Sql как найти повторяющиеся строки

asked Jan 21, 2010 at 20:29

If you want to delete duplicates:

WITH CTE AS(
   SELECT orgName,id,
       RN = ROW_NUMBER()OVER(PARTITION BY orgName ORDER BY Id)
   FROM organizations
)
DELETE FROM CTE WHERE RN > 1

answered Jun 17, 2016 at 9:51

select a.orgName,b.duplicate, a.id
from organizations a
inner join (
    SELECT orgName, COUNT(*) AS duplicate
    FROM organizations
    GROUP BY orgName
    HAVING COUNT(*) > 1
) b on o.orgName = oc.orgName
group by a.orgName,a.id

select orgname, count(*) as dupes, id 
from organizations
where orgname in (
    select orgname
    from organizations
    group by orgname
    having (count(*) > 1)
)
group by orgname, id

answered Jan 21, 2010 at 20:49

You have several way for Select duplicate rows.

for my solutions , first consider this table for example

CREATE TABLE #Employee
(
ID          INT,
FIRST_NAME  NVARCHAR(100),
LAST_NAME   NVARCHAR(300)
)

INSERT INTO #Employee VALUES ( 1, 'Ardalan', 'Shahgholi' );
INSERT INTO #Employee VALUES ( 2, 'name1', 'lname1' );
INSERT INTO #Employee VALUES ( 3, 'name2', 'lname2' );
INSERT INTO #Employee VALUES ( 2, 'name1', 'lname1' );
INSERT INTO #Employee VALUES ( 3, 'name2', 'lname2' );
INSERT INTO #Employee VALUES ( 4, 'name3', 'lname3' );

First solution :

SELECT DISTINCT *
FROM   #Employee;

WITH #DeleteEmployee AS (
                     SELECT ROW_NUMBER()
                            OVER(PARTITION BY ID, First_Name, Last_Name ORDER BY ID) AS
                            RNUM
                     FROM   #Employee
                 )

SELECT *
FROM   #DeleteEmployee
WHERE  RNUM > 1

SELECT DISTINCT *
FROM   #Employee

Secound solution : Use identity field

SELECT DISTINCT *
FROM   #Employee;

ALTER TABLE #Employee ADD UNIQ_ID INT IDENTITY(1, 1)

SELECT *
FROM   #Employee
WHERE  UNIQ_ID < (
    SELECT MAX(UNIQ_ID)
    FROM   #Employee a2
    WHERE  #Employee.ID = a2.ID
           AND #Employee.FIRST_NAME = a2.FIRST_NAME
           AND #Employee.LAST_NAME = a2.LAST_NAME
)

ALTER TABLE #Employee DROP COLUMN UNIQ_ID

SELECT DISTINCT *
FROM   #Employee

and end of all solution use this command

DROP TABLE #Employee

answered Nov 7, 2013 at 7:06

i think i know what you need
i needed to mix between the answers and i think i got the solution he wanted:

select o.id,o.orgName, oc.dupeCount, oc.id,oc.orgName
from organizations o
inner join (
    SELECT MAX(id) as id, orgName, COUNT(*) AS dupeCount
    FROM organizations
    GROUP BY orgName
    HAVING COUNT(*) > 1
) oc on o.orgName = oc.orgName

having the max id will give you the id of the dublicate and the one of the original which is what he asked for:

id org name , dublicate count (missing out in this case) 
id doublicate org name , doub count (missing out again because does not help in this case)

only sad thing you get it put out in this form

id , name , dubid , name

hope it still helps

answered Oct 1, 2014 at 8:13

Suppose we have table the table ‘Student’ with 2 columns:

• student_id int

• student_name varchar

  Records:
  +------------+---------------------+
  | student_id | student_name        |
  +------------+---------------------+
  |        101 | usman               |
  |        101 | usman               |
  |        101 | usman               |
  |        102 | usmanyaqoob         |
  |        103 | muhammadusmanyaqoob |
  |        103 | muhammadusmanyaqoob |
  +------------+---------------------+
  

Now we want to see duplicate records
Use this query:

select student_name,student_id ,count(*) c from student group by student_id,student_name having c>1;

+---------------------+------------+---+
| student_name        | student_id | c |
+---------------------+------------+---+
| usman               |        101 | 3 |
| muhammadusmanyaqoob |        103 | 2 |
+---------------------+------------+---+

I got a better option to get the duplicate records in a table

SELECT x.studid, y.stdname, y.dupecount
FROM student AS x INNER JOIN
(SELECT a.stdname, COUNT(*) AS dupecount
FROM student AS a INNER JOIN
studmisc AS b ON a.studid = b.studid
WHERE (a.studid LIKE '2018%') AND (b.studstatus = 4)
GROUP BY a.stdname
HAVING (COUNT(*) > 1)) AS y ON x.stdname = y.stdname INNER JOIN
studmisc AS z ON x.studid = z.studid
WHERE (x.studid LIKE '2018%') AND (z.studstatus = 4)
ORDER BY x.stdname

Result of the above query shows all the duplicate names with unique student ids and number of duplicate occurances

Click here to see the result of the sql

answered Jun 25, 2018 at 9:22

 /*To get duplicate data in table */

 SELECT COUNT(EmpCode),EmpCode FROM tbl_Employees WHERE Status=1 
  GROUP BY EmpCode HAVING COUNT(EmpCode) > 1

answered Apr 26, 2019 at 14:01

I use two methods to find duplicate rows.
1st method is the most famous one using group by and having.
2nd method is using CTE — Common Table Expression.

