Mysql slave invalidating query cache entries table natural selection dating new york

Your app can survive one slave node going down and still serve the traffic.

Having a strong dependency on a master node (that you cannot scale by simply adding more masters) for your read-only requests is a risky game.

While this approach solves scaling problems, it brings its own set of problems. All writes (like INSERT, UPDATE and DELETE queries and schema ALTERs) go to a master node.

Slaves are connected permanently to a master node and receive updates form it that are then applied to a copy (which happens with a slight delay compared to when master received an update).

This is indeed something we have observed in the My SQL team for a while.

Before we get to the subject of today’s post, let me start with an introduction. It compares incoming queries that start with The ideal scenario for the query cache tends to be largely read-only, where there are a number of very expensive queries which examine millions of rows only to return a few.

Cache miss is handled by a slave database node only. Moving read SQL queries to slave nodes (and adding caching around them) makes your application more resilient to master database problems.We used this approach to improve the behaviour of the code that was responsible for 21% of database queries that were made to a master node when handling GET requests (for instance when viewing a wiki article). A similar fix was applied to a code that was handling talk page edits notifications.Before it the code was making 800 k SELECT queries an hour and they were always performed on a master.Such setup improves the performance of database writes (a master can now focus solely on them, instead of handling reads as well) and reads (more slaves can be added as the application gets more load). But what if we simply build an application in such a way that this tricky read query will simply not be needed. When handling the aforementioned request, we can do the following.Any slave can be taken out of a pool for a maintenance without causing a problem to the application. Let’s take a look at some real life examples…Imagine the typical scenario of a user performing a page edit: Reading from slave shortly after altering the data we’re interested in is a tricky business — we may get data from before the update. Instead of invalidating the cache we update it with the latest data.

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