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Decoding the Magento 2.3 Upgrade: Unveiling the Mystery of Rising Database CPU Load and Strategies to Counteract

Decoding the Magento 2.3 Upgrade: Unveiling the Mystery of Rising Database CPU Load and Strategies to Counteract

Decoding the Magento 2.3 Upgrade: Unveiling the Mystery of Rising Database CPU Load and Strategies to Counteract

The Magento 2.3 upgrade has inadvertently led to a surge in database CPU load, instigating a myriad of performance issues predominantly owing to a taxing query linked to the Popular Search Term Cache feature. This post sheds light on the complexities of this issue, tracing its roots to the size of the search_query table and the inclusion of the DISTINCT operator, while offering potential countermeasures. We attempt to unravel the challenge, which has pervaded various Magento versions, impacting the user experience and conversion rates, necessitating urgent attention from the Magento development team.

Unraveling the Conundrum: Understanding the Query and Its Impact on Performance

The crux of the quandary lies in a specific, resource-intensive query, particularly associated with the Popular Search Term Cache feature. This query, SELECT DISTINCT COUNT(*) FROM search_query WHERE store_id = 1 AND num_results > 0, has been Identified as the primary catalyst for the sudden surge in the database CPU load following the Magento 2.3 upgrade. The high CPU usage can drastically degrade the overall performance of the website, leading to slower search results and a compromised user experience. Notably, the "num_results > 0" part of the query acts as the main bottleneck, consuming a significant time to execute. The slow-executing query can cause search requests to take an inordinate amount of time, in turn impacting the overall user experience on the website. The consequences are dire, potentially inducing higher bounce rates and lower customer satisfaction, thus affecting conversion rates and revenue generation.

The Role of the Search_query Table: A Deeper Dive into Size and Performance

The performance of the query is directly proportional to the size of the "search_query" table. The larger this table grows, the slower the query becomes – an undesired domino effect that ultimately strains the database and results in sluggish search queries. This table can rapidly accumulate records, leading to millions of unique search terms and associated MySQL inserts, thus exacerbating the performance issue further. The challenge is not merely contained within the confines of a specific Magento version but is consistently observed across different versions, including 2.4.1-p1 and 2.4.5-p4. What's more, the issue stands relevant in the latest Magento version, 2.4.6, and has been replicated on the latest 2.4-develop branch of Magento. This persistent issue is not exclusive to a particular hosting environment or server configuration and can occur on websites irrespective of traffic volumes and database sizes. The CPU usage on the Magento admin panel can skyrocket due to the frequent execution of this slow-performing query.

Dismantling the Query: The Distinct Operator and Its Implications

The DISTINCT operator in the query serves as another major bottleneck in search performance. The "search_query" table already has a unique constraint on the "query_text" and "store_id" columns, thus rendering the DISTINCT operator redundant. It neither contributes to the accuracy of the search results nor improves the performance. On the contrary, it adds unnecessary overhead to the query and slows down performance. Tweaking the query by disposing of the DISTINCT operator can significantly reduce the execution time, without affecting the accuracy of the search results. However, this proposed solution may require further testing to ensure compatibility across different Magento versions. Recognizing and addressing the implications of the DISTINCT operator is a key step towards mitigating the performance issue and optimizing search performance on Magento websites. This understanding paves the way for effective solutions, which we will explore comprehensively in the following sections.

Tracing the Issue Across Versions: A Pan-Magento Phenomenon

The conundrum under investigation is not exclusive to the Magento 2.3 branch, but rather, a pan-Magento phenomenon that has been confirmed and reproduced on the latest 2.4-develop branch as well. This pervasive issue has been reported on multiple Magento versions ranging from 2.3 to 2.4, affecting both the community and commerce versions. The performance problem persists across different versions of Magento, including 2.4.1-p1, 2.4.5-p4, and is still relevant in the latest Magento version, 2.4.6.

Even with various search configurations, the issue of slow search queries persists, making it an omnipresent concern. This cross-version, cross-configuration occurrence indicates that the root cause is more likely linked to the core design of the Magento platform. Consequently, the inconsistent performance affects the overall user experience. High CPU usage on the Magento admin panel, unreasonably long search request times, and slower search results can lead to higher bounce rates and lower customer satisfaction, negatively impacting conversion rates and stressing the need for urgent attention from the Magento development team.

Mitigating the Impact: Optimization Strategies and the Future of Magento Search Performance

How can we mitigate the impact and optimize search performance? The answer lies in a combination of code optimization, database tuning, infrastructure upgrades, and strategic insertions. Possible solutions include:

  • Modifying the isTopSearchResult function in the \Magento\Search\Model\ResourceModel\Query\Collection class.
  • Overriding the execute function in the \Magento\Search\Model\ResourceModel\Query\Collection class.
  • Limiting the tracking of search terms and reducing the size of the search_query table.
  • Asynchronous insertion of search terms in batches.
  • Indexing the 'search_query' table or using Elasticsearch for search-related operations.

These solutions underscore the need for constant refinement and enhancement within the Magento platform. Overcoming this performance issue may necessitate expert Magento developers who can meticulously identify and execute effective solutions. It is crucial to understand that the problem could be complicated by other factors such as inefficient code or poorly optimized database operations, emphasizing the importance of comprehensive understanding of the Magento platform and its underlying technologies. The future success of Magento search performance relies heavily on how efficiently we can address these current issues while preparing for potential future obstacles. Implementing these strategies will not only provide an improved user experience but also amplify conversion rates, forging the path towards a robust and efficient Magento platform.

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