I like to have wider images in Cacti, the system we use to monitor our servers.
Specifically, I like to have images that are 750px wide instead of the default 500px. It can be cumbersome to change the templates individually, so the following SQL can be executed against your Cacti database and they’ll all be changed at once:
UPDATE graph_templates_graph SET width = 750 WHERE ID > 0;
I’ve found that some templates can’t jam all their information into a 500px wide image, so this SQL fixes that. It’s annoying having to reverse-engineer the database every time I add a new device template but now I have this post to refer back to.
I came from a Microsoft background, when I was there I complained about some aspects of it, but in hindsight one thing I miss a lot is a good IDE for SQL and database related development. SQL server didn’t have anything amazing, but it did the job and was stable.
I’m a big believer in visualisation and easy visualisation when working with data. It’s there to be used and if you can’t visualise it simply, if you can muck around with it and fiddle and massage it into various shapes and sizes easily then it’s more likely to be left alone. Data that’s left to rot is like leaving gold to rust. If gold rusted.
In short data is valuable, but only if it’s used.
In my quest for tools I’ve tried a few and found none that I would actually pay for, except the one I’ve been using now for a couple of months without a problem. DBVisualiser Free edition, I’d pay for that. It’s lucky too because they make a paid version with a bunch of extra features.
I’m always on the lookout for better applications to improve my performance and more importantly my enjoyment at work. So far this has been the closest application I’ve found to make MySQL a joy to use on the Mac. The free version does 99% of what I want to do, the pro version just seems to add features to make life even easier.
I’d urge people working with a database on the Mac to give DBVisualiser a try.
In a previous job I dealt with the IT tasks related to a multi level marketing business. We stored everything in a database of course and due to the nature of multi level marketing most of the operations performed had to take into account the tree like structure of the people involved.
An example would be, given a party that was run there would be rewards based on future bookings made, how much the party sold and so on. The largest direct benefitor of these rewards was of course the person that ran the party. However this person had a manager, who in turn may have a manager who in turn may have a manager and so on up the tree. At each level the manager got a cut based on a number of factors such as how many people she was managing, what her position was an so on.
At the time the way I dealt with trees was via adjacency lists, mostly because that’s what was most logical to me and how it seemed everyone else did it. I thought I’d have a look around and see if anything had changed in the last couple of years and found this article on using nested sets to deal with hierarchical data.
It seems to me that this method trades insertion performance for selection performance which for most situations is fantastic! It seems to be exactly what I need given I’ll be performing far more selects than inserts and it also has given me another tool in my toolbox.
It’s long been understood that to keep someone in IT happy one of the most important things is change and new stuff. I think this constitutes new stuff for me.