SQL UNION vs UNION ALL: An In-Depth Analysis of Deduplication Mechanisms and Practical Applications

Introduction

In SQL queries, merging multiple result sets is a common requirement, and the UNION and UNION ALL operators are key tools for this purpose. Based on a typical problem scenario, this article delves into the core mechanisms of these operators, particularly their distinct behaviors in handling duplicate records.

Problem Context and Case Analysis

Consider the following query scenario: a user needs to retrieve data from the calls table by left-joining the users table twice, based on the assigned_to and requestor_id fields, and filtering for records with department number 4. The initial query uses UNION to merge the two result sets, but the user has questions about the deduplication mechanism.

The original query code is as follows:

select * from calls
left join users a on calls.assigned_to= a.user_id
where a.dept = 4 
union
select * from calls
left join users r on calls.requestor_id= r.user_id
where r.dept = 4

This query aims to combine the results of two left joins, but the user may be concerned about duplicate records. In fact, the UNION operator automatically removes duplicate rows, which is the fundamental difference from UNION ALL.

Core Differences Between UNION and UNION ALL

The UNION operator, when performing a merge, automatically eliminates duplicate records from the result set. It identifies duplicates by comparing values across all columns; if two rows match completely in every column, they are considered duplicates, and only one is retained. This deduplication mechanism is based on the entire row's values, not individual columns.

In contrast, the UNION ALL operator retains all rows, including duplicates. It simply concatenates the two result sets without any deduplication processing. Therefore, UNION ALL generally offers better performance because it avoids the additional computational overhead required for deduplication.

To illustrate more intuitively, consider this simplified example:

-- Using UNION, removes duplicate rows
SELECT column1 FROM table1
UNION
SELECT column1 FROM table2;

-- Using UNION ALL, retains all rows
SELECT column1 FROM table1
UNION ALL
SELECT column1 FROM table2;

In the first query, if table1 and table2 share the same column1 value, it appears only once in the result set; in the second query, all values are retained, potentially leading to duplicates.

Practical Applications and Performance Considerations

In the user's case, using UNION is appropriate because the query might produce duplicate records (e.g., the same call record matching under both join conditions). UNION ensures no duplicate rows in the final result set, providing a clean data view.

However, if it is certain that the two subqueries will not produce duplicates, or if all rows need to be retained for further analysis, UNION ALL is the better choice. For example, in scenarios like:

-- Assuming subqueries are based on different conditions with no overlap
SELECT * FROM calls WHERE status = 'open'
UNION ALL
SELECT * FROM calls WHERE status = 'closed';

Here, UNION ALL can improve query efficiency, as deduplication might involve sorting and comparisons, increasing time complexity and resource consumption.

Optimization Recommendations and Notes

1. Clarify Requirements: When choosing between UNION and UNION ALL, first determine if deduplication is needed. If data sources may overlap and duplicate records are meaningless, use UNION; otherwise, consider UNION ALL for performance gains.

2. Performance Monitoring: For large datasets, the deduplication process in UNION can become a bottleneck. Analyzing query execution plans helps assess overhead and decide whether to use UNION ALL with subsequent deduplication logic.

3. Code Readability: In complex queries, clearly comment on the rationale for operator selection to aid team collaboration and maintenance.

Conclusion

UNION and UNION ALL are essential tools in SQL for merging result sets, with their core difference lying in deduplication mechanisms. Through this analysis, developers should be able to select the appropriate operator based on specific contexts: UNION for scenarios requiring automatic deduplication, and UNION ALL when performance-sensitive or no deduplication is needed. Proper use of these operators ensures data accuracy and optimizes query performance.