Related
I want to join two tables and remove duplicates from both the tables but keeping any duplicate value found in the first table.
T1
Name
-----
A
A
B
C
T2
Name
----
A
D
E
Expected result
A - > FROM T1
A - > FROM T1
B
C
D
E
I tried union but removes all duplicates of 'A' from both tables.
How can I achieve this?
Filter T2 before UNION ALL
select col
from T1
union all
select col
from T2
where not exists (select 1 from T1 where T1.col = T2.col)
Assuming you want the number of duplicates from the table with the most repetitions for each value, you can do it with the ROW_NUMBER() windowing function, to eliminate duplicates by their sequence with the set of repetitions in each table.
SELECT Name FROM (
SELECT Name, ROW_NUMBER() OVER ( PARTITION BY Name ORDER BY Name ) AS Row
FROM T1
UNION
SELECT Name, ROW_NUMBER() OVER ( PARTITION BY Name ORDER BY Name ) AS Row
FROM T2
) x
ORDER BY Name
To see how this works out, we add two B rows to T2 then do this:
SELECT Name, ROW_NUMBER() OVER ( PARTITION BY Name ORDER BY Name ) AS Row
FROM T1
Name Row
A 1
A 2
B 1
C 1
SELECT Name, ROW_NUMBER() OVER ( PARTITION BY Name ORDER BY Name ) AS Row
FROM T2
Name Row
A 1
B 1
B 2
D 1
E 1
Now UNION them without ALL to combine and eliminate duplicates:
SELECT Name, ROW_NUMBER() OVER ( PARTITION BY Name ORDER BY Name ) AS Row
FROM T1
UNION
SELECT Name, ROW_NUMBER() OVER ( PARTITION BY Name ORDER BY Name ) AS Row
FROM T2
Name Row
A 1
A 2
B 1
B 2
C 1
D 1
E 1
The final query up top is then just eliminating the Row column and sorting the result, to ensure ascending order.
See SQL Fiddle for demo.
select * from T1
union all
select * from T2 where name not in (select distinct name from T1)
Sql Fiddle Demo
you should use "union all" instead of "union".
"union" remove other duplicated records while "union all" gives all of them.
for you result,because of we filtered intersects from table 2 in "where",we don't need "UNION ALL"
select col1 from t1
union
select col1 from t2 where t2.col1 not in(select t1.col1 from t1)
I D'not know the following code is good practice or not But it's working
select name from T1
UNION
select name from T2 Where name not in (select name from T1)
The Above Query Filter the value based on T1 value and then join two tables values and show the result.
I hope it's helps you thanks.
Note : It's not better way to get result it's affect your performance.
I sure i update the better solution after my research
You want all names from T1 and all names from T2 except the names that are in T1.
So you can use UNION ALL for the 2 cases and the operator EXCEPT to filter the rows of T2:
SELECT Name FROM T1
UNION ALL
(
SELECT Name FROM T2
EXCEPT
SELECT Name FROM T1
)
See the demo.
Results:
> | Name |
> | :--- |
> | A |
> | A |
> | B |
> | C |
> | D |
> | E |
I spend day in hope to figure out how to solve this query.
I have following table
ID Name Pregnancy Gender
1 Raghad Yes Female
1 Raghad No Female
2 Ohoud no Male
What I need is to remove duplicate (in this case 1,1) and to keep one of these rows which has a pregnancy status of yes.
To clarify, I can't use delete since it's a restricted database. I can only retrieve data.
Using an exists clause:
DELETE
FROM yourTable t1
WHERE
pregnancy = 'no' AND
EXISTS (SELECT 1 FROM yourTable t2 WHERE t2.ID = t1.ID AND t2.pregnancy = 'yes');
There are other ways to go about doing this, e.g. using ROW_NUMBER, but as you did not tag your database, I offer the above solution which should work on basically any database.
