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:
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
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:
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
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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