Question about parallel data cleansing

user194372

Hello, everyone.

I need following information for my project.

(Data cleansing includes handling missing values, outliers, error correction, scaling, binning, necessary transformations etc

 which is done before the main analysis)

My question is

Does Rapidminer support parallel data cleansing?

Also I want to know which operators and which parameters support parallel cleansing.

Thank you and have a nice day

BalazsBaranyRM

Hi,

RapidMiner executes process steps (operators) one by one sequentially, as it by default assumes that they rely on the previous results. 

Some operators are internally parallelized if the algorithm is suitable for it. This is the case, for example, in Cross Validation or Random Forest. The preprocessing steps you described are usually not very suitable for parallelization.

So the answer to your question is: RapidMiner supports it but only a few operators are actually implemented in a parallel way.

If you have a lot of data and the different data cleansing steps don't rely on each other, you can use background execution in Studio or jobs on AI Hub to execute multiple processes at once.

Regards,

Balázs