If you want to just view your data with the "duplicates" removed, then use:
SELECT *
FROM yourTable t1
WHERE
pregnancy = 'yes' OR
NOT EXISTS (SELECT 1 FROM yourTable t2 WHERE t2.ID = t1.ID AND t2.pregnancy = 'yes');
If column Pregnancy have just two values "Yes" and "No", in that case you can use ROW_NUMBER() also to get the results.
;WITH CTE
AS (
SELECT *,ROW_NUMBER() OVER (PARTITION BY id ORDER BY Pregnancy DESC) RN
FROM TABLE_NAME
)
SELECT *
FROM CTE
WHERE RN = 1
In case of multiple values when you want to give highest priorty to "Yes", you can write your query like following
;WITH CTE
AS (
SELECT *,ROW_NUMBER() OVER
(PARTITION BY id ORDER BY CASE WHEN Pregnancy = 'Yes' then 0 else 1 end) RN
FROM TABLE_NAME
)
SELECT *
FROM CTE
WHERE RN= 1
For this sample data you can group by ID, Name, Gender and return the maximum value of the column Pregnancy for each group since Yes is greater compared to No:
SELECT ID, Name, MAX(Pregnancy) Pregnancy, Gender
FROM tablename
GROUP BY ID, Name, Gender
See the demo.
Results:
> ID | Name | Pregnancy | Gender
> -: | :----- | :-------- | :-----
> 1 | Raghad | Yes | Female
> 2 | Ohoud | No | Male
Here is how you could do it in MySQL 8.
Similar Common Table Expressions exist in SQL Server and Oracle.
There you may need to add a comma after then closing parentheses that
ends the CTE (with) definition.
with dups as (
Select id from test
group by id
Having count(1) > 1
)
select * from test
where id in (select id from dups)
and Pregnancy = 'Yes'
union all
select * from test where id not in (select id from dups);
You can see it in action, by running it here
Note this does it without deleting the original.
But it gives you a result set to work with that has what you want.
If you wanted to delete, then you could use this instead, after the dups CTE definition:
delete from test
where id in (select id from dups) and Pregnancy = 'No'
Or distill this into:
delete from test
where id in (Select id from test
group by id
Having count(1) > 1) and Pregnancy = 'No'
1) First of all, update design of your table. ID must be primary key. This would automatically restrict the duplicate rows having same ID.
2) You can use Group by and having clause to remove duplicates
delete from table where pregnancy='no' and exists (SELECT
id
FROM table
GROUP BY id
HAVING count(id)>1)
I have a table where ID must be unique. There are some IDs that are not unique. How do I generate a new column which adds a sequence to this ID? I want to generate ID_new_generated in the table below
ID Company Name ID_new_generated
1 A 1
1 B 1_2
2 C 2
You can use a windowing function (e.g. Rank) to to generate an secondary ID, over each window defined by rows that have the same ID number, then just concatenate it to create the new one.
something like:
select
ID
, companyName
, rank() over(partition by ID ORDER BY companyName)
, concat(ID, '_', rank() over(partition by ID ORDER BY companyName)) as new_id
from test;
See this demo: https://www.db-fiddle.com/f/bd6aQKnZ7gcZCQjFpZicrp/0
Syntax will be different depending on which sql you are using.
Assumed you are looking for a solution in SQL Server:
First you will need to add a nullable column ID_Generated like below:
ALTER TABLE tablename
ADD COLUMN ID_Generated varchar(25) null
GO
Then, use row_number like below in a cte structure (you can use temp table if you are using mysql):
;with cte as (
SELECT DISTINCT t.ID,
(ROW_NUMBER() over (partition by t.ID order by t.ID)) as RowNumber
FROM tablename t
INNER JOIN (select ID, Count(*) RecCount
From tablename
group by ID
having Count(*) > 1) tt on t.ID = t.ID
ORDER BY id ASC
)
Update t
set t.ID_Generated = cte.RowNumber
from tablename t
inner join cte on t.ID = cte.ID
I think you want:
select ID, companyName,
(case when row_number() over (partition by id order by companyname) = 1
then cast(id as varchar(255))
else id || '_' || row_number() over (partition by id order by companyname)
end) as new_id
from test;
|| is the ANSI/ISO standard concatenation operator in SQL. Not all databases support it, so you might need to replace the operator with the one appropriate for your database.
