Can a Single Join Replace Multiple Subqueries for Efficient Row Counting in Database Optimization?

A One-Query Count for Each Join Optimization

In database optimization, it's crucial to minimize joins. Each additional join multiplies the processing cost, resulting in a large matrix calculation that can be challenging for the database engine. However, it's possible to optimize queries by counting with a single join.

Consider the task of counting the number of rows resulting from joins between tables in a specific scenario. While using multiple subqueries for separate joins is a straightforward approach, it's worth exploring whether a single query could be more efficient.

To achieve this, the tables involved must have unique keys and the joining field (e.g., "idAlb") must be a unique key for the primary table (e.g., "album"). With these conditions met, it's possible to use a modified version of the original query:

select alb.titreAlb as "Titre",
       count(distinct payalb.idAlb, payalb.PrimaryKeyFields) "Pays",
       count(distinct peralb.idAlb, peralb.PrimaryKeyFields) "Personnages",
       count(distinct juralb.idAlb, juralb.PrimaryKeyFields) "Jurons"
from album alb
left join pays_album payalb using ( idAlb )
left join pers_album peralb using ( idAlb )
left join juron_album juralb using ( idAlb )
where alb.titreAlb = "LES CIGARES DU PHARAON"
group by alb.titreAlb

In this query, "PrimaryKeyFields" represents the primary key fields of the joined tables. Using the "distinct" keyword eliminates duplicate counts and helps optimize costs. However, it's important to note that in general, using "distinct" will not completely remove the costs associated with the joins themselves.

If optimal indexes covering the necessary fields are in place, this approach may perform as well as the subquery solution. However, in most cases, it's more likely to be less efficient due to the database engine's need to find the optimal execution strategy. It's recommended to test and analyze the EXPLAIN plans for both approaches to determine the most optimal solution for the specific database setup and dataset.

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