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
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
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.