How to Efficiently Query Multiple Columns from Different Tables in SQL?

Optimizing Multi-Table, Multi-Column SQL Queries

Retrieving data from multiple tables often presents challenges, especially when needing to aggregate values from various columns. A recent support case highlighted a user's difficulty in accurately counting values across multiple columns in two tables. Their initial attempt, using nested subqueries, yielded incorrect results.

The flawed query looked like this:

<code class="language-sql">SELECT * from
    ( SELECT COUNT(DAY_IN) AS arr FROM t_hospital WHERE DAY_IN between @start_check and @finish_check and RES_DATE between @start_res and @finish_res and ID_daily_hos =@daily_hos group by DAY_IN )e,
    (SELECT COUNT(PAT_STATUS) AS ONG1 FROM t_hospital WHERE PAT_STATUS like '%ong%' and DAY_IN between @start_check and @finish_check and RES_DATE between @start_res and @finish_res and ID_daily_hos =@daily_hos group by DAY_IN ) a,
    (SELECT COUNT(PAT_STATUS) AS RTED FROM t_hospital WHERE PAT_STATUS like '%rtde%'and DAY_IN between @start_check and @finish_check and RES_DATE between @start_res and @finish_res and ID_daily_hos =@daily_hos group by DAY_IN )b,
    (SELECT COUNT(PAT_STATUS) AS POLI FROM t_hospital WHERE PAT_STATUS like '%pol%'and DAY_IN between @start_check and @finish_check and RES_DATE between @start_res and @finish_res and ID_daily_hos =@daily_hos group by DAY_IN )c,
    (SELECT COUNT(PAT_STATUS) AS para FROM t_hospital WHERE PAT_STATUS like '%para%' and DAY_IN between @start_check and @finish_check and RES_DATE between @start_res and @finish_res and ID_daily_hos =@daily_hos group by DAY_IN )d</code>

The solution lies in using conditional aggregation within a single query. This streamlined approach calculates multiple columns based on specified conditions, providing accurate results. The improved query is:

<code class="language-sql">SELECT DAY_IN, COUNT(*) AS arr,
        SUM(IF(PAT_STATUS like '%ong%', 1, 0)) AS ONG1,
        SUM(IF(PAT_STATUS like '%rtde%', 1, 0)) AS RTED,
        SUM(IF(PAT_STATUS like '%pol%', 1, 0)) AS POL1,
        SUM(IF(PAT_STATUS like '%para%', 1, 0)) AS para
FROM t_hospital 
WHERE DAY_IN between @start_check and @finish_check 
    and RES_DATE between @start_res and @finish_res  
    and ID_daily_hos =@daily_hos
GROUP BY DAY_IN</code>

This revised query efficiently retrieves the necessary data, eliminating the errors associated with the original, overly complex structure. The key is consolidating the calculations into a single, well-structured query using conditional SUM() statements.

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