HI -
Any advice on doing this for a very large dataset? i.e. I'd like to get the cosine similarity for all pairs of cases (as you'd do w. proc distance) but for a dataset with ~280K observations. As this will be ~280K^2 observations, that's slow and big (about 78B obs). So what I'd want to do is only write out the cases above a certain cosine sim value in sparse matrix format (rowID, colID, value) and only the lower triangle (Since its symmetric). Could probably write as an SQL merge...but seems DISTANCE should be faster?

Thank you!