I have a Postgres table created with the following statement. This table is filled by as dump of data from another service.
CREATE TABLE data_table (
date date DEFAULT NULL,
dimension1 varchar(64) DEFAULT NULL,
dimension2 varchar(128) DEFAULT NULL
) TABLESPACE pg_default;
One of the steps in a ETL I'm building is extracting the unique values of dimension1 and inserting them in another intermediary table.
However, during some tests I found out that the 2 commands below do not return the same results. I would expect for both to return the same sum.
The first command returns more results compared with the second (1466 rows vs. 1504.
-- command 1
SELECT DISTINCT count(dimension1)
FROM data_table;
-- command 2
SELECT count(*)
FROM (SELECT DISTINCT ON (dimension1) dimension1
FROM data_table
GROUP BY dimension1) AS tmp_table;
Any obvious explanations for this? Alternatively to an explanation, is there any suggestion of any check on the data I should do?
EDIT: The following queries both return 1504 (same as the "simple" DISTINCT)
SELECT count(*)
FROM data_table WHERE dimension1 IS NOT NULL;
SELECT count(dimension1)
FROM data_table;
Thank you!
DISTINCT and DISTINCT ON have completely different semantics.
First the theory
DISTINCT applies to an entire tuple. Once the result of the query is computed, DISTINCT removes any duplicate tuples from the result.
For example, assume a table R with the following contents:
#table r;
a | b
---+---
1 | a
2 | b
3 | c
3 | d
2 | e
1 | a
(6 rows)
SELECT distinct * from R will result:
# select distinct * from r;
a | b
---+---
1 | a
3 | d
2 | e
2 | b
3 | c
(5 rows)
Note that distinct applies to the entire list of projected attributes: thus
select distinct * from R
is semantically equivalent to
select distinct a,b from R
You cannot issue
select a, distinct b From R
DISTINCT must follow SELECT. It applies to the entire tuple, not to an attribute of the result.
DISTINCT ON is a postgresql addition to the language. It is similar, but not identical, to group by.
Its syntax is:
SELECT DISTINCT ON (attributeList) <rest as any query>
For example:
SELECT DISTINCT ON (a) * from R
It semantics can be described as follows. Compute the as usual--without the DISTINCT ON (a)---but before the projection of the result, sort the current result and group it according to the attribute list in DISTINCT ON (similar to group by). Now, do the projection using the first tuple in each group and ignore the other tuples.
Example:
select * from r order by a;
a | b
---+---
1 | a
2 | e
2 | b
3 | c
3 | d
(5 rows)
Then for every different value of a (in this case, 1, 2 and 3), take the first tuple. Which is the same as:
SELECT DISTINCT on (a) * from r;
a | b
---+---
1 | a
2 | b
3 | c
(3 rows)
Some DBMS (most notably sqlite) will allow you to run this query:
SELECT a,b from R group by a;
And this give you a similar result.
Postgresql will allow this query, if and only if there is a functional dependency from a to b. In other words, this query will be valid if for any instance of the relation R, there is only one unique tuple for every value or a (thus selecting the first tuple is deterministic: there is only one tuple).
For instance, if the primary key of R is a, then a->b and:
SELECT a,b FROM R group by a
is identical to:
SELECT DISTINCT on (a) a, b from r;
Now, back to your problem:
First query:
SELECT DISTINCT count(dimension1)
FROM data_table;
computes the count of dimension1 (number of tuples in data_table that where dimension1 is not null). This query
returns one tuple, which is always unique (hence DISTINCT
is redundant).
Query 2:
SELECT count(*)
FROM (SELECT DISTINCT ON (dimension1) dimension1
FROM data_table
GROUP BY dimension1) AS tmp_table;
This is query in a query. Let me rewrite it for clarity:
WITH tmp_table AS (
SELECT DISTINCT ON (dimension1)
dimension1 FROM data_table
GROUP by dimension1)
SELECT count(*) from tmp_table
Let us compute first tmp_table. As I mentioned above,
let us first ignore the DISTINCT ON and do the rest of the
query. This is a group by by dimension1. Hence this part of the query
will result in one tuple per different value of dimension1.
