Machine Learning on Oracle Autonomous Data Warehouse

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Last week I wrote a blog post about how long it took to create machine learning models on Oracle Database Cloud service. There was some impressive results and some surprising results too.

I decided to try out the exact same tests, using the exact same data on the Oracle Autonomous Data Warehouse Cloud service (ADW).

When creating the ADW service I took the basic configuration and didn’t change anything. The inbuilt machine learning for the Autonomous service will magically workout my needs and make the necessary adjustments, Right? It can handle any data volume and any data processing requirements, Right?

Here are the results.

ml_adwc

* You will notice that there is no time given for creating a SVM model for the 10M record data set. After waiting for 4 hours I got bored and gave up waiting (I actually did this three time to make sure it wasn’t a once off)

[I also had a 50M record data set. I just didn’t waste time trying that.]

[Neural Networks algorithm hasn’t been ported onto ADW at this point in time]

If you look back at the results from using the DBaaS you will see it was significantly quicker than the ADW. (for some it would be quicker using Python on my laptop)

Before you believe the hype, go test it yourself and make sure it measures up.

I re-ran my test cases over a number of days to see if the machine learning aspect of the Autonomous kicked in to learn from the processing and make any performance improvements. Sadly the results were basically the same or slightly slower. Disappointing.

When some tells you, you should be using this, ask them have they actually used and tested it themselves. And more importantly, don’t believe them. Go test it yourself.

 

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