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Unraveling the Mystery of Magento's CPU Overload: Insights, Impact, and Innovative Solutions for Enhanced E-commerce Performance

Unraveling the Mystery of Magento’s CPU Overload: Insights, Impact, and Innovative Solutions for Enhanced E-commerce Performance

Unraveling the Mystery of Magento's CPU Overload: Insights, Impact, and Innovative Solutions for Enhanced E-commerce Performance

In the complex world of e-commerce, the performance of Magento 2.3 and 2.4 versions has come under scrutiny due to a persistent keyword search issue that is causing high CPU usage and impacting both front and back-end performance. Despite various updates, the issue persists, specifically linked to a time-consuming query related to the search_query table. This article delves into the intricacies of this performance issue, exploring its impact on large-scale e-commerce platforms, and the innovative solutions proposed to enhance the overall efficiency of Magento.

An In-depth Analysis of Magento's CPU Overload Problem

The issue of high CPU usage in Magento 2.3 and 2.4 versions primarily stems from a time-consuming query related to the search_query table. This query executes a distinct count from the table, a function that becomes increasingly laborious as the table size expands. Specifically, the trigger for this CPU overload is the condition where num_results > 0, which is particularly time-consuming and straining on the database.

Indeed, the larger the search_query table, the longer the query takes to complete. For instance, on a live site with approximately 2.7 million search terms, the queries can put a significant strain on the database, ultimately slowing down performance. This CPU overload problem is exacerbated by the fact that the issue is associated with the addition of Popular Search Term Cache in Magento 2.3.0, meaning it has been an ongoing problem since this version.

The impact transcends beyond the database and affects both the front-end and back-end performance of Magento, making it a significant issue that requires addressing. It's also important to note that this problem is reproducible even on a vanilla Magento instance, indicating that it's inherent to Magento's operational structure and not merely a result of specific configurations or customizations.

Evaluating the Impact of the High CPU Load on the Performance of Magento 2.3 and 2.4 Versions

Despite various updates and upgrades, the CPU overload problem persists in Magento 2.4.x versions, signifying an underlying issue that's yet to be adequately addressed. This issue impacts the main search bar significantly, even when using ElasticSearch, a popular open-source search and analytics engine.

Interestingly, disabling search suggestions and enabling ElasticSearch does not resolve the problem, as one might expect. Such observations highlight that the CPU overload issue is not only robust but also resistant to traditional performance enhancement strategies. This problem is also present in Magento 2.4.6 Commerce, demonstrating its prevalence across various versions of Magento.

The repercussions of this issue are particularly pronounced when using the keyword search function—an integral component of any e-commerce platform. The keyword search function takes an unacceptably long time to complete, presenting a significant bottleneck in user experience and overall platform efficiency. On a platform with 1.4 million rows in the search_query table, the keyword search function can be shortened from 10 seconds to 2-3 seconds, indicating the considerable impact the CPU overload problem has on performance.

Delving Into the Role of Search_query Table and the Time-Consuming Query

Digging deeper into the crux of the problem, it becomes apparent that the search_query table plays a significant role in this performance issue. The search_query table grows in size due to the frequent and time-consuming query, causing high CPU usage. Specifically, the query "SELECT DISTINCT COUNT(*) FROM search_query AS main_table WHERE (main_table.store_id = 1) AND (num_results > 0)" is the culprit for this CPU overload.

It's worth noting that the DISTINCT operator, used in the query, is redundant, given that the search_query table already has a unique constraint on query_text and store_id. Removing the num_results > 0 condition from the query significantly improves performance, offering a possible solution to the problem.

However, it's not just the redundancy of the DISTINCT operator that's concerning. The c90edaa commit, which does not appear to be a fix for this performance issue, also suggests the problem's depth. Furthermore, the issue persists in Magento 2.4.4-p2, demonstrating the challenge's stubborn nature. The high CPU usage linked to this query is a significant performance issue that Magento needs to address urgently to enhance its overall e-commerce performance.

Assessing ElasticSearch and its Role in the Performance Issue

With the promise of improved performance by facilitating swift and efficient searches, ElasticSearch has been positioned as a viable solution to the ongoing performance issues in Magento 2.3 and 2.4 versions. However, our analysis reveals that the performance issue rears its head even with ElasticSearch enabled, underscoring that the root cause lies deeper.

The problem is linked to the SELECT DISTINCT COUNT(*) query pulling from the search_query table, a persistent and time-consuming operation that continues to put a strain on CPU usage, and ultimately, Magento's performance. This issue directly impacts the keyword search function, causing it to slow down significantly, extending the search time from a bearable 2-3 seconds to an unacceptably long 10 seconds.

Disappointingly, even disabling search suggestions and enabling ElasticSearch does not seem to resolve the problem. The performance issue persists, affecting both the front-end and back-end functioning of Magento, a concern that is reproducible even on a vanilla Magento instance.

Promising Strategies for Enhanced E-commerce Performance: Potential Solutions and Outlook

Given the persistent nature of the performance issues, several solutions have been proposed, focusing on the query and the role of the DISTINCT operator. Modifying the query to remove the DISTINCT operator is one of the suggested solutions, as it is considered redundant due to the unique constraint on query_text and store_id in the search_query table.

Furthermore, altering the $select->distinct(false) in Collection.php has been suggested, which can shorten the keyword search function from 10 seconds to 2-3 seconds, providing some relief from the performance bottleneck. However, the ramifications on other operations are yet to be fully understood.

Another proposed solution involves overriding the execute function in Magento_CatalogSearch/Controller/Result/Index to remove the getCacheableResult part. This action has shown to revert the performance to its pre-update state, providing a temporary respite.

The introduction of asynchronous insertion of search terms in batches may also help mitigate performance issues. Additionally, only inserting a fraction of the search terms or disabling tracking entirely are potential solutions receiving attention.

While these solutions show promise, it is important to note that they are yet to be fully tested and their long-term impact is still unclear. Therefore, as we move forward, continuous monitoring, testing, and iteration will be crucial in finding a robust, scalable solution to Magento's performance issues.

As the e-commerce landscape continues to evolve, the needs for efficient and reliable performance will continue to grow. Therefore, it is imperative for Magento and its community to find a comprehensive solution to this performance issue. Despite the challenges, the journey toward improved performance brings with it opportunities for innovation, highlighting the dynamic nature of the e-commerce industry.

Thus, we arrive at a confluence of intriguing insights, impactful revelations, and innovative solutions surrounding Magento's CPU overload issue. It is evident that:

  • The high CPU usage primarily stems from a resource-intensive query related to the search_query table, specifically when num_results > 0.
  • Despite enabling ElasticSearch and disabling search suggestions, the issue persists, indicating a deeper, inherent flaw within Magento's structure.
  • The DISTINCT operator in the problematic query is redundant and removing it could enhance performance.
  • Solutions include altering the DISTINCT operator in the $select->distinct(false) in Collection.php and implementing asynchronous insertion of search terms in batches.

In conclusion, while the proposed solutions offer a glimmer of hope, their full implications remain to be comprehensively explored. Therefore, it is crucial for Magento's community to continue investigating, testing, and innovating to find a scalable resolution that bolsters Magento's performance, ultimately enhancing its e-commerce capabilities. As we navigate the ever-evolving e-commerce landscape, it's imperative that we approach these challenges not as roadblocks, but as opportunities for growth and innovation. Indeed, it is through such trials that we can truly push the boundaries of what's possible, transforming challenges into catalysts for change and disruption.

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