Using `ARRAY_AGG()` Aggregate Function in PostgreSQL: A Deep Dive into Multiple Cases

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PostgreSQL’s ARRAY_AGG function is a powerful tool for aggregating arrays of data. In this article, we will explore how to use it in multiple cases using the CASE statement.

Introduction

The CASE statement is a fundamental part of SQL that allows us to make decisions based on conditions and return different values accordingly. When combined with the ARRAY_AGG function, we can perform complex aggregations and filtering operations.

In this article, we will focus on using ARRAY_AGG() in multiple cases for the same array. We will explore how to define these cases using the CASE statement and provide examples of how to use it in real-world scenarios.

Background

Before diving into the code, let’s understand some key concepts:

Arrays: In PostgreSQL, arrays are collections of values that can be stored in a single column. They are defined by enclosing values within square brackets [].
Aggregators: Aggregate functions, such as ARRAY_AGG, group rows based on specific columns and return aggregated results.
Case Statements: The CASE statement is used to make decisions based on conditions. It allows us to specify different actions for each condition.

Case 1: Running Campaigns

A campaign is considered “running” if its publish start date was less than a minute ago, or we are currently between the publish start and end dates. We want to use ARRAY_AGG() to aggregate the IDs of campaigns that match these conditions for each row in the publish_queue table.

SELECT 
    publish_queue.message_id,
    (
        SELECT ARRAY_AGG(id) 
        FROM campaign 
        WHERE react_to_publish_queue_id = publish_queue.id
        AND (publish_end_at IS NULL OR publish_start_at BETWEEN NOW() - '1 minute'::interval AND NOW())
    ) AS running_status
FROM publish_queue;

Case 2: Published Campaigns

A campaign is considered “published” if its publish end date is unknown, or we are currently past the publish end date. We want to use ARRAY_AGG() to aggregate the IDs of campaigns that match these conditions for each row in the publish_queue table.

SELECT 
    publish_queue.message_id,
    (
        SELECT ARRAY_AGG(id) 
        FROM campaign 
        WHERE react_to_publish_queue_id = publish_queue.id
        AND (publish_end_at IS NULL OR NOW() > publish_start_at)
    ) AS published_status
FROM publish_queue;

Combining Cases Using `CASE` Statement

To use both cases together, we can use the CASE statement to conditionally apply one case or another. We will use the publish_end_at column to determine which case to apply.

SELECT 
    publish_queue.message_id,
    CASE 
        WHEN publish_end_at IS NULL THEN (
            SELECT ARRAY_AGG(id) 
            FROM campaign 
            WHERE react_to_publish_queue_id = publish_queue.id
            AND (publish_end_at IS NULL OR publish_start_at BETWEEN NOW() - '1 minute'::interval AND NOW())
        )
        ELSE (
            SELECT ARRAY_AGG(id) 
            FROM campaign 
            WHERE react_to_publish_queue_id = publish_queue.id
            AND (publish_end_at IS NOT NULL OR NOW() > publish_start_at)
        )
    END AS running_status,
    CASE 
        WHEN publish_end_at IS NULL THEN (
            SELECT ARRAY_AGG(id) 
            FROM campaign 
            WHERE react_to_publish_queue_id = publish_queue.id
            AND (publish_end_at IS NOT NULL OR NOW() > publish_start_at)
        )
        ELSE (
            SELECT ARRAY_AGG(id) 
            FROM campaign 
            WHERE react_to_publish_queue_id = publish_queue.id
            AND (publish_end_at IS NULL OR publish_start_at BETWEEN NOW() - '1 minute'::interval AND NOW())
        )
    END AS published_status
FROM publish_queue;

Conclusion

In this article, we explored how to use the CASE statement with the ARRAY_AGG() function in PostgreSQL. We defined two cases for aggregating campaign IDs: one for running campaigns and another for published campaigns. By using a combination of conditions and conditional logic, we can perform complex aggregations and filtering operations.

We hope this article has provided you with a deeper understanding of how to use ARRAY_AGG in PostgreSQL and how to tackle more complex data analysis tasks.

Last modified on 2024-09-16

Using ARRAY_AGG() Aggregate Function in PostgreSQL: A Deep Dive into Multiple Cases