I'm having a table called table such that:
| id | name | city |
|----|-------|---------|
| 0 | Rose | Madrid |
| 1 | Alex | Lima |
| 2 | Rose | Sidney |
| 3 | Mario | Glasgow |
And I need to UPDATE the table so that two rows sharing the same name combined into a new one and deleted.
| id | name | city |
|----|-------|----------------|
| 1 | Alex | Lima |
| 3 | Mario | Glasgow |
| 4 | Rose | Madrid, Sidney |
I don't care if it has to be done in several SQL statements.
So far all I've done is to list the rows that are affected by this.
SELECT *
FROM table
WHERE name IN (
SELECT name
FROM table
GROUP BY name
HAVING COUNT(*) > 1
);
Assuming that id is auto increment primary key, you need an INSERT and a DELETE statement:
insert into tablename(name, city)
select name, group_concat(city, ',')
from tablename
group by name
having count(*) > 1;
delete from tablename
where instr(name, ',') = 0
and exists (
select 1 from tablename t
where t.id <> tablename.id and t.name = tablename.name
and ',' || t.city || ',' like '%,' || tablename.city || ',%'
);
See the demo.
Results:
| id | name | city |
| --- | ----- | ------------- |
| 1 | Alex | Lima |
| 3 | Mario | Glasgow |
| 4 | Rose | Madrid,Sidney |
Related
My goal is to add another column to an existing table, to see if the value/conditions exists in a group and appropriately labeling the entire group if it is present or not.
If a Team has one project with a budget >= 20M or Actual_Spend >=2.5M I want to label the Team and all it's projects as Table 1 in the Category column. Irrespective if the other projects within the same Team fit this criteria.
I will provide a SQL fiddle link w/ my solution: http://sqlfiddle.com/#!18/3ddaf/12/0
I'm ending up with two extra columns of "Team" and "Category" and not sure how they're ending up there.
Below is the end result I'm looking for. I'm open to better solutions than the one I provided.
Thank you for your time
| Team | ProjectID | Budget | Actual_Spend | State | Category |
|------|-----------|----------|--------------|------------|----------|
| Cyan | 2 | NULL | NULL | Utah | Table 1 |
| Blue | 1 | NULL | 3000000 | California | Table 1 |
| Cyan | 1 | 20000000 | 1000000 | Utah | Table 1 |
| Blue | 2 | 22000000 | NULL | California | Table 1 |
| Red | 1 | 7000000 | 1000000 | Washington | Table 2 |
| Red | 2 | 19999000 | 2490000 | Oregon | Table 2 |
| Gray | 1 | 19000000 | 2500000 | Utah | Table 1 |
| Gray | 1 | 10000000 | 500000 | Utah | Table 1 |
Providing code to create the dataset:
Create Table Source_Data
(
Team varchar(50),
ProjectID INT,
BUDGET INT,
Actual_Spend INT,
State varchar(max),
)
INSERT INTO Source_Data
VALUES
('Blue',1,NULL,3000000,'California'),
('Green',1,20000000,1000000,'Utah'),
('Blue',2,22000000,NULL,'California'),
('Green',2,NULL,NULL,'Utah'),
('Red',1,7000000,1000000,'Washington'),
('Red',2,19999000,2490000,'Oregon'),
('Yellow',1,19000000,2500000,'Utah'),
('Yellow',1,10000000,500000,'Utah');
I think that you are looking for window functions:
select
s.*,
min(case when Budget>=20000000 or Actual_Spend>=2500000 then 'Table1' else 'Table2' end)
over(partition by team) Category
from Source_Data s
If any of the records having the same team satisfies condition Budget>=20000000 or Actual_Spend>=2500000, the new column yields Table1, else it produces Table2.
Demo on DB Fiddle:
Team | ProjectID | Budget | Actual_Spend | State | Category
:--- | --------: | -------: | -----------: | :--------- | :-------
Blue | 2 | 22000000 | null | California | Table1
Blue | 1 | null | 3000000 | California | Table1
Cyan | 1 | 20000000 | 1000000 | Utah | Table1
Cyan | 2 | null | null | Utah | Table1
Gray | 1 | 19000000 | 2500000 | Utah | Table1
Gray | 1 | 10000000 | 500000 | Utah | Table1
Red | 1 | 7000000 | 1000000 | Washington | Table2
Red | 2 | 19999000 | 2490000 | Oregon | Table2
I have some troubles with deleting partial duplicate rows
The structure is like this:
+-----+--------+--+-----------+--+------+
| id | userid | | location | | week |
+-----+--------+--+-----------+--+------+
| 1 | 001 | | amsterdam | | 11 |
| 2 | 001 | | amsterdam | | 23 |
| 3 | 002 | | berlin | | 28 |
| 4 | 002 | | berlin | | 22 |
| 5 | 003 | | paris | | 19 |
| 6 | 003 | | paris | | 35 |
+-----+--------+--+-----------+--+------+
I only need to keep one row from each userid, it doesn't matter which week number it has.
