In SAS Viya, a data scientist wants to perform distributed text analytics on 2 million documents. Which architecture advantage does running PROC TEXTMINE in SAS Viya CAS provide over traditional SAS 9.4?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because the core architectural advantage of CAS for text mining is distributed in-memory processing — the term-document matrix (which can be enormous for millions of documents) and the SVD computation are parallelized across CAS worker nodes, overcoming single-machine memory and compute limitations of SAS 9.4 Workspace Server execution. A is wrong because CAS PROC TEXTMINE uses the same statistical text mining methods, not deep learning embeddings by default.
Full explanation below image
Full Explanation
B is correct because the core architectural advantage of CAS for text mining is distributed in-memory processing — the term-document matrix (which can be enormous for millions of documents) and the SVD computation are parallelized across CAS worker nodes, overcoming single-machine memory and compute limitations of SAS 9.4 Workspace Server execution. A is wrong because CAS PROC TEXTMINE uses the same statistical text mining methods, not deep learning embeddings by default. C is wrong because stop word lists are still applicable in CAS. D is wrong because the number of topics is a parameter, not a CAS vs. 9.4 distinction.