How to Efficiently Aggregate Multiple Columns from Different Tables in a Single MySQL Statement?

Consolidating Data from Multiple Tables with a Single MySQL Query

Initially, using multiple subqueries to aggregate data from various tables yielded inaccurate results, with only the first column showing correct values. To resolve this, a more efficient method is required.

The most effective solution involves conditional aggregation within a single table query. This approach avoids the limitations of multiple subqueries and produces accurate results. The following query demonstrates this technique:

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 query uses the IF() function to conditionally count occurrences based on the PAT_STATUS column. Each row is counted only once, contributing to a single aggregated column. The SUM() function then totals these conditional counts for each DAY_IN.

This single-query approach provides a concise and accurate method for aggregating data from different columns within the same table, thereby resolving the issue of inaccurate results obtained from the original multiple subquery method.

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