I was really pleased to see the announcement by Oracle MySQL yum repositories that they have now produced a yum repository from where the MySQL RPMs they provide can be downloaded. This makes keeping up to date much easier. Many companies setup internal yum repositories with the software they need as then updating servers is much easier and can be done with a simple command. For many people at home that means you set this up once and don’t need to check for updates and do manual downloads, but can do a quick yum update xxxx and you get the latest version. Great! This new yum repository only covers RHEL6 did not include RHEL5 which is not yet end of life and still used by me and probably quite a lot of other people. I filed bug#70773 to ask for RHEL5 support to be …[Read more]
I've written a few times about database consistency before,
mainly in conjunction with NoSQL and the concept of Eventual
consistency. Now, I'm about to do an update on the subject, as I
have come to realize a few things.
From an oldtimer like myself, having been an SQL guy for 25 years, I remember Punk-rock and even The Beatles and I having hair growing out of my ears, what can be contributed? Well, let me beging with stating what I mean when I say Database consistency. What I mean is Consistency as the C in ACID (no, we aren't talking drugs here, we are talking databases). Let's see what the online authorative reference work on just about anything on this planet, from the size of J-Lo's feet to the number of Atoms in the universe (those two numbers are quite far apart by the way), Wikipedia: "The consistency property ensures that any transaction will bring the database from one valid state to another. Any data written to the database …
Having just written an interview response about NoSQL concepts for a RDBMS audience it was poetic that an inconspicuous title “(4 of 3)” highlights that both a MySQL read scalable implementation via replication and a NoSQL solution can share a common lack of timely consistency of data. For the sake of Group Commit I hope my data is always consistent at some location at some point in time as soon as possible.
In attempting to comment to Kristian Nielsen’s Fixing MySQL group commit (part 4 of 3) I was forced to watch an ad before I could even add a comment. Go jump Live Journal, it’s quicker to write my own blog post.
And if anybody is still reading, I had just written the following.
“There is clearly a place for NoSQL solutions. The two primary types of products are a key/value store and a schema-less solution. You need to learn …[Read more]
We all knew that we are risking with MMM. Risking, and placing availability as a more important like consistency. But non of us can risk loosing data forever but we show using it, regarding to our conversations think: "I can fix my data later on, but I can’t turn back time and prevent the downtime. (Pascal Hofmann@xaprb.com)".
As I wrote before about staying online, now let me write about how to stay consistent.
We all know, mmm is not like a key of salvation, but its getting close to it . While MySQL doesn't support multi-master-slave environments from it's source code, we will sleep badly wondering on the safety of our precious databases.
But its not just about MMM, a few days ago we ran in to a well known InnoDB "feature". Its about the auto increment counter determination on restart. InnoDB try to count the next auto increment value on MySQL restart what can screw up things in the replication as in your …[Read more]
In the first article in this series on archiving strategies for online transaction processing (OLTP) database servers, I covered some basics: why to archive, and what to consider when gathering requirements for the archived data itself. This article is more technical. I want to help you understand how to choose which rows are archivable, and how to deal with complex data relationships and dependencies. In that context, I'll also discuss a few concrete archiving strategies, their strengths and shortcomings, and how they can satisfy your requirements, especially requirements for data consistency, which as you will see is one of the most difficult problems in archiving.