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SQL update columns with sum() and group by

In this page, we are going to discuss, how to change the data of the columns with the SQL UPDATE statement using aggregate function SUM() and GROUP BY clause.

Example:

Sample table : customer1
+-----------+-------------+-------------+--------------+--------------+-------+-------------+-------------+-------------+---------------+--------------+------------+  
|CUST_CODE  | CUST_NAME   | CUST_CITY   | WORKING_AREA | CUST_COUNTRY | GRADE | OPENING_AMT | RECEIVE_AMT | PAYMENT_AMT |OUTSTANDING_AMT| PHONE_NO     | AGENT_CODE |
+-----------+-------------+-------------+--------------+--------------+-------+-------------+-------------+-------------+---------------+--------------+------------+
| C00013    | Holmes      | London      | London       | UK           |     2 |     6000.00 |     5000.00 |     7000.00 |       4000.00 | BBBBBBB      | A003       |
| C00001    | Micheal     | New York    | New York     | USA          |     2 |     3000.00 |     5000.00 |     2000.00 |       6000.00 | CCCCCCC      | A008       |
| C00020    | Albert      | New York    | New York     | USA          |     3 |     5000.00 |     7000.00 |     6000.00 |       6000.00 | BBBBSBB      | A008       |
| C00025    | Ravindran   | Bangalore   | Bangalore    | India        |     2 |     5000.00 |     7000.00 |     4000.00 |       8000.00 | AVAVAVA      | A011       |
| C00024    | Cook        | London      | London       | UK           |     2 |     4000.00 |     9000.00 |     7000.00 |       6000.00 | FSDDSDF      | A006       |
| C00015    | Stuart      | London      | London       | UK           |     1 |     6000.00 |     8000.00 |     3000.00 |      11000.00 | GFSGERS      | A003       |
| C00002    | Bolt        | New York    | New York     | USA          |     3 |     5000.00 |     7000.00 |     9000.00 |       3000.00 | DDNRDRH      | A008       |
| C00018    | Fleming     | Brisban     | Brisban      | Australia    |     2 |     7000.00 |     7000.00 |     9000.00 |       5000.00 | NHBGVFC      | A005       |
| C00021    | Jacks       | Brisban     | Brisban      | Australia    |     1 |     7000.00 |     7000.00 |     7000.00 |       7000.00 | WERTGDF      | A005       |
| C00019    | Yearannaidu | Chennai     | Chennai      | India        |     1 |     8000.00 |     7000.00 |     7000.00 |       8000.00 | ZZZZBFV      | A010       |
| C00005    | Sasikant    | Mumbai      | Mumbai       | India        |     1 |     7000.00 |    11000.00 |     7000.00 |      11000.00 | 147-25896312 | A002       |
| C00007    | Ramanathan  | Chennai     | Chennai      | India        |     1 |     7000.00 |    11000.00 |     9000.00 |       9000.00 | GHRDWSD      | A010       |
| C00022    | Avinash     | Mumbai      | Mumbai       | India        |     2 |     7000.00 |    11000.00 |     9000.00 |       9000.00 | 113-12345678 | A002       |
| C00004    | Winston     | Brisban     | Brisban      | Australia    |     1 |     5000.00 |     8000.00 |     7000.00 |       6000.00 | AAAAAAA      | A005       |
| C00023    | Karl        | London      | London       | UK           |     0 |     4000.00 |     6000.00 |     7000.00 |       3000.00 | AAAABAA      | A006       |
| C00006    | Shilton     | Torento     | Torento      | Canada       |     1 |    10000.00 |     7000.00 |     6000.00 |      11000.00 | DDDDDDD      | A004       |
| C00010    | Charles     | Hampshair   | Hampshair    | UK           |     3 |     6000.00 |     4000.00 |     5000.00 |       5000.00 | MMMMMMM      | A009       |
| C00017    | Srinivas    | Bangalore   | Bangalore    | India        |     2 |     8000.00 |     4000.00 |     3000.00 |       9000.00 | AAAAAAB      | A007       |
