Add by rows in SQL [closed]

You can do it grouping and filtering.

Let's say, if I want the sum of all the attributes of pedro, I do not see fit to bring the column attributes in the query, why? because I will give you something for this style in case I miss this many times:

    Nombres Attributos  Altura   Gtb    
    Pedro*    0.5         5.1    1.7    
    Pedro*    0.7         5.1    1.7  
    Pedro*    0.5         5.1    1.7  

As you can see, the engine will bring the n records that are from Pedro and even then it will fill the field Gtb with the result of the sum.

what you can do is, group by the common factor of your query, for example: wants to know the sum of the attributes of x people and the height (since the latter does not change, assuming), then your query may look like this:

    SELECT NOMBRES, ALTURA, SUM(Attributos) AS Gtb FROM Atleticos
    /*y el campo por el que quiere filtrar tus resultados*/where NOMBRES in ('Pedro', 'Carla', 'Johan')
    /*agrupas*/ group by NOMBRES, ALTURA,

This will give you the sum of the attributes of Pedro, Carla and Johan.

I hope it serves you!

I suggest you use the update command to update an existing registry value, for example:

update atleticos set gtb = 7 where nombres='Pedro';

The value 7 is the value you want to update in the gtb field.

First, we put together an example like yours:

DECLARE @Tabla TABLE (
    Id          INT IDENTITY,
    Nombres     VARCHAR(255),
    Attributos  NUMERIC(15,2),
    Altura      NUMERIC(15,2),
    Gtb         NUMERIC(15,2)
)

INSERT INTO @Tabla (Nombres, Attributos, Altura)
VALUES  ('Pedro*', 0.5, 5.1),
    ('Anna', 0.6, 4.3),
    ('Carla*', 0.3, 6.4),
    ('Johan*', 0.4, 3.4),
    ('Bryan', 10, 6),        
    ('Cecilia*', 5, 5.7)

It is fundamental that the input table has a unique ID for each row, in this case we simulate it with a Id INT IDENTITY . The next thing is to create a temporary table where we will store the result of the accumulated sum, we need to do this to then update the final table:

DECLARE @TablaResultados TABLE (
    Id          INT,
    Nombres     VARCHAR(255),
    Gtb         NUMERIC(15,2)
)

Now we do a query to achieve the accumulated sum but only of certain records, this is an example, note that I am simply selecting those rows where Nombres contain an asterisk, the actual filter you will configure it with what corresponds:

;
WITH CTE AS (
    SELECT  Id,
        Nombres,
        Attributos,
        ROW_NUMBER() OVER (ORDER BY Id) RN
        FROM @Tabla
        WHERE CHARINDEX('*', Nombres) > 0
)
INSERT INTO @TablaResultados ( Id, Nombres, Gtb)
SELECT  T1.Id,
    T1.Nombres,
    SUM(T2.Attributos) AS 'Gtb'
    FROM CTE T1
    LEFT JOIN CTE T2
        ON T2.RN <= T1.RN
    GROUP BY    
        T1.Id,
        T1.Nombres

We use a "Common table expression" so as not to repeat queries, the idea is that for each row we will make a LEFT JOIN with the same rows whose number is equal or previous. Here it is fundamental to establish the Order, although the final accumulated is always the same, each partial will depend on the order that we establish by ROW_NUMBER() OVER (ORDER BY Id) RN . in this case I use the ID of each original record.

If we review, the result would be something like this:

╔══════╦══════════╦══════╗
║ Id   ║ Nombres  ║ Gtb  ║
╠══════╬══════════╬══════╣
║ 1,00 ║ Pedro*   ║ 0,50 ║
╠══════╬══════════╬══════╣
║ 3,00 ║ Carla*   ║ 0,80 ║
╠══════╬══════════╬══════╣
║ 4,00 ║ Johan*   ║ 1,20 ║
╠══════╬══════════╬══════╣
║ 6,00 ║ Cecilia* ║ 6,20 ║
╚══════╩══════════╩══════╝

And now, we use the temporary variable type @TablaResultados to update the final table, only those rows that we have originally filtered

UPDATE  @Tabla
    SET Gtb = T2.Gtb
    FROM @Tabla T1
    INNER JOIN @TablaResultados T2
        ON T1.Id = T2.Id 

SELECT  *
    FROM @Tabla

The final result:

╔══════╦══════════╦════════════╦════════╦══════╗
║ Id   ║ Nombres  ║ Attributos ║ Altura ║ Gtb  ║
╠══════╬══════════╬════════════╬════════╬══════╣
║ 1,00 ║ Pedro*   ║ 0,50       ║ 5,10   ║ 0,50 ║
╠══════╬══════════╬════════════╬════════╬══════╣
║ 2,00 ║ Anna     ║ 0,60       ║ 4,30   ║      ║
╠══════╬══════════╬════════════╬════════╬══════╣
║ 3,00 ║ Carla*   ║ 0,30       ║ 6,40   ║ 0,80 ║
╠══════╬══════════╬════════════╬════════╬══════╣
║ 4,00 ║ Johan*   ║ 0,40       ║ 3,40   ║ 1,20 ║
╠══════╬══════════╬════════════╬════════╬══════╣
║ 5,00 ║ Bryan    ║ 10,00      ║ 6,00   ║      ║
╠══════╬══════════╬════════════╬════════╬══════╣
║ 6,00 ║ Cecilia* ║ 5,00       ║ 5,70   ║ 6,20 ║
╚══════╩══════════╩════════════╩════════╩══════╝