In PHP, there is a need to implement caching for executed queries to MySQL. However, embedding caching directly into MySQL is not appropriate for several reasons. One major issue is that the cache needs to be reset whenever there is a table change, which is critical in a multi-user system being developed.

One approach I had considered is storing the results of heavy queries in files on the server. Then, during the next request execution (with reference to the system user), checking if there was a previous request and retrieving the result from the file. However, this method poses the challenge of tracking changes in the table.

Do you have any recommendations for an optimal solution for caching SQL queries from PHP? Or perhaps there are other interesting alternatives?

Thank you in advance for your responses!

One common approach to caching SQL queries in PHP is to use a caching layer like Memcached or Redis. These caching systems allow you to store key-value pairs in memory, which can be used to cache the results of SQL queries.

Here's how it could work:

1. Before executing a query, check if the result is already present in the cache by using a unique key for that query. The key could be constructed based on the query itself, including the table name and parameters.

2. If the result is found in the cache, retrieve it from there and skip executing the query.

3. If the result is not found in the cache, execute the query and store the result in the cache using the unique key.

4. When a table change occurs (e.g., an update, insert, or delete operation), you can invalidate the corresponding cached results by removing the associated keys from the cache. This ensures that the cache is updated whenever the underlying data changes.

By using a caching layer, you can significantly reduce the load on your database server and improve the performance of your application. Additionally, it provides a more flexible solution compared to embedding caching directly into MySQL.

Another alternative to consider is query result caching at the application level. Instead of storing results in files, you can use PHP's built-in caching mechanisms, such as APCu or Memcached. These systems allow you to store arbitrary data in memory and retrieve it quickly. However, keep in mind that these caches are typically shared across all users of the application, so you need to be careful about cache invalidation to ensure data consistency.

considerations and alternatives for caching SQL queries in PHP:

1. Query-specific caching: Instead of caching the whole result set, you can consider caching individual query results or specific parts of the result set that are frequently accessed. This can be useful when dealing with large result sets or when only a subset of the data is needed.

2. Time-based expiration: You can set an expiration time for cached query results. This approach ensures that the cache is refreshed periodically, even if no table changes occur. This way, you strike a balance between serving fresh data and minimizing database load.

3. Partial caching: If you have complex queries that involve multiple tables or aggregations, you can consider caching intermediate or partial results instead of the final result. This can help to optimize performance while still accounting for table changes.

4. Query result metadata caching: In addition to caching the query results, you can also cache metadata about the query itself, such as column names and data types. This can help eliminate redundant calls to gather metadata information and improve the efficiency of your application.

5. Database-level caching: Although you mentioned that embedding caching directly into MySQL is not suitable for your scenario, it's worth mentioning that MySQL does offer query cache functionality. However, it comes with its own limitations, and you need to carefully evaluate whether it fits your use case.

The primary reason for not utilizing the normal option is based on false information, although this is not the main concern. It is advisable to create tables-aggregates and examine queries in order to construct indexes. These indexes should be populated with data after contracts have been transitioned to stable statuses. Instead of allocating extra RAM to an unnecessary memcache in this scenario, it is more beneficial to allocate it to a well-designed database.

Contracts expire and periods come to a close, resulting in static data that is easily obtained from aggregates. The cache option is suitable for frequent access to the same data. Consider whether your users consistently retrieve the same contract or if they view different contracts each time. It is likely the latter, and storing these unused contracts in RAM will only occupy valuable space. As mentioned earlier, it is recommended to utilize this RAM for indexes.

One of the primary concerns is to reset the cache whenever there is a change in the table, which is crucial due to the multi-user nature of the system being developed. I have already considered the option of storing the results of complex queries in server files and checking during subsequent request executions if the same query has been made before, in which case it can be retrieved from the file. However, implementing this approach would require addressing the challenge of tracking changes in the table.

It may seem somewhat contradictory that on one hand, I am emphasizing the importance of resetting the cache with every table change, while on the other hand, I am acknowledging the impact of table changes on the cache and the need for monitoring them.

Moving on to potential solutions for caching, one relatively straightforward option is to utilize a memory table in MySQL. This table can store either frequently accessed data or IDs for accessing data from the main tables. One advantage of this approach compared to using third-party solutions is that data can be cached without the need to involve PHP or the network; instead, a simple "insert into select from" operation can be used in most cases. This is the first aspect to consider. Additionally, by utilizing triggers, it is possible to configure more flexible caching updates when the main table undergoes changes, as opposed to relying solely on a static query cache.

Lastly, if the size of the database is relatively small, combining innodb with a large pool/cache size can ensure that the entire database remains constantly accessible in memory.