| C00012    | Steven      | San Jose    | San Jose     | USA          |     1 |     5000.00 |     7000.00 |     9000.00 |       3000.00 | KRFYGJK      | A012       |
| C00008    | Karolina    | Torento     | Torento      | Canada       |     1 |     7000.00 |     7000.00 |     9000.00 |       5000.00 | HJKORED      | A004       |
| C00003    | Martin      | Torento     | Torento      | Canada       |     2 |     8000.00 |     7000.00 |     7000.00 |       8000.00 | MJYURFD      | A004       |
| C00009    | Ramesh      | Mumbai      | Mumbai       | India        |     3 |     8000.00 |     7000.00 |     3000.00 |      12000.00 | Phone No     | A002       |
| C00014    | Rangarappa  | Bangalore   | Bangalore    | India        |     2 |     8000.00 |    11000.00 |     7000.00 |      12000.00 | AAAATGF      | A001       |
| C00016    | Venkatpati  | Bangalore   | Bangalore    | India        |     2 |     8000.00 |    11000.00 |     7000.00 |      12000.00 | JRTVFDD      | A007       |
| C00011    | Sundariya   | Chennai     | Chennai      | India        |     3 |     7000.00 |    11000.00 |     7000.00 |      11000.00 | PPHGRTS      | A010       |
+-----------+-------------+-------------+--------------+--------------+-------+-------------+-------------+-------------+---------------+--------------+------------+
Sample table: orders
   ORD_NUM ORD_AMOUNT ADVANCE_AMOUNT ORD_DATE  CUST_CODE       AGENT_CODE      ORD_DESCRIPTION
---------- ---------- -------------- --------- --------------- --------------- -----------------
    200114       3500           2000 15-AUG-08 C00002          A008
    200122       2500            400 16-SEP-08 C00003          A004
    200118        500            100 20-JUL-08 C00023          A006
    200119       4000            700 16-SEP-08 C00007          A010
    200121       1500            600 23-SEP-08 C00008          A004
    200130       2500            400 30-JUL-08 C00025          A011
    200134       4200           1800 25-SEP-08 C00004          A005
    200108       4000            600 15-FEB-08 C00008          A004
    200103       1500            700 15-MAY-08 C00021          A005
    200105       2500            500 18-JUL-08 C00025          A011
    200109       3500            800 30-JUL-08 C00011          A010
    200101       3000           1000 15-JUL-08 C00001          A008
    200111       1000            300 10-JUL-08 C00020          A008
    200104       1500            500 13-MAR-08 C00006          A004
    200106       2500            700 20-APR-08 C00005          A002
    200125       2000            600 10-OCT-08 C00018          A005
    200117        800            200 20-OCT-08 C00014          A001
    200123        500            100 16-SEP-08 C00022          A002
    200120        500            100 20-JUL-08 C00009          A002
    200116        500            100 13-JUL-08 C00010          A009
    200124        500            100 20-JUN-08 C00017          A007
    200126        500            100 24-JUN-08 C00022          A002
    200129       2500            500 20-JUL-08 C00024          A006
    200127       2500            400 20-JUL-08 C00015          A003
    200128       3500           1500 20-JUL-08 C00009          A002
    200135       2000            800 16-SEP-08 C00007          A010
    200131        900            150 26-AUG-08 C00012          A012
    200133       1200            400 29-JUN-08 C00009          A002
    200100       1000            600 08-JAN-08 C00015          A003
    200110       3000            500 15-APR-08 C00019          A010
    200107       4500            900 30-AUG-08 C00007          A010
    200112       2000            400 30-MAY-08 C00016          A007
    200113       4000            600 10-JUN-08 C00022          A002
    200102       2000            300 25-MAY-08 C00012          A012

