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How Can Raw SQL Enhance the Performance of Complex Rails Queries?

Patricia Arquette
Release: 2025-01-15 09:15:45
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How Can Raw SQL Enhance the Performance of Complex Rails Queries?

Optimizing Complex Rails Queries with Raw SQL

Deploying Rails applications, especially on platforms like Heroku, can sometimes reveal performance bottlenecks stemming from complex database queries. This article demonstrates how using raw SQL can significantly improve the efficiency of such queries.

Leveraging Raw SQL in Rails

Rails provides a mechanism for executing custom SQL directly. This bypasses the ActiveRecord query builder, often resulting in faster execution times. Here's the process:

  1. Construct your SQL query as a string.
  2. Use ActiveRecord::Base.connection.execute to run the query against the database.
  3. The results are returned as an array, ready for processing in your Ruby code.

Illustrative Example

Let's examine a scenario involving joined tables and ordering:

<code class="language-ruby">@payments = PaymentDetail.joins(:project).order('payment_details.created_at desc')
@payment_errors = PaymentError.joins(:project).order('payment_errors.created_at desc')
@all_payments = (@payments + @payment_errors)</code>
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This code joins PaymentDetail and PaymentError tables, ordering the results by the created_at timestamp. The equivalent raw SQL is:

<code class="language-sql">sql = "SELECT * FROM payment_details pd
       LEFT JOIN projects p ON pd.project_id = p.id
       UNION ALL
       SELECT * FROM payment_errors pe
       LEFT JOIN projects p ON pe.project_id = p.id
       ORDER BY created_at DESC"</code>
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Execution is then straightforward:

<code class="language-ruby">records_array = ActiveRecord::Base.connection.execute(sql)</code>
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Performance Gains

Employing raw SQL eliminates the overhead of Rails' Active Record query generation, potentially leading to substantial performance improvements, especially with large datasets. The records_array can be treated like any Ruby array, allowing for seamless integration into your application logic. This technique is particularly valuable when dealing with intricate queries prone to timeouts.

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