As mentioned by @RedFilter this way is also right. Many times I find CTE method is also useful for me.

WITH TempOrg (orgName,RepeatCount)
AS
(
SELECT orgName,ROW_NUMBER() OVER(PARTITION by orgName ORDER BY orgName) 
AS RepeatCount
FROM dbo.organizations
)
select t.*,e.id from organizations   e
inner join TempOrg t on t.orgName= e.orgName
where t.RepeatCount>1

In the example above we collected the result by finding repeat occurrence using ROW_NUMBER and PARTITION BY. Then we applied where clause to select only rows which are on repeat count more than 1. All the result is collected CTE table and joined with Organizations table.

Source : CodoBee

Try

SELECT orgName, id, count(*) as dupes
FROM organizations
GROUP BY orgName, id
HAVING count(*) > 1;

1. Using Count
2. MINUS Function
3. Analytic Functions

The most obvious answer is YES! John occurs 3 times and so does Sam.

How about if we were to look at columns NAME and FRUIT? Once again, the answer would be YES, because “Sam” and “Banana” occurs twice. Apparently, Sam loves bananas, while John prefers a different fruit every day.

Finally, let’s look at columns NAME, FRUIT and DAY. Do you see any duplicates now?

The answer is NO. There are no duplicates because both Sam and John had a different fruit on each day.

The point I would like to drive home is this! To truly understand if data is duplicate, you need to understand the context and the functionality behind it.

Note: All SQL examples below use Oracle SQL syntax. However, they should work across most relational databases with minimal changes.

Related post: Apache Spark SQL date functions

1. SQL Find Duplicates using Count

The most common method to find duplicates in sql is using the count function in a select statement. There are two other clauses that are key to finding duplicates: GROUP BY and HAVING.

Let us continue using the database table (USER_DIET) from the previous example and see if we can find duplicates for the NAME column.

a. Duplicates in a single column

In this second example, let us look at finding duplicates in multiple columns: NAME and FRUIT. 

Lets think this thru and put things in context before diving into our select statement. As yourself, what am I trying to find here ? 

We are trying to find if any of the users, in this case, Sam/John had the same fruit twice. That it ! This context is based on the two fields NAME and FRUIT. 

b. Duplicates in multiple columns

Key to remember, the columns in the select statement, excluding the count(*) should be the exact same in the group by clause as well. 

Also note that using the count(*) function gives you a count of the number of occurrences of a value. In this case, “Sam” + “Banana” occurs twice in the table, but in actuality we only have one duplicate row.

c. SQL to find duplicate rows

Ideally, if the database table has the right combination of key columns, you should not have duplicate rows. Regardless, if you are suspicious that your table has duplicate rows, perform the below steps.

1. Determine they Key columns on your table.
2. If the table does not have keys defined, determine which column(s) makes a row unique. Often times this depends on the functional use case of the data.
3. Add the fields from Step 1 or Step 2 to your SQL COUNT(*) clause. 

SELECT name, fruit, day, count(*) from user_diet
GROUP BY name, fruit, day
HAVING count(*)>1;

2. SQL Find Duplicates using MINUS function

The MINUS function works on two tables ( or datasets) and returns rows from the first table that does not belong in the second table. This option using the MINUS function in SQL, to find duplicates, is specific to Oracle. Use it for awareness and to validate your results using the count(*) method. 

Find duplicates using MINUS function and rowid

ROWID is a pseudo column in Oracle and contains a distinct ID for each row in a table.

The first select statement (before the MINUS function) returns 6 rows containing NAME and a distinct value for the ROWID column.  The second select statement on the other hand returns 2 rows, one for Sam and one for John. Why do you think that is ?

It’s because of the min function on the ROWID column.

The final output contains the “actual” number of duplicate rows, and not the total number of rows like the count(*) function.

Find duplicates using MINUS function and rownum

In this second example, we used ROWNUM, which is a pseudo column used to uniquely identify the order of each row in a select statement. 

So, what’s the difference between ROWNUM and ROWID in our example? 

They are both pseudo columns in Oracle.

ROWNUM is a number and is generated on the result of the SQL statement. ROWID on the other hand is associated with each row of a table. 

3. Find Duplicates in SQL using Analytic functions

Analytic functions are used to perform calculations on a grouping of data, normally called a “window”. This technique can be a bit confusing if you are just starting off with SQL, but it’s definitely worth knowing.

What are we doing here?

SELECT name FROM (
SELECT name, ROW_NUMBER() OVER ( PARTITION BY name ORDER BY name) AS rnum FROM user_diet)
WHERE rnum = 1;

Conclusion

A final tidbit, SQL is not limited to transactional databases.

Apache Spark has a module called Spark SQL to handle structured data. AWS Athena even lets you write SQL against files!

The demand for SQL skills is endless. So play around with what you learned here. Try selecting multiple columns, switch the PARTITIONS, change the SORT order. Practice is the best way to master something !

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