Thanks,
Maxcim
This should work across most databases:
DELETE
FROM yourTable
WHERE id <> (SELECT MIN(id)
FROM yourTable t
WHERE t.userid = userid)
This query would delete from each userid group all records except for the record having the lowest id for that group. I assume that id is a unique column.
This method is tested, try it.
We are getting the number of rows occuring at each record, and then we are deleting only the ones with more than 1 row occruring... keeping the original one.
BEGIN TRANSACTION
SELECT UserID, Location,
RN = ROW_NUMBER()OVER(PARTITION BY UserID, Location ORDER BY UserID, Location)
into #test1
FROM dbo.MyTbl
Delete MyTbl
From MyTbll
INNER JOIN #test1
ON #test1.UserID= MyTbl.UserID
WHERE RN > 1
if ##Error <> 0 GOTO Errlbl
Commit Transaction
RETURN
Errlbl:
RollBack Transaction
GO
I made a INNER JOIN in stored procedure, but I don't know what to put to my WHERE clause to filter those column with null values and only shows those rows who has not null on a particular column.
CREATE PROCEDURE [dbo].[25]
#param1 int
AS
SELECT c.Name, c.Age, c2.Name, c2.Country
FROM Cus C
INNER JOIN Cus2 C2 ON c.id = c2.id
WHERE c2.country is not null and c2.id = #param1
Order by c2.Country
RETURN 0
ID 1
+-----+----+---------+---------+
| QID | ID | Name | Country |
+-----+----+---------+---------+
| 1 | 1 | Null | PH |
| 2 | 1 | Null | CN |
| 3 | 1 | Japhet | USA |
| 4 | 1 | Abegail | UK |
| 5 | 1 | Norlee | Ger |
+-----+----+---------+---------+
ID 2
+-----+----+----------+---------+
| QID | ID | Name | Country |
+-----+----+----------+---------+
| 1 | 2 | Null | PH |
| 2 | 2 | Null | CN |
| 3 | 2 | Reynaldo | USA |
| 4 | 2 | Abegail | UK |
| 5 | 2 | Norlee | Ger |
+-----+----+----------+---------+
ID 3
+-----+----+----------+---------+
| QID | ID | Name | Country |
+-----+----+----------+---------+
| 1 | 3 | Gab | PH |
| 2 | 3 | Null | CN |
| 3 | 3 | Reynaldo | USA |
| 4 | 3 | Abegail | UK |
| 5 | 3 | Norlee | Ger |
+-----+----+----------+---------+
I want when I choose any of the user in the C Table it will display the C child table data and remove the null name rows and remain the rows with not null name column.
Desired Result:
C Table (Parent)
+----+---------+-----+
| ID | Name | Age |
+----+---------+-----+
| 3 | Abegail | 31 |
+----+---------+-----+
C2 Table (Child)
+-----+----+----------+---------+
| QID | ID | Name | Country |
+-----+----+----------+---------+
| 1 | 3 | Gab | PH |
| 3 | 3 | Reynaldo | USA |
| 4 | 3 | Abegail | UK |
| 5 | 3 | Norlee | Ger |
+-----+----+----------+---------+
WHERE column IS NOT NULL is the syntax to filter out NULL values.
Solution 1: test not null value
Example:
WHERE yourcolumn IS NOT NULL
Solution 2: test comparaison value in your where clause (comparaison substract null values)
Examples:
WHERE yourcolumn = value
WHERE yourcolumn <> value
WHERE yourcolumn in ( value)
WHERE yourcolumn not in ( value)
WHERE yourcolumn between value1 and value2
WHERE yourcolumn not between value1 and value2
I have 5 columns in SQL that I need to turn into a cross tab in Crystal.
