Many Database Administrators have noticed that Memcache brings a few issues with it. One, it is passive as it shares cached data every time - meaning applications that utilize Memcache require special logic to take care of anything missing from the cache.
Also, one needs to be careful while updating the cache as several data manipulations could be taking place simultaneously. Another thing to keep in mind in such cases is the rise in latency when it comes to constructing cache expired items. This is especially true during optimization of SQL queries when they could just as easily been recovered in the background.
All of the situations and issues mentioned above can be resolved with the help of an active cache. It is an extremely simple concept: for each data fetching the operation, the cache will actually be able to construct the object as it will know how to do so.
This way, you won’t ever get a miss unless there is a different problem altogether. This kind of solution is the best there is at present, particularly when you need to register the jobs with Gearman
Here, the updates regarding data are supposed to pass through the same process to enable the user to fain serialization or whichever logic you prefer for the updates. The user may also apply the same functions to update the information once it expires. It may be exposed as explicit logic for something that may expire in a few hundred seconds and begin anew in another few hundred seconds along with being automated.
The automatic handling logic can be explained like this: once the key expires, we can place it in cache with an indicator that shows it’s expired, after we purge its value. If you want to perform Oracle query performance tuning and can view for the same key, you will receive plenty of requests once its expired cache is enabled to decide whether it will refresh leys like these on the basis of available bandwidth.
Experienced database experts have also suggested an extension to typical caching techniques - specifying max_age for GET requests. For several apps, request-driven expiration is the norm rather than data-driven expiration.
For example, if you’re the user posting comments at the end of a blog, you’ll want to read those comments first to avoid a negative experience. Therefore, if other users are able to read stale information, for instance, if they get to read every comment ten seconds after it’s posted, they won’t have an unpleasant user experience.
Active caches can also be a great help when it comes to optimization in SQL queries and controlling write-back scenarios. Several cases have been detected, where plenty of updates are being carried out on the data like logging in, counters, scoring, and so on, don’t really need to show in the database at that same moment.
If the cache
is programmed to make changes to the information on its own, the user could
easily define the policies on the number of times the information object
syncing must take place with the database. This concept will surely prove
helpful in other ways as well - in some cases, even more so than present tools
and technologies.
