Why Doesn't My LEFT JOIN Return Zero Counts for Organizations?

Troubleshooting LEFT JOIN Queries: Zero Counts and Optimization

A common issue when using LEFT JOINs is the failure to return zero counts for certain groups. This often occurs when filtering conditions are placed in the WHERE clause instead of the JOIN clause. This example demonstrates how to correctly structure a LEFT JOIN to ensure all organizations are included, even those with a zero count.

Correcting the LEFT JOIN

The problem arises from incorrectly placing WHERE clauses. Consider this corrected query:

<code class="language-sql">LEFT JOIN exam_items e ON e.organisation_id = o.id
                         AND e.item_template_id = #{sanitize(item_template_id)}
                         AND e.used</code>

Placing filtering conditions (e.item_template_id, e.used) within the JOIN clause ensures that only matching rows are joined. Previously, placing these conditions in the WHERE clause inadvertently transformed the LEFT JOIN into an INNER JOIN, excluding organizations without matching entries.

COUNT(e.id) Behavior

It's crucial to understand that COUNT(*) and COUNT(e.id) always return a numerical value (0 or greater), unlike other aggregate functions which might return NULL. Therefore, using COALESCE to handle NULL values is unnecessary in this case.

Performance Optimization: Aggregate Before Joining

For scenarios where the majority of exam_items rows are counted, a performance enhancement is achieved by pre-aggregating the counts:

<code class="language-sql">LEFT JOIN (
   SELECT organisation_id AS id  -- aliased for simpler join
        , COUNT(*) AS total_used  -- COUNT(*) is generally faster
   FROM   exam_items
   WHERE  item_template_id = #{sanitize(item_template_id)}
   AND    used
   GROUP  BY 1
   ) e USING (id)</code>

This optimized approach first aggregates the counts from exam_items, then performs a simpler join with the organizations table. This can significantly improve query speed, especially with large datasets.

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