icloudber.blogg.se - Pentaho data integration variables

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So what’s going on here? Well we call the library, use the sample dataset and detect our anomalies. Res = AnomalyDetectionTs(raw_data, max_anoms=0.02, direction=’both’, plot=FALSE)

#Pentaho data integration variables how to

Then we just need to work out how to call that stuff from PDI. The command in that blog doesnt work either.

#Pentaho data integration variables install

Oh also see this page as to how to install from github. I followed that blog only to find devtools doesn’t install on ubuntu. Where is the line between simply a quiet day due to a national holiday and an intermittent problem causing your site to lose traffic? Very nice – I’ve done a lot of work in the past around automatic alerting and it’s very hard to get this kind of thing right. Later on this twitter blog appeared about a similar library – this time for anomaly detection. (As an aside it would be very interesting to understand more about how twitter are managing to scale R and use it with their vast quantities of data – Not something that R has traditionally been very good at) It is commonly used in trading, as typically when a share breaks out it goes up quite a lot) I admit it also piqued my interest that this was from Twitter! you can find the library on github it breaks out of previous normal boundaries. (A breakout is when something you are measuring over time reaches a new high, i.e. Last October I noticed the twitter engineering team had released a R module for breakout detection. So now what? Well now we can do something interesting.

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I think it would be good if they included a full working example in github alongside the plugin source code. I don’t know if this is an issue in the plugin, in my code, or even something different in PDI 5.3. For some reason R didn’t like the simple a+b calculation. Now I went down the enterprise route, but there is a community version of the R script executor available in the marketplace from these guys: However I was not able to get their example to work.

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Download the examples on the wiki page above and confirm they work.

Try an assortment of libswt/linux, libswt/linux/x86_64 and even.

Mess around with the libjri.so and keep trying various places to put it until PDI Finds it.

(This comes with the enterprise PDI by default.) The wiki page above refers to the R Executor step which is an enterprise only plugin. Don’t install the default r-base package, it’s ancient. So, here’s how I set everything up, note I’m on (K)Ubuntu 12, so some of the steps may not be necessary for everyone. R is extremely good at the number crunching or stats side. PDI is extremely good at the plumbing or data architecture side. Why would I want to do that? R can do everything PDI can do right? Err, yes and no. On the meetup side LondonR is extremely successful (not jealous, ahem.) and never fails to sell out. It’s an extremely hot sector at the moment. Well given any knowledge of R means you can classify yourself as a data scientist, that means you can really pick and choose any of many different jobs. There are commercial offerings too – I don’t pretend to know the market in depth, but one of the leads seems to be RevolutionRĪs usual I judge the success of the product by 2 things – Job opportunities and meetups. R is open source, and has a mighty impressive selection of libraries. SAS is a traditional old-school package of tools and is extremely expensive – Although it is generally accepted that if you can afford it, it is the best tool. These days everyone has heard of R (or RStats if you want something more google-able) and it is doing an amazing job of replacing SAS.