A common activity in data warehousing is needing to build a dimension table from a parent-chiad source table.
Here are some common git commands for a basic working session using git.
git remote -v
git remote rm origin git remote add origin git@gitlab:atindale/repos.git
git remote set-url origin http://gitlab/USERNAME/OTHERREPOSITORY.git
git config -l
git config --format=full
git tag -a v1.0 "First version of software" git push --follow-tags
git tag -d v1.0 git push --follow-tags
As reported recently, I have set up an internal gitlab server. The reason for this being github, though incredibly awesome, does not allow you to have private repositories unless you part with hard cash. Enter the also incredibly awesome gitlab.
Over the course of my learning I have ended up with a base configuration for serving Python web applications. This configuration utilised the nginx web server together with uwsgi as the Python > web gateway. As is the norm it is recommended to utilise virtualenv to isolate your software requirements. The full stack is:
The standard operating system I go to for web apps such as this is Ubuntu. The steps detailed below are all given for that operating system.
You’ve entered cloudland and built your shiny Amazon EC2 instance. But you want to keep your costs down so you want to make sure your machine is not burning cycles while you’re in dreamland… so what do you do? You write a script and schedule it to start and stop your instance in the morning and evening.
Here are some common SQL problems, all of which have related solutions: how do I find the most recent log entry for each program? How do I find the most popular item from each category? How do I find the top score for each player? In general, these types of “select the extreme from each group” queries can be solved with the same techniques. I’ll explain how to do that in this article, including the harder problem of selecting the top N entries, not just the top 1.
Business Intelligence is big business. It almost seems like every software company in existence has some sort of “BI” suite. Of course those companies are at different stages of maturity and understanding or focussing on a different segment of the market just as many customers have different wants and needs. Some suites are little more that the old line reporting tools we may be familiar with. On the other hand, some companies are forging ahead into cutting edge branches such as the statistical exploitation of data and into the mobile device area which has become so ubiquitous. All of this software choice does lead to confusion in the marketplace. I have often been party to vendor sales processes where I’ve not been convinced the vendor knows what they are selling! But, choice is never a bad thing, we can all look forward to much more innovation in this space.
I rebooted the ESXi host just now after updating to ESXi 4.0 Update 2 and an NFS datastore was marked as “inactive”.
Decided to change some of the NFS parameters as follows
NFS.HeartbeatFrequency = 12 NFS.HeartbeatMaxFailures = 10
The original values of these parameters was:
NFS.HeartbeatFrequency = 9 NFS.HeartbeatMaxFailures = 3
We’ll see how we go with this, I’ll update this post with any follow-up.