This is what I have:
Key | RELATIONSHIP | DISABLED | LIMITED | RURAL | IMMIGRANT
-----------------------------------------------------------------
1 | Other Dependent | Yes | No | No | No
2 | Victim/Survivor | No | No | No | No
3 | Victim/Survivor | Yes | No | No | No
4 | Child | No | No | No | No
5 | Victim/Survivor | No | No | No | No
6 | Victim/Survivor | No | No | No | No
7 | Child | No | No | No | No
8 | Victim/Survivor | No | Yes | Yes | Yes
9 | Child | No | Yes | Yes | Yes
10 | Child | No | Yes | Yes | Yes
This is what I want the cross tab to look like (Distinct count on Key):
| Victim/Survivor | Child | Other Dependent | Total |
--------------------------------------------------------------
| DISABLED | 1 | 0 | 1 | 2 |
--------------------------------------------------------------
| LIMITED | 1 | 2 | 0 | 3 |
--------------------------------------------------------------
| RURAL | 1 | 2 | 0 | 3 |
--------------------------------------------------------------
| IMMIGRANT | 1 | 2 | 0 | 3 |
--------------------------------------------------------------
| TOTAL | 4 | 6 | 1 | 11 |
--------------------------------------------------------------
I used this formula in Crystal in an effort to combine 4 columns (Field name = {#OTHERDEMO})...
IF {TABLE.DISABLED} = "YES" THEN "DISABLED" ELSE
IF {TABLE.LIMITED} = "YES" THEN "LIMITED" ELSE
IF {TABLE.IMMIGRANT} = "YES" THEN "IMMIGRANT" ELSE
IF {TABLE.RURAL} = "YES" THEN "RURAL"
...then made the cross-tab with #OTHERDEMO as the rows, RELATIONSHIP as the Columns with a distinct count on KEY:
Problem is, once crystal hits the first "Yes" it stops counting thus not categorizing correctly in the cross-tab. So I get a table that counts the DISABILITY first and gives the correct display, then counts the Limited and gives some info, but then dumps everything else.
In the past, I have done mutiple conditional formulas...
IF {TABLE.DISABLED} = "YES" AND {TABLE.RELATIONSHIP} = "Victim/Survivor" THEN {TABLE.KEY} ELSE {#NULL}
(the #null formula is because Crystal, notoriously, gets confused with nulls.)
...then did a distinct count on Key, and finally summed it in the footer.
I am convinced there is another way to do this. Any help/ideas would be greatly appreciated.
If you unpivot those "DEMO" columns into rows it will make the crosstab super easy...
select
u.[Key],
u.[RELATIONSHIP],
u.[DEMO]
from
Table1
unpivot (
[b] for [DEMO] in ([DISABLED], [LIMITED], [RURAL], [IMMIGRANT])
) u
where
u.[b] = 'Yes'
SqlFiddle
or if you were stuck on SQL2000 compatibility level you could manually unpivot the Yes values...
select [Key], [REALTIONSHIP], [DEMO] = cast('DISABLED' as varchar(20))
from Table1
where [DISABLED] = 'Yes'
union
select [Key], [REALTIONSHIP], [DEMO] = cast('LIMITED' as varchar(20))
from Table1
where [LIMITED] = 'Yes'
union
select [Key], [REALTIONSHIP], [DEMO] = cast('RURAL' as varchar(20))
from Table1
where [RURAL] = 'Yes'
union
select [Key], [REALTIONSHIP], [DEMO] = cast('IMMIGRANT' as varchar(20))
from Table1
where [IMMIGRANT] = 'Yes'
For the crosstab, use a count on the Key column (aka row count), [DEMO] on rows, and [RELATIONSHIP] on columns.
I would like to update a table:
| id | type_id | created_at | sequence |
|----|---------|------------|----------|
| 1 | 1 | 2010-04-26 | NULL |
| 2 | 1 | 2010-04-27 | NULL |
| 3 | 2 | 2010-04-28 | NULL |
| 4 | 3 | 2010-04-28 | NULL |
To this (note that created_at is used for ordering, and sequence is "grouped" by type_id):
| id | type_id | created_at | sequence |
|----|---------|------------|----------|
| 1 | 1 | 2010-04-26 | 1 |
| 2 | 1 | 2010-04-27 | 2 |
| 3 | 2 | 2010-04-28 | 1 |
| 4 | 3 | 2010-04-28 | 1 |
Same question has been raised but for SQL Server.
Link
Thanks.
You can use ROW_NUMBER() to get sequence number per type_id slice. Use a CTE to make UPDATE operation simpler:
;WITH ToUpdate AS (
SELECT id, type_id, created_at, sequence,
ROW_NUMBER() OVER (PARTITION BY type_id ORDER BY created_at) AS newSeq
FROM mytable
)
UPDATE ToUpdate
SET sequence = newSeq
Demo here