Finding MAX value for two different time ranges in one day PostgreSQL

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As a professional technical blogger, I’ll be exploring how to find the maximum values for production counts in two different time ranges - day shift (7AM to 7PM) and night shift (7PM to 7AM) - within a single query. We’ll delve into the intricacies of PostgreSQL queries, exploring alternative approaches and optimizing our solution.

Understanding Time Ranges

To approach this problem, we first need to understand how time ranges are represented in PostgreSQL. The t_stamp column in the eight_ft_stacker_counts table contains timestamps, which can be used to extract the hour of the day using the extract(HOUR FROM t_stamp) function.

Existing Queries

The original query provided by the user attempts to achieve the desired result using a UNION operator. This approach results in two separate queries being executed, one for each time range. While this works, it has limitations, such as returning multiple values per day.

{< highlight sql >}
SELECT 
    DATE(t_stamp) as t_stamp, 
    MAX("Stacker_8ft_Ongrade_Units") as "Day Ongrade Units", 
    MAX("Stacker_8ft_Downgrade_Units") as "Day Downgrade Units", 
    MAX("Stacker_8ft_Ongrade_Panels") as "Day Ongrade Panels", 
    MAX("Stacker_8ft_Downgrade_Panels") as "Day Downgrade Panels", 
    MAX("Stacker_8ft_Ongrade_Panels") + MAX("Stacker_8ft_Downgrade_Panels") as "Day Total Panels" 
FROM eight_ft_stacker_counts 
WHERE "Stacker_8ft_Ongrade_Panels" > 0 AND (extract(HOUR FROM t_stamp) > 07 AND extract(HOUR FROM t_stamp) < 19) AND t_stamp > '2023-07-11 00:00:00' 
GROUP BY DATE(t_stamp)

UNION

SELECT 
    DATE(t_stamp) as t_stamp, 
    MAX("Stacker_8ft_Ongrade_Units") as "Night Ongrade Units", 
    MAX("Stacker_8ft_Downgrade_Units") as "Night Downgrade Units", 
    MAX("Stacker_8ft_Ongrade_Panels") as "Night Ongrade Panels", 
    MAX("Stacker_8ft_Downgrade_Panels") as "Night Downgrade Panels", 
    MAX("Stacker_8ft_Ongrade_Panels") + MAX("Stacker_8ft_Downgrade_Panels") as "Night Total Panels" 
FROM eight_ft_stacker_counts 
WHERE "Stacker_8ft_Ongrade_Panels" > 0 AND (extract(HOUR FROM t_stamp) > 19 OR extract(HOUR FROM t_stamp) < 07) AND t_stamp > '2023-07-11 00:00:00' 
GROUP BY DATE(t_stamp)
ORDER BY DATE(t_stamp);
{/highlight}

Alternative Approaches

One alternative approach to the existing UNION query is to use conditional aggregation. This technique allows us to perform different calculations for each time range, without relying on a UNION operator.

{< highlight sql >}
SELECT 
    DATE(t_stamp) as t_stamp, 
    MAX(CASE WHEN extract(HOUR FROM t_stamp) BETWEEN 7 AND 19 THEN "Stacker_8ft_Ongrade_Panels" END) as "Day Ongrade Panels", 
    MAX(CASE WHEN extract(HOUR FROM t_stamp) BETWEEN 7 AND 19 THEN "Stacker_8ft_Downgrade_Panels" END) as "Day Downgrade Panels", 
    MAX(CASE WHEN extract(HOUR FROM t_stamp) BETWEEN 7 AND 19 THEN "Stacker_8ft_Ongrade_Panels" + "Stacker_8ft_Downgrade_Panels" END) as "Day Total Panels",
    MAX(CASE WHEN extract(HOUR FROM t_stamp) NOT BETWEEN 7 AND 19 THEN "Stacker_8ft_Ongrade_Panels" END) as "Night Ongrade Panels", 
    MAX(CASE WHEN extract(HOUR FROM t_stamp) NOT BETWEEN 7 AND 19 THEN "Stacker_8ft_Downgrade_Panels" END) as "Night Downgrade Panels", 
    MAX(CASE WHEN extract(HOUR FROM t_stamp) NOT BETWEEN 7 AND 19 THEN "Stacker_8ft_Ongrade_Panels" + "Stacker_8ft_Downgrade_Panels" END) as "Night Total Panels"
FROM eight_ft_stacker_counts
GROUP BY DATE(t_stamp);
{/highlight}

Conclusion

In this article, we explored how to find the maximum values for production counts in two different time ranges within a single query. We began by examining the original query provided by the user and discussed its limitations. Then, we introduced alternative approaches using conditional aggregation, which allowed us to perform different calculations for each time range.

By utilizing these techniques, developers can optimize their queries to achieve better performance and improve overall system efficiency. Additionally, understanding the intricacies of PostgreSQL queries helps developers become more proficient in solving complex problems and creating efficient database solutions.

Last modified on 2023-06-16