable y
        INNER JOIN (SELECT
                        name,email, COUNT(*) AS CountOf
                        FROM @YourTable
                        GROUP BY name,email
                        HAVING COUNT(*)>1
                    ) dt ON y.name=dt.name AND y.email=dt.email

输出:

id          name       email
----------- ---------- ------------
1           John       John-email
2           John       John-email
5           sam        sam-email
6           sam        sam-email

(4 row(s) affected)

要删除重复项,请尝试:

DELETE d
    FROM @YourTable d
        INNER JOIN (SELECT
                        y.id,y.name,y.email,ROW_NUMBER() OVER(PARTITION BY y.name,y.email ORDER BY y.name,y.email,y.id) AS RowRank
                        FROM @YourTable y
                            INNER JOIN (SELECT
                                            name,email, COUNT(*) AS CountOf
                                            FROM @YourTable
                                            GROUP BY name,email
                                            HAVING COUNT(*)>1
                                        ) dt ON y.name=dt.name AND y.email=dt.email
                   ) dt2 ON d.id=dt2.id
        WHERE dt2.RowRank!=1
SELECT * FROM @YourTable

输出:

id          name       email
----------- ---------- --------------
1           John       John-email
3           fred       John-email
4           fred       fred-email
5           sam        sam-email

(4 row(s) affected)

其他回答

删除名称重复的记录

;WITH CTE AS    
(

    SELECT ROW_NUMBER() OVER (PARTITION BY name ORDER BY name) AS T FROM     @YourTable    
)

DELETE FROM CTE WHERE T > 1

我们可以在这里使用have,它处理聚合函数,如下所示

create table #TableB (id_account int, data int, [date] date)
insert into #TableB values (1 ,-50, '10/20/2018'),
(1, 20, '10/09/2018'),
(2 ,-900, '10/01/2018'),
(1 ,20, '09/25/2018'),
(1 ,-100, '08/01/2018')  

SELECT id_account , data, COUNT(*)
FROM #TableB
GROUP BY id_account , data
HAVING COUNT(id_account) > 1

drop table #TableB

这里有两个字段id_account和data与Count(*)一起使用。因此,它将给出两列中值超过一倍的所有记录。

由于某种原因,我们错误地错过了在SQL server表中添加任何约束,并且记录已在前端应用程序的所有列中重复插入。然后我们可以使用下面的查询从表中删除重复的查询。

SELECT DISTINCT * INTO #TemNewTable FROM #OriginalTable
TRUNCATE TABLE #OriginalTable
INSERT INTO #OriginalTable SELECT * FROM #TemNewTable
DROP TABLE #TemNewTable

在这里,我们获取了原始表的所有不同记录,并删除了原始表中的记录。我们再次将新表中的所有不同值插入到原始表中,然后删除新表。

请尝试

SELECT UserID, COUNT(UserID) 
FROM dbo.User
GROUP BY UserID
HAVING COUNT(UserID) > 1

如果要查找重复的数据(通过一个或多个标准),请选择实际的行。

with MYCTE as (
    SELECT DuplicateKey1
        ,DuplicateKey2 --optional
        ,count(*) X
    FROM MyTable
    group by DuplicateKey1, DuplicateKey2
    having count(*) > 1
) 
SELECT E.*
FROM MyTable E
JOIN MYCTE cte
ON E.DuplicateKey1=cte.DuplicateKey1
    AND E.DuplicateKey2=cte.DuplicateKey2
ORDER BY E.DuplicateKey1, E.DuplicateKey2, CreatedAt

http://developer.azurewebsites.net/2014/09/better-sql-group-by-find-duplicate-data/

你可能想试试这个

SELECT NAME, EMAIL, COUNT(*)
FROM USERS
GROUP BY 1,2
HAVING COUNT(*) > 1