To change the value of 'outstanding_amt' of 'customer1' table with following conditions -

1. modified value for 'outstanding_amt' is 0,

2. sum of 'ord_amount' from 'orders' table must be greater than 5000 which satisfies the condition bellow:

3. unique 'cust_code' of 'customer1' makes a group,

4. and 'cust_code' of 'customer1' and 'orders' must be same,

the following SQL statement can be used:

SQL Code:


-- This SQL code updates the 'outstanding_amt' column in the 'customer1' table to 0 for customers whose total order amount exceeds 5000.
-- UPDATE statement begins
UPDATE customer1
-- Specifies the target table 'customer1' where the data will be updated
SET outstanding_amt=0
-- Sets the value of the 'outstanding_amt' column to 0 for rows that meet the specified condition
WHERE (SELECT SUM(ord_amount) FROM orders
-- Subquery calculates the total order amount for each customer
WHERE customer1.cust_code=orders.cust_code
-- Matches customers in 'customer1' with their orders in 'orders' based on 'cust_code'
GROUP BY cust_code )>5000;
-- Specifies the condition for updating rows: only rows where the total order amount for a customer exceeds 5000 will be affected

Explanation:

  • This SQL code uses the UPDATE statement to modify existing records in the 'customer1' table.

  • The UPDATE statement specifies the target table 'customer1' where the update operation will be performed.

  • The SET clause assigns a new value of 0 to the 'outstanding_amt' column for rows that meet the specified condition.

  • The WHERE clause includes a subquery that calculates the total order amount for each customer in the 'customer1' table by joining it with the 'orders' table using the 'cust_code' column.

  • The subquery result is compared to 5000 in the outer WHERE clause to filter rows, ensuring that only customers with a total order amount exceeding 5000 will have their 'outstanding_amt' set to 0.

SQL update columns with NULL

In the following we are going to discuss, how the NULL works with the UPDATE statement.

Example:

Sample table: agents1
+------------+----------------------+--------------------+------------+-----------------+---------+
| AGENT_CODE | AGENT_NAME           | WORKING_AREA       | COMMISSION | PHONE_NO        | COUNTRY |
+------------+----------------------+--------------------+------------+-----------------+---------+
| A007       | Ramasundar           | Bangalore          |       0.15 | 077-25814763    |         |
| A003       | Alex                 | London             |       0.13 | 075-12458969    |         |
| A008       | Alford               | New York           |       0.12 | 044-25874365    |         |
| A011       | Ravi Kumar           | Bangalore          |       0.15 | 077-45625874    |         |
| A010       | Santakumar           | Chennai            |       0.14 | 007-22388644    |         |
| A012       | Lucida               | San Jose           |       0.12 | 044-52981425    |         |
| A005       | Anderson             | Brisban            |       0.13 | 045-21447739    |         |
| A001       | Subbarao             | Bangalore          |       0.14 | 077-12346674    |         |
| A002       | Mukesh               | Mumbai             |       0.11 | 029-12358964    |         |
| A006       | McDen                | London             |       0.15 | 078-22255588    |         |
| A004       | Ivan                 | Torento            |       0.15 | 008-22544166    |         |
| A009       | Benjamin             | Hampshair          |       0.11 | 008-22536178    |         |
+------------+----------------------+--------------------+------------+-----------------+---------+

To update the 'agent1' table with following conditions -

1. modified value for 'phone_no' is NULL,

2. 'commission' must be more than .15,

the following SQL statement can be used :

SQL Code:


-- This SQL code updates the 'phone_no' column in the 'agent1' table to NULL for agents whose commission is greater than or equal to 0.15.
-- UPDATE statement begins
UPDATE agent1
-- Specifies the target table 'agent1' where the data will be updated
SET phone_no=NULL
-- Sets the value of the 'phone_no' column to NULL for rows that meet the specified condition
WHERE commission>=.15;
-- Specifies the condition for updating rows: only rows where the 'commission' column is greater than or equal to 0.15 will be affected

Explanation:

  • This SQL code uses the UPDATE statement to modify existing records in the 'agent1' table.

  • The UPDATE statement specifies the target table 'agent1' where the update operation will be performed.

  • The SET clause assigns a new value of NULL to the 'phone_no' column for rows that meet the specified condition.

  • The WHERE clause filters the rows to be updated, ensuring that only rows where the 'commission' column is greater than or equal to 0.15 will be affected by the update operation.

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