Now, the DISTINCT ON. It uses dimension1 again. But dimension1 is unique already (due to the group by). Hence
this makes the DISTINCT ON superflouos (it does nothing).
The final count is simply a count of all the tuples in the group by.
As you can see, there is an equivalence in the following query (it applies to any relation with an attribute a):
SELECT (DISTINCT ON a) a
FROM R
and
SELECT a FROM R group by a
and
SELECT DISTINCT a FROM R
Warning
Using DISTINCT ON results in a query might be non-deterministic for a given instance of the database.
In other words, the query might return different results for the same tables.
One interesting aspect
Distinct ON emulates a bad behaviour of sqlite in a much cleaner way. Assume that R has two attributes a and b:
SELECT a, b FROM R group by a
is an illegal statement in SQL. Yet, it runs on sqlite. It simply takes a random value of b from any of the tuples in the group of same values of a.
In Postgresql this statement is illegal. Instead, you must use DISTINCT ON and write:
SELECT DISTINCT ON (a) a,b from R
Corollary
DISTINCT ON is useful in a group by when you want to access a value that is functionally dependent on the group by attributes. In other words, if you know that for every group of attributes they always have the same value of the third attribute, then use DISTINCT ON that group of attributes. Otherwise you would have to make a JOIN to retrieve that third attribute.
The first query gives the number of not null values of dimension1, while the second one returns the number of distinct values of the column. These numbers obviously are not equal if the column contains duplicates or nulls.
The word DISTINCT in
SELECT DISTINCT count(dimension1)
FROM data_table;
makes no sense, as the query returns a single row. Maybe you wanted
SELECT count(DISTINCT dimension1)
FROM data_table;
which returns the number of distinct not null values of dimension1. Note, that it is not the same as
SELECT count(*)
FROM (
SELECT DISTINCT ON (dimension1) dimension1
FROM data_table
-- GROUP BY dimension1 -- redundant
) AS tmp_table;
The last query yields the number of all (null or not) distinct values of the column.
To learn and understand what happens by visual example.
Here's a bit of SQL to execute on a PostgreSQL:
DROP TABLE IF EXISTS test_table;
CREATE TABLE test_table (
id int NOT NULL primary key,
col1 varchar(64) DEFAULT NULL
);
INSERT INTO test_table (id, col1) VALUES
(1,'foo'), (2,'foo'), (3,'bar'), (4,null);
select count(*) as total1 from test_table;
-- returns: 4
-- Because the table has 4 records.
select distinct count(*) as total2 from test_table;
-- returns: 4
-- The count(*) is just one value. Making 1 total unique can only result in 1 total.
-- So the distinct is useless here.
select col1, count(*) as total3 from test_table group by col1 order by col1;
-- returns 3 rows: ('bar',1),('foo',2),(NULL,1)
-- Since there are 3 unique col1 values. NULL's are included.
select distinct col1, count(*) as total4 from test_table group by col1 order by col1;
-- returns 3 rows: ('bar',1),('foo',2),(NULL,1)
-- The result is already grouped, and therefor already unique.
-- So again, the distinct does nothing extra here.
select count(distinct col1) as total5 from test_table;
-- returns 2
-- NULL's aren't counted in a count by value. So only 'foo' & 'bar' are counted
select distinct on (col1) id, col1 from test_table order by col1 asc, id desc;
-- returns 3 rows: (2,'a'),(3,'b'),(4,NULL)
-- So it gets the records with the maximum id per unique col1
-- Note that the "order by" matters here. Changing that DESC to ASC would get the minumum id.
select count(*) as total6 from (select distinct on (col1) id, col1 from test_table order by col1 asc, id desc) as q;
-- returns 3.
