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Content Tagged replication

Using BASE instead of ACID for scalability

My editor Andy Oram recently sent me an ACM article on BASE, a technique for improving scalability by being willing to give up some other properties of traditional transactional systems.

It’s a really good read. In many ways it is the same religion everyone who’s successfully scaled a system Really Really Big has advocated. But this is different: it’s a very clear article, with a great writing style that really cuts out the fat and teaches the principles without being specific to any environment or sounding egotistical.

He mentions a lot of current thinking in the field, including the CAP principle, which Robert Hodges of Continuent first turned me onto a couple months ago. It has been proven formally, though I have not read the proof myself.

One of the most important concepts he advances is giving up the illusion of control. As programmers and DBAs, I think we may tend to like control too much. Foreign keys are a perfect example. I think the point here is that these things make you feel safe, but they don’t really make you safe. Just as with so many things in life, recognizing our inability to really control the systems we build is key to working with their strengths — instead of trying to bind them with iron bands.

Another great point is idempotency. This is a great way to help avoid problems with MySQL replication, by the way. I’ll leave the “why” as an exercise for the reader, but let me just point out that the file MySQL uses to remember its current position in replication is not synced to disk, so it will almost certainly get out of whack if MySQL dies ungracefully. (Google has solved this problem.)

A highly recommended read — worth more than most case studies about how specific companies have scaled their specific systems.

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MySQL: Planet MySQL

Creating an Intermediate Replication Layer

A few weeks ago, I discussed how to keep binlogs in sync in a tree or pyramid replication scheme. That thread discussed how to re-distribute load in case of failure in one of the intermediate slaves. Today we will look at how to create those intermediate replication slaves. We start with a traditional flat replication [...]

MySQL: Planet MySQL

Falcon Transactional Characteristics

It’s time to continue our series on the transactional storage engines for MySQL. Some might question why I even include Falcon because it is very much beta at this time. MySQL, however, has made quite an investment into Falcon, and while it is currently beta, the code is improving and it looks like that it will be production-worthy when MySQL server 6.0 hits GA.

If this is the case, it is important to begin to understand what Falcon was designed for and how it differs from other transactional engines such as InnoDB. I am going to concentrate quite a bit on the Falcon/InnoDB comparison as that is what everyone wants to talk about. This is despite my having heard MySQL employees repeatedly make statements to the effect of, “Falcon is not going to replace InnoDB,” or “Falcon is not competing with InnoDB.” Well, take that with a grain of salt. It certainly seems to me that they are competing for the same spot.

Warning

As I said, Falcon is beta. First off, don’t even try to use it in production. Using it in production means you will also be using MySQL Server 6.0, which itself is considered alpha. Your data will explode, be corrupted, or eaten by jackals. It won’t be pretty. It will cause great pain.

In addition, the features of Falcon are still changing. What I say here might or might not be accurate in the future.

End of Warning

So, why was Falcon even created?

(more…)

MySQL: Planet MySQL

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