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Unmasking the Hidden Culprit: The Unexpected Database CPU Load Surge in Magento 2.3 and How to Tame it

Unmasking the Hidden Culprit: The Unexpected Database CPU Load Surge in Magento 2.3 and How to Tame it

Unmasking the Hidden Culprit: The Unexpected Database CPU Load Surge in Magento 2.3 and How to Tame it

The upgrade to Magento 2.3 unexpectedly unleashed a silent predator, an insidious surge in database CPU load that crippled website efficiency. This stealthy assailant, a frequent query linked to the 'Popular Search Term Cache' feature, increases its grip as the size of the search_query table grows. This article delves deep into the heart of the issue, unmasking the hidden culprit and exploring potential solutions to tame this unforeseen adversary.

The Silent Predator: Unraveling the Mystery of the Increased CPU Load

In the realm of eCommerce, where milliseconds can equate to financial success or failure, the sudden surge in database CPU load following an upgrade to Magento 2.3 sent shockwaves through the digital community. The predator lurking behind this rise was a frequent query, a silent but exhaustive process that consumed an alarming amount of computing resources. This phenomenon was not a mere random spike but, disturbingly, seemed proportional to the size of the search_query table. As the table grew, the query, much like a ravenous beast, devoured more CPU load, thereby slowing website transactions and affecting customer experience.

The problem was not just a single query. It was a series of continuous executions of a query embedded within Magento's 'Popular Search Term Cache' feature. The function of this feature, whilst innocent in its intention, is to observe and record popular search terms, thus refining the user experience. However, the execution of this feature came at a heavy cost of performance, especially when the num_results > 0 component was incorporated.

Under the Microscope: Deconstructing the Query Tied to the ‘Popular Search Term Cache’ Feature

The 'Popular Search Term Cache' feature, introduced in Magento 2.3.0, was designed to enhance the overall user experience by monitoring and storing popular search terms. However, this seemingly beneficial feature harbored a latent issue. The integrated query, running with the num_results > 0 part, drastically increased the CPU load, specifically when the row count in the search_query table climbed. This was due to the query's continuous execution, an underlying process that magnified the CPU load's adverse effects.

Indeed, the query in question, "SELECT DISTINCT COUNT(*) FROM search_query AS main_table WHERE (main_table.store_id = 1) AND (num_results > 0)," proved to be the critical link in this chain of events. The DISTINCT operator, when faced with millions of records in the search_query table, was the primary source of the CPU load surge. Hence, the issue was not in the feature's conception but in its intricate workings that led to the unforeseen performance problem.

Caught in the Crosshairs: The Role of num_results in Extended Query Duration

The num_results > 0 part of the query emerged as a key player in this performance issue. This component's inclusion amplified the query's execution duration, resulting in an extended waiting period for the end-users. Tests revealed that removing the num_results > 0 from the query could potentially ease the CPU load. However, such a modification requires careful analysis to ensure it does not impact other aspects of the system.

The num_results component is a critical factor in the query. It determines the number of results returned for each search term. When executing a search, the system should finish the operation within a reasonable timeframe. However, as the size of the search_query table grows, the inclusion of the num_results > 0 part lengthens the query duration, impacting the system's performance.

The issue is evidently more noticeable in larger systems with extensive search_query tables, where the num_results > 0 component's impact is significantly amplified. If left unchecked, this could lead to severe performance issues, impacting overall website efficiency. As such, it becomes crucial to identify a feasible solution to this performance bottleneck, whether it be refining the query structure or employing more advanced methods for managing high search term cardinality.

Dissecting the Execution Function: A Potential Panacea for the Performance Issue?

The performance issue's potent sting lies in the num_results > 0 aspect of the query. This, when included, skyrockets the query duration, leaving the application gasping for breath. However, an intriguing solution swims into our view – the execution function. Overriding the execute function nested in the Magento_CatalogSearch/Controller/Result/Index could be our first light at the end of the tunnel. Yet, like a medical cure, it demands rigorous and precise examination before implementation.

The DISTINCT operator, a key player in the query, has been identified as another potential source of the problem. Its incessant use on the table with millions of records creates a bottleneck, slowing down the system. One might argue that plucking out the DISTINCT operator from the Magento\Search\Model\ResourceModel\Query\Collection could improve performance. But the solution is not so black and white. The performance issue may be an outcome of a larger problem, a high search term cardinality. If that stands true, then we need to gear up for more advanced solutions.

The Quest for a Cure: Advanced Solutions and Workarounds for High Search Term Cardinality

As we wrestle with this high search term cardinality, we must consider innovative yet practical solutions. One such possibility is to asynchronously insert search terms into the table in batches. This method could prevent search requests from slowing down, maintaining the website's optimal efficiency.

Alternatively, we could employ the strategy of inserting only a fraction of search terms, or to cease tracking search terms entirely. While this might seem a drastic measure, unusual problems call for unusual solutions. All we need is a keen sense of application and creativity in our approach.

Before jumping the gun, we need to remember that all these potential solutions require validation through further investigation. The complex machinery of Magento's operations cannot be tampered with lightly. Our quest for a cure must be guided by both urgency and caution.

Persistent Predator: The Performance Issue in Magento 2.4.4-p1 and Future Implications

Despite our best efforts, the performance issue remains a persistent predator across Magento versions, with the issue still plaguing Magento 2.4.4-p1. This problem, previously thought to be contained within the 2.3.4 version, has proven to be a more tenacious adversary than expected.

This persistence underscores the importance of identifying a solution at the earliest possible opportunity. The problem affects not only the website's efficiency but also the functionality of the admin panel, making this issue a double-edged sword cutting into Magento's overall performance.

Looking ahead, the need for a quick yet enduring solution is clear. Whether the answer lies in removing the DISTINCT operator, adjusting the num_results > 0 part of the query, or adapting to high search term cardinality lies in the hands of future investigations.

Yet, one thing is certain: this performance issue needs to be tamed. As we march on this quest for a cure, let us remember that in every problem lies an opportunity – the opportunity to learn, to adapt, and to innovate. The silent predator might have been unmasked, but the battle is far from over.

In conclusion, the unexpected surge in the database CPU load following an upgrade to Magento 2.3.0 has been traced to the seemingly innocuous 'Popular Search Term Cache' feature. With its continuous query execution, particularly the num_results > 0 component, causing a proportional increase in CPU load with the growth of the search_query table, the issue is a clear threat to the efficiency of eCommerce platforms.

Potential solutions include overriding the execution function, considering the role of the DISTINCT operator, and exploring advanced solutions for high search term cardinality, such as asynchronous insertion of search terms or limiting the tracking of search terms.

The problem is persistent, extending into Magento 2.4.4-p1, and requires urgent attention not only for the site's efficiency but also for the smooth functioning of the admin panel.

Therefore, while the silent predator causing the CPU load surge has been unmasked, the journey to taming it is just beginning. Our quest for a solution, guided by both urgency and caution, opens up opportunities for further learning, adaptation, and innovation in the face of this eCommerce challenge.