-- After seeing the previous query, what else would one expect?
select distinct col1 from test_table order by col1;
-- returns 3 unique values : ('bar'),('foo'),(null)
select distinct id, col1 from test_table order by col1;
-- returns all records.
-- Because id is the primary key and therefore makes each returned row unique
Here's a more direct summary that might useful for Googlers, answering the title but not the intricacies of the full post:
SELECT DISTINCT
availability: ISO
behaviour:
SELECT DISTINCT col1, col2, col3 FROM mytable
returns col1, col2 and col3 and omits any rows in which all of the tuple (col1, col2, col3) are the same. E.g. you could get a result like:
1 2 3
1 2 4
because those two rows are not identical due to the 4. But you could never get:
1 2 3
1 2 4
1 2 3
because 1 2 3 appears twice, and both rows are exactly the same. That is what DISTINCT prevents.
vs GROUP BY: SELECT DISTINCT is basically a subset of GROUP BY where you can't use aggregate functions: Is there any difference between GROUP BY and DISTINCT
SELECT DISTINCT ON
availability: PostgreSQL extension, WONTFIXED by SQLite
behavior: unlike DISTINCT, DISTINCT ON allows you to separate
what you want to be unique
from what you want to return
E.g.:
SELECT DISTINCT ON(col1) col2, col3 FROM mytable
returns col2 and col3, and does not return any two rows with the same col1. E.g.:
1 2 3
1 4 5
could not happen, because we have 1 twice on col1.
And e.g.:
SELECT DISTINCT ON(col1, col2) col2, col3 FROM mytable
would prevent any duplicated (col1, col2) tuples, e.g. you could get:
1 2 3
1 4 3
as it has different (1, 2) and (1, 4) tuples, but not:
1 2 3
1 2 4
where (1, 2) happens twice, only one of those two could appear.
We can uniquely determine which one of the possible rows will be selected with ORDER BY which guarantees that the first match is taken, e.g.:
SELECT DISTINCT ON(col1, col2) col2, col3 FROM mytable
ORDER BY col1 DESC, col2 DESC, col3 DESC
would ensure that among:
1 2 3
1 2 4
only 1 2 4 would be picked as it happens first on our DESC sorting.
vs GROUP BY: DISTINCT ON is not a subset of GROUP BY because it allows you to access extra rows not present in the GROUP BY, which is generally not allowed in GROUP BY, unless:
you group by primary key in Postgres (unique not null is a TODO for them)
or if that is allows as an ISO extension as in SQLite/MySQL
This makes DISTINCT ON extremely useful to fulfill the common use case of "find the full row that reaches the maximum/minimum of some column": Is there any difference between GROUP BY and DISTINCT
E.g. to find the city of each country that has the most sales:
SELECT DISTINCT ON ("country") "country", "city", "amount"
FROM "Sales"
ORDER BY "country" ASC, "amount" DESC, "city" ASC
or equivalently with * if we want all columns:
SELECT DISTINCT ON ("country") *
FROM "Sales"
ORDER BY "country" ASC, "amount" DESC, "city" ASC
Here each country appears only once, within each country we then sort by amount DESC and take the first, and therefore highest, amount.
RANK and ROW_NUMBER window functions
These can be used basically as supersets of DISTINCT ON, and implemented tested as of both SQLite 3.34 and PostgreSQL 14.3. I highly recommend also looking into them, see e.g.: How to SELECT DISTINCT of one column and get the others?
This is how the above "city with the highest amount of each country" query would look like with ROW_NUMBER:
SELECT *
FROM (
SELECT
ROW_NUMBER() OVER (
PARTITION BY "country"
ORDER BY "amount" DESC, "city" ASC
) AS "rnk",
*
FROM "Sales"
) sub
WHERE
"sub"."rnk" = 1
ORDER BY
"sub"."country" ASC
Try
SELECT count(dimension1a)
FROM (SELECT DISTINCT ON (dimension1) dimension1a
FROM data_table
ORDER BY dimension1) AS tmp_table;
DISTINCT ON appears to be synonymous with GROUP BY.
I have a table with 10 columns.
