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Learn how to prevent duplicated results in PostgreSQL JSON aggregation while constructing complex JSON objects from SQL queries. Discover effective subqueries to optimize your data retrieval.
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Resolving Duplicate Results in PostgreSQL with json_agg

When working with PostgreSQL, a common challenge is encountering duplicate results while attempting to aggregate JSON data. This issue often arises when using json_agg in combination with multiple JOIN statements. In this post, we will explore a specific problem related to duplicate results in a PostgreSQL query and provide a clear, organized solution.

Understanding the Problem

Imagine you have constructed an SQL query involving various tables related to businesses, including details about both legal and physical persons, their representatives, and observations. The intention is to generate a JSON object that captures all this information in a single, well-structured output.

However, when executing your query, you notice that the representants and observations arrays in the resulting JSON are duplicated. For example, instead of returning distinct names and IDs, your result might look like this:

[[See Video to Reveal this Text or Code Snippet]]

This demonstrates that the JOIN operations are resulting in a Cartesian product, leading to unintended duplicates in the json_agg results.

The Solution

To prevent duplicates in your JSON arrays, we can utilize subqueries. By restructuring our SQL query to employ subqueries for representants and observations, we can ensure that these JSON arrays are populated independently and yield accurate, distinct values.

Revised Query Structure

Here's the amended version of your original query that effectively utilizes subqueries:

[[See Video to Reveal this Text or Code Snippet]]

Key Changes Explained

Subqueries for Aggregation:

Instead of aggregating representants and observations in the main query block, we now call separate subqueries that isolate these aggregations. This structure prevents the Cartesian product effect caused by the JOINs.

Handling Empty Arrays:

To handle potential nulls where no records exist for representants or observations, consider wrapping your subqueries in the COALESCE function, like this:

[[See Video to Reveal this Text or Code Snippet]]

Benefits of this Approach

Performance: Reducing unnecessary JOIN operations can improve the performance of your SQL queries.

Clarity: Each JSON array is constructed in isolation, which helps maintain the clarity and accuracy of the resulting data structure.

Flexibility: This approach allows for easier modifications in the future, as the logic for each data fetch is encapsulated in its own subquery.

Conclusion

Encountering duplicated results while using json_agg in PostgreSQL can be perplexing, but understanding the cause—rooted in the behaviors of JOIN operations—helps pave the way for effective solutions. By leveraging subqueries for aggregation, you can create clean, distinct arrays in your JSON output.

If you found this guide helpful or have additional questions, feel free to leave a comment below!