Why Does GROUP_CONCAT Produce Duplicates After Multiple LEFT JOINs and GROUP BYs?

Understanding Duplicate Output from GROUP_CONCAT with Multiple LEFT JOINs and GROUP BYs

This SQL query uses two LEFT JOINs followed by a GROUP BY clause, resulting in unexpected duplicate values within the GROUP_CONCAT function. The root cause lies in the non-uniqueness of intermediate results from the LEFT JOINs for each user ID.

Several strategies can effectively eliminate these duplicates:

Method 1: Efficient Inner Join Strategy

1. Perform a LEFT JOIN between q1 and q2, followed by a GROUP BY.
2. Repeat this process for q1 and q3.
3. Finally, INNER JOIN the two resulting datasets using the common user_id key. This ensures only unique combinations are considered.

Method 2: Leveraging Scalar Subqueries

1. Employ scalar subqueries within the GROUP BY clause to retrieve the GROUP_CONCAT results directly from q1. This isolates the aggregation to a single table before joining.

Method 3: Cumulative LEFT JOIN Approach

1. Execute a LEFT JOIN between q1 and q2, followed by a GROUP BY.
2. Then, perform another LEFT JOIN on the resulting dataset with q3 and apply another GROUP BY. This method handles the joins sequentially, reducing the risk of duplicate combinations.

Method 4: Preventing Duplicates During LEFT JOINs

1. Begin with a LEFT JOIN of q1 and q2, followed by a GROUP BY.
2. Next, perform a LEFT JOIN with q3 (handling potential many-to-many relationships).
3. Finally, apply a GROUP BY to the combined result, ensuring uniqueness for (user_id, tag) and (user_id, category) pairs.

Important Consideration: Using DISTINCT

While adding DISTINCT to the GROUP_CONCAT function can mitigate duplicates, it's crucial to understand that this is a band-aid solution. The optimal method depends on factors like query performance, data size, and the anticipated level of duplication. The methods described above address the underlying cause, leading to more efficient and reliable results.

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