Question

I have an SQL table that looks like this:

CREATE TABLE diet_watch (
  entry_date date NOT NULL,
  user_id    int default 1,
  weight     double precision NOT NULL
);

INSERT INTO diet_watch VALUES ('2001-01-01', 1, 128.2);
INSERT INTO diet_watch VALUES ('2001-01-02', 1, 121.2);
INSERT INTO diet_watch VALUES ('2001-01-03', 1, 100.6);
INSERT INTO diet_watch VALUES ('2001-01-04', 1, 303.7);
INSERT INTO diet_watch VALUES ('2001-01-05', 1, 121.0);
INSERT INTO diet_watch VALUES ('2001-01-01', 2, 121.0);
INSERT INTO diet_watch VALUES ('2001-01-06', 2, 128.0);
INSERT INTO diet_watch VALUES ('2001-01-07', 2, 138.0);
INSERT INTO diet_watch VALUES ('2001-01-01', 3, 128.2);
INSERT INTO diet_watch VALUES ('2001-01-02', 3, 125.5);
INSERT INTO diet_watch VALUES ('2001-01-03', 3, 112.8);
INSERT INTO diet_watch VALUES ('2001-01-06', 3, 111.2);

I further have this table:

CREATE TABLE summing_period (
    user_id INT NOT NULL, 
    start_date DATE NOT NULL, 
    end_date DATE NOT NULL); 

insert into summing_period VALUES (1, '2001-01-01', '2001-01-03'); 
insert into summing_period VALUES (2, '2001-01-02', '2001-01-06'); 
insert into summing_period VALUES (3, '2001-01-03', '2001-01-06'); 

I want to write a query that returns DISTINCT ROWS with the following columns:

• the user_id
• the sum of the weights in table diet_watch between the specified dates in table summing_period (for the user_id)

So the result of the query based on the data in table summing period should be:

1,350.0
2,128.0
3,224.0

Unfortunately, this time, I have reached the limit of my SQLfu – and I no idea how to even get started in writing the SQL. Ideally, the solution should be ANSI SQL (i.e. db agnostic). however, since I am developing to a PostgreSQL 8.4 backend, if the solution is db centric, it must at least run on PG.

Answer 1

SELECT
    sp.user_id, SUM(dw.weight)
FROM
    summing_period sp,
    diet_watch dw
WHERE
    dw.user_id = sp.user_id AND
    dw.entry_date >= sp.start_date AND
    dw.entry_date <= sp.end_date
GROUP BY
    sp.user_id

What this query does is join each diet_watch row to the row in summing_period that matches its user_id and whose date falls in the summing_period‘s range.

The SELECT then asks for the SUM of the weights for each different user_id (as a result of the GROUP BY user_id).