I want to return all rows for which Col006 is distinct, but return all columns...
How can I do this?
if column 6 appears like this:
| Column 6 |
| item1 |
| item1 |
| item2 |
| item1 |
I want to return two rows, one of the records with item1 and the other with item2, along with all other columns.
In SQL Server 2005 and above:
;WITH q AS
(
SELECT *, ROW_NUMBER() OVER (PARTITION BY col6 ORDER BY id) rn
FROM mytable
)
SELECT *
FROM q
WHERE rn = 1
In SQL Server 2000, provided that you have a primary key column:
SELECT mt.*
FROM (
SELECT DISTINCT col6
FROM mytable
) mto
JOIN mytable mt
ON mt.id =
(
SELECT TOP 1 id
FROM mytable mti
WHERE mti.col6 = mto.col6
-- ORDER BY
-- id
-- Uncomment the lines above if the order matters
)
Update:
Check your database version and compatibility level:
SELECT ##VERSION
SELECT COMPATIBILITY_LEVEL
FROM sys.databases
WHERE name = DB_NAME()
The key word "DISTINCT" in SQL has the meaning of "unique value". When applied to a column in a query it will return as many rows from the result set as there are unique, different values for that column. As a consequence it creates a grouped result set, and values of other columns are random unless defined by other functions (such as max, min, average, etc.)
If you meant to say you want to return all rows for which Col006 has a specific value, then use the "where Col006 = value" clause.
If you meant to say you want to return all rows for which Col006 is different from all other values of Col006, then you still need to specify what that value is => see above.
If you want to say that the value of Col006 can only be evaluated once all rows have been retrieved, then use the "having Col006 = value" clause. This has the same effect as the "where" clause, but "where" gets applied when rows are retrieved from the raw tables, whereas "having" is applied once all other calculations have been made (i.e. aggregation functions have been run etc.) and just before the result set is returned to the user.
UPDATE:
After having seen your edit, I have to point out that if you use any of the other suggestions, you will end up with random values in all other 9 columns for the row that contains the value "item1" in Col006, due to the constraint further up in my post.
You can group on Col006 to get the distinct values, but then you have to decide what to do with the multiple records in each group.
You can use aggregates to pick a value from the records. Example:
select Col006, min(Col001), max(Col002)
from TheTable
group by Col006
order by Col006
If you want the values to come from a specific record in each group, you have to identify it somehow. Example of using Col002 to identify the record in each group:
select Col006, Col001, Col002
from TheTable t
inner join (
select Col006, min(Col002)
from TheTable
group by Col006
) x on t.Col006 = x.Col006 and t.Col002 = x.Col002
order by Col006
SELECT *
FROM (SELECT DISTINCT YourDistinctField FROM YourTable) AS A
CROSS APPLY
( SELECT TOP 1 * FROM YourTable B
WHERE B.YourDistinctField = A.YourDistinctField ) AS NewTableName
I tried the answers posted above with no luck... but this does the trick!
select * from yourTable where column6 in (select distinct column6 from yourTable);
SELECT *
FROM harvest
GROUP BY estimated_total;
You can use GROUP BY and MIN() to get more specific result.
Lets say that you have id as the primary_key.
And we want to get all the DISTINCT values for a column lets say estimated_total, And you also need one sample of complete row with each distinct value in SQL. Following query should do the trick.
SELECT *, min(id)
FROM harvest
GROUP BY estimated_total;
create table #temp
(C1 TINYINT,
C2 TINYINT,
C3 TINYINT,
C4 TINYINT,
C5 TINYINT,
C6 TINYINT)
INSERT INTO #temp
SELECT 1,1,1,1,1,6
UNION ALL SELECT 1,1,1,1,1,6
UNION ALL SELECT 3,1,1,1,1,3
UNION ALL SELECT 4,2,1,1,1,6
SELECT * FROM #temp
SELECT *
FROM(
SELECT ROW_NUMBER() OVER (PARTITION BY C6 Order by C1) ID,* FROM #temp
)T
WHERE ID = 1