Re: StringIndexer with high cardinality huge data

Thanks guys. @Filipp Zhinkin Yes, we might have couple of string columns which will have 15million+ unique values which need to be mapped to indices. @Nick Pentreath We are on 2.0.2 though I will check it out. Is it better from hashing collision perspective or can handle large volume of data as

Re: StringIndexer with high cardinality huge data

Also check out FeatureHasher in Spark 2.3.0 which is designed to handle this use case in a more natural way than HashingTF (and handles multiple columns at once). On Tue, 10 Apr 2018 at 16:00, Filipp Zhinkin wrote: > Hi Shahab, > > do you actually need to have a few

Re: StringIndexer with high cardinality huge data

Hi Shahab, do you actually need to have a few columns with such a huge amount of categories whose value depends on original value's frequency? If no, then you may use value's hash code as a category or combine all columns into a single vector using HashingTF. Regards, Filipp. On Tue, Apr 10,

StringIndexer with high cardinality huge data

Is the StringIndexer keeps all the mapped label to indices in the memory of the driver machine? It seems to be unless I am missing something. What if our data that needs to be