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As @Nicholas said in a comment KX/KDB+ is popular in finance for this purpose. Direct message passing and local aggregation on the machine may be the best method in this case IMO.


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You may have a look at a list of clustering algos available in sklearn here, but I think all of them are of $O(n^2$) complexity. As well, have a look at the TSNE clustering algo, which is supposed to be $O(log(n)*n)$, but this may not be the fact depending on a particular implementation. A particular case in point is again Python sklearn implementation of ...



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