"Unmasking Magento's Search Query Dilemma: How the 'Distinct' Operator Burdens Databases and the Potential Fixes You Should Know About"
Magento's upgrade to 2.3 has seemingly led to a surge in database CPU load, largely due to a query related to the search term cache, revealing a significant flaw in its system. The crux of the problem lies in the 'DISTINCT' operator in the search query, which not only is unnecessary given the unique constraint on query_text and store_id, but also remarkably slows down the process. This article delves into the intricate dynamics of the Magento's search query conundrum, and explores how removing this operator, alongside optimizing the insertion of search terms, may significantly enhance performance.
Unraveling the Magento 2.3 Upgrade: Exposing the Root Cause
With the release of Magento 2.3, an unexpected side effect emerged: a sudden surge in database CPU load attributable to a popular search term cache-related query. Data from multiple Magento Commerce 2.3.4 platforms using ElasticSearch 6.7.0 shows the same trend. The query, "SELECT DISTINCT COUNT(*) FROM search_query AS main_table WHERE (main_table.store_id = 1) AND (num_results > 0)," has been the root cause of this CPU load spike.
The larger the
search_query table, the longer the query takes, ranging from 0.7 to a staggering 23 seconds depending on the table size. The main culprit in this slowdown is the 'num_results > 0' condition. What's more, disabling search suggestions from the admin panel does nothing to alleviate the strain, as the main search bar still hits the
search_query table hard.
The 'Distinct' Operator: Unnecessary Complexity in Search Queries
Interestingly, it is the
DISTINCT operator in the query that is unnecessary and burdensome. As the
search_query table in Magento has a unique constraint on
DISTINCT operator is redundant and significantly slows down the process. The persistent use of this operator in queries within Magento's Search\Model\ResourceModel\Query\Collection not only does not improve performance, but in fact, conversely impacts it negatively.
DISTINCT operator, a common face in database queries, is used to return unique values in the output, eliminating duplicates from the result set. However, when already faced with a unique constraint, its presence is not only unnecessary but also a needless complexity that hinders query performance.
The Impact of the Search Term Cache: A Closer Look at CPU Load and Query Times
search_query table grows rapidly, putting a vast strain on the database and resulting in slow queries, particularly for sites with a large number of search terms. With the table sometimes reaching hundreds of thousands, or even millions of entries, it can lead to slow query times, notably impacting website performance.
What's more, the continuous execution of our query of interest in the admin panel leads to high CPU usage. The correlation between CPU load and the size of the
search_query table is undeniable, as is the impact of the
DISTINCT operator in exacerbating the issue.
Interestingly, it's not just Magento 2.3 that is affected. The problem has been replicated on the latest 2.4-develop branch of Magento and persists in Magento 2.4.1-p1, Magento 2.4.2-p2, Magento 2.4.4-p1, and Magento 2.4.5-p4. In other words, this is not a one-time issue. It's a persistent problem that needs urgent attention.
The search term cache feature, designed to improve user experience by storing popular search terms, has ironically turned into a cause for performance issues. The feature inadvertently causes high CPU usage and slow query times, particularly on sites with a large number of search terms. As such, this functionality, which should be enhancing the shopping experience, ends up slowing it down.
The Persistent Problem: Understanding Magento's P2 Defect Status and Future Implications
An interesting and perplexing aspect of Magento's search query problem is its persistent nature, it continues to haunt various versions of Magento even after multiple updates. This issue, identified as a P2 defect, remains pertinent in as late versions as Magento 2.4.4-p2, and Magento 2.4.5-p4, causing high CPU usage and prolonged query times despite several attempted fixes, including the proposed c90edaa patch.
The search term cache feature, a central component to this issue, is particularly problematic. Even with hundreds of thousands, and sometimes millions of search terms, disabling search suggestions from the admin panel doesn't prevent the main search bar from hitting the search_query table, contributing to a significant CPU load on the servers. The more the entries in the search_query table, the more sluggish the queries become, with durations ranging from a somewhat bearable 0.7 seconds to an crippling 23 seconds.
Interestingly, the complexity introduced by the 'DISTINCT' operator in the SQL query: SELECT DISTINCT COUNT(*) FROM search_query AS main_table WHERE (main_table.store_id = 1) AND (num_results > 0), only adds to the load, which brings us to potential solutions that could alleviate this persistent issue.
Proposed Solutions: Overriding Functions and Asynchronous Insertions
To address the pervasive search query predicament, the Magento community has proposed multiple solutions that could potentially improve performance. The first suggests overriding the execute function in Magento_CatalogSearch/Controller/Result/Index to revert changes made in the 2.3 upgrades, thereby eliminating the excess load caused by the DISTINCT operator.
However, another more systematic approach focuses on the way search terms are inserted into the search_query table. By asynchronously inserting search terms into the table in batches, the system can prevent slowdowns during search requests, reducing the strain on the database and CPU. This approach might be more viable as it addresses the issue directly at its root, rather than trying to mitigate its effects afterward.
Towards an Optimized Magento: Removing the 'Distinct' Operator and Streamlining Search Term Insertion
Considering the distinctive constraint on query_text and store_id, the DISTINCT operator in the query doesn’t provide any added benefit, in fact, it significantly hampers performance. Consequently, one of the most straightforward and effective solutions lies in removing the DISTINCT operator from the query. This operator's removal within Magento\Search\Model\ResourceModel\Query\Collection has been repeatedly demonstrated to significantly improve the query performance.
In addition to this, streamlining search term insertion is integral in curbing the problem. By only inserting a fraction of the search terms or entirely stopping their tracking, the system could enhance its efficiency and reduce the load on the database and CPU.
In conclusion, while Magento's search query problem might be complex and persistent, it's not insurmountable. By implementing systematic changes, like removing the redundant DISTINCT operator and optimizing the insertion of search terms, the Magento community can navigate towards an optimized and efficient system.
In conclusion, Magento's search query conundrum, which has been prevailing across multiple versions of the platform, can be attributed to the unnecessary complexity introduced by the 'DISTINCT' operator and the unoptimized insertion of search terms in the search_query table.
- Firstly, by eliminating the 'DISTINCT' operator from the Magento\Search\Model\ResourceModel\Query\Collection, notable improvement in query performance can be achieved, reducing CPU load, and enhancing the overall system efficiency.
- Secondly, the process of search term insertion needs to be optimized – either by inserting a fraction of search terms or halting their tracking altogether, it's possible to prevent the database and CPU from being burdened.
Thus, while the issue might seem daunting, the solutions lie in systematic changes to the core functions of Magento. By prudently addressing these, the Magento community can pave the way towards an optimized, efficient, and robust system, improving not just the platform's performance, but also the user experience. These necessary fixes underscore the importance of ongoing vigilance in the face of persistent technical challenges.