Know when to fold 'em: visualizing the streaming, concurrent reduce

Holy cow! Can you believe your luck? What better way to spend some portion of whatever day of the week it is than to think about parallelizing reduction algorithms?

Really? You can't think of one? In that case, I'll kick off our inevitable friendship by contributing a clojure implementation of a fancy algorithm that asynchronously reduces arbitrary input streams while preserving order. Then I'll scare you with glimpses of my obsessive quest to visualize what this algorithm is actually doing; if you hang around, I'll show you what I eventually cobbled together with clojurescript and reagent ...

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Varieties of laziness: clojure reducers, scala views and closure functors

This is very cool.

(Thanks to David Nolen, who pointed out errors in the original.)

I hadn't realized that the standard higher order sequence functions compose in a manner that requires quite a bit of run-time machinery. For example nested map calls will cause a separate lazy sequence to be instantiated at each level of nesting, with each level "pulling" results from the next innermost as needed. The function calls are thus temporally interleaved, but the functions are not actually composed. We can see this happening by adding some printlns to some unary functions and then running a ...

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