Breaking the Chains of Slow Performance: Unraveling Magento 2.3 Database CPU Load Spike Mystery and Pioneering Solutions
In the dynamic world of eCommerce, the recent shift to Magento 2.3 has exposed an alarming performance issue, causing sites with high user interaction to experience a sudden uptick in database CPU load. This unsought slowdown is largely attributed to a persistent, time-consuming query related to the 'Popular Search Term Cache' feature. This article aims to dissect this complex issue, pinpoint the elements exacerbating it, and explores potential solutions to restore Magento to its optimal performance.
Unearthing the Root Cause: The Persistent Query Behind Increased CPU Load
The mystery of the sudden CPU load spike in Magento 2.3 is largely linked to a query relating to the Popular Search Term Cache feature. An upgrade to this version resulted in frequent, time-consuming queries linked to this feature, causing a significant strain on the database and slowing down the sites with high search terms.
Interestingly, the performance issue is proportional to the size of the search_query table; the larger the table, the longer the query takes to complete. This problem persists, causing a consistent drain on the system resources while offering little to no benefit in return. As the search_query table continues to accumulate data, the issue becomes more pronounced, affecting both the admin panel and frontend search functionality.
The 'num_results > 0' Condition: A Hidden Culprit of Performance Degradation
A deep dive into the query uncovers the num_results > 0 condition as a significant driver of this performance issue. This seemingly innocuous condition amplifies the duration of the query, exacerbating the CPU load. Removing this condition has been observed to improve query performance significantly, but it's not without its complications.
The num_results > 0 condition is a major contributor to the performance problem, and addressing it requires a delicate balance. While its removal has shown promise, it is not a conclusive solution and further testing is needed to determine any unforeseen impacts. While the num_results > 0 condition is indeed a hidden culprit, it is merely a part of a much larger and more complex issue.
The Workaround: A Temporary Relief to the Magento Performance Conundrum
In response to this vexing issue, a workaround has emerged, providing temporary relief. By overriding the execute function in the Magento_CatalogSearch module, the problematic getCacheableResult part of the code is removed, leaving only the getNotCacheableResult part. This alteration restores the original performance level prior to the implementation of the problematic query in Magento 2.3.
While this workaround has proven effective in some cases, it is by no means a permanent solution. The root cause of the problem lies deeper within the system and requires a more comprehensive resolution. The workaround, while helpful for immediate relief, only treats the symptoms and not the cause of the issue. Nevertheless, it provides an interim respite, allowing for thorough exploration of a more lasting solution to this perplexing Magento performance conundrum.
The Distinct Operator Dilemma: An Unnecessary Burden on Magento's Performance
As we delve into the intricacies of the performance issue, an additional culprit becomes apparent: the DISTINCT operator. This operator, as part of the query SELECT DISTINCT COUNT(*) FROM search_query, has been consistently identified as a source of high CPU usage and slow performance. The issue is particularly noticeable when the search_query table contains a large number of records, as each instance of the DISTINCT operator requires additional computation.
Logically, the DISTINCT operator should be beneficial, ensuring that duplicate values are eliminated, and only unique records are considered. However, in the context of Magento's search_query table, it becomes a computational burden. The table already has a unique constraint on query_text and store_id, rendering the DISTINCT operator unnecessary. In fact, removing the DISTINCT operator can significantly improve keyword search performance, cutting down execution time from 10 seconds to a mere 2-3 seconds.
Probing the Future: The Roadmap for Performance Optimization in Upcoming Magento Releases
This exploration into the performance hitches of Magento has highlighted several crucial areas for improvement. However, the solutions offered thus far, from removing the num_results condition to eliminating the DISTINCT operator, are temporary fixes rather than comprehensive solutions. The search_query table will continue to grow in size, and without significant changes, performance issues will persist.
Fortunately, the performance issue has been confirmed and reproduced in the latest 2.4.x branch of Magento, and it has been reported to the development team for further evaluation and resolution. While we are awaiting an official fix, other extensive solutions need to be considered. These may include asynchronous insertion of search terms in batches, reducing the number of tracked search terms, or reconsidering the need for the Popular Search Term Cache feature.
As we venture into the future of Magento, it is crucial that these performance issues are not merely patched over, but thoroughly addressed. The eCommerce world is dynamic, and a slow performance can significantly hinder user experience, leading to lost opportunities. By addressing the root cause of these issues, we can hope to see a far more optimized performance in the upcoming Magento releases.
In conclusion, understanding the root cause of the performance conundrum in Magento 2.3 has revealed several interesting culprits, including the problematic query linked to the Popular Search Term Cache feature, the num_results > 0 condition, and the unnecessary burden of the DISTINCT operator. However, solutions proposed thus far like overriding the execute function in the Magento_CatalogSearch module or removing the DISTINCT operator are merely temporary workarounds, not comprehensive fixes. As we look ahead, the need for thorough and extensive solutions becomes clear. These might include measures such as asynchronous insertion of search terms in batches, reducing the number of tracked search terms, or even reconsidering the need for the Popular Search Term Cache feature. We anticipate that the Magento development team will diligently address these performance issues in future versions, having acknowledged and reproduced the performance issue in the latest 2.4.x branch.
In conclusion, the journey towards optimal performance in Magento is certainly complex, requiring a deep understanding of the system's nuances as well as an openness to innovation and change. These explorations into the performance issues of Magento 2.3, while enlightening, are just the beginning, and the unfolding conversation promises to bring us closer to a more efficient and effective Magento.