Hi, I have used the Spark Normalizer node and after that I was searching for the Denormalizer node but I couldn’t find it. Is it missing or is there another node that can perform this transformation via Spark?
Cause I supposed I could also use the Spark to Table node and then apply the Denormalizer node, but I want to know if there is a way to perform the denormalization also within spark.
Hi @gujodm
we currently do not have a Denormalizer node for Spark. And apart from doing it in a Spark Java Snippet node there is no option to do this right now within Spark. We can only denormalize in KNIME. I will open a feature request for a Spark Denormalizer node.
Thanks @mareike.hoeger,
I hope to see soon the spark denormalizer node…
meantime, can you show me a quick example for perform the denormalization within the Spark java snippet node?
Hi, I also need Spark denormalizer node, could you please let me know when it will be available or kindly share the java snippet code to do it??.
Thanks in advance!!
Eloy
Hey @eloyga, @gujodm,
sorry for the late reply. I do not know when we are able to provide a denormalizer node.
Regarding the snippet:
What we are doing during normalization is to calculate the scale and the translation and then calculate the normalization as scale * value + translation
So what you would have to do during denormalization is to calculate (normalizedValue -translation)/scale
You get the scale and translation from the PMML Model from the normalizer node.
You will find to LinearNorm value. The norm for 0.0 = translation and for 1.0 = scale + translation.
With those values you should be able to calculate the denormalization. I have created a very basic example workflow to give you an idea.