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Ramblings of a mad engineer. Taking MapReduce to Monte Carlo. May 5, 2010. Before theses key-value pairs are passed to the Reducers, they are sorted and the keys are aggregated. A reduce instance will get all of the values associated with a single key. It will then compute some new value from this, emitting an answer (also as a key-value pair). Def Mapper(line): for x in line.split : emit(x, 1). Def Reducer(key, values): count = 0 for v in values: count = v emit(key, count). For example, you can calculat...

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Ramblings of a mad engineer. Taking MapReduce to Monte Carlo. May 5, 2010. Before theses key-value pairs are passed to the Reducers, they are sorted and the keys are aggregated. A reduce instance will get all of the values associated with a single key. It will then compute some new value from this, emitting an answer (also as a key-value pair). Def Mapper(line): for x in line.split : emit(x, 1). Def Reducer(key, values): count = 0 for v in values: count = v emit(key, count). For example, you can calculat...
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2 mapreduce
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6 coroutines in c
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NathanWiegand.com | nathanwiegand.com Reviews

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Ramblings of a mad engineer. Taking MapReduce to Monte Carlo. May 5, 2010. Before theses key-value pairs are passed to the Reducers, they are sorted and the keys are aggregated. A reduce instance will get all of the values associated with a single key. It will then compute some new value from this, emitting an answer (also as a key-value pair). Def Mapper(line): for x in line.split : emit(x, 1). Def Reducer(key, values): count = 0 for v in values: count = v emit(key, count). For example, you can calculat...

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Taking MapReduce to Monte Carlo - NathanWiegand.com

http://www.nathanwiegand.com/taking_mapreduce_to_monte_carlo.html

Taking MapReduce to Monte Carlo. May 5, 2010. Before theses key-value pairs are passed to the Reducers, they are sorted and the keys are aggregated. A reduce instance will get all of the values associated with a single key. It will then compute some new value from this, emitting an answer (also as a key-value pair). One of the canonical examples of how this works is to calculate word-frequencies from some very large body of text. What follows is some Python-esque pseudo code for doing just this. For exam...

2

Coroutines in C - NathanWiegand.com

http://www.nathanwiegand.com/coroutines_in_c.html

April 21, 2010. A while ago, I read this article on coroutines in C. One of the main downfalls of this technique is that since it uses the static keyword, it makes it much harder to write recursive coroutines, and nigh-impossible to have multiple coroutines using the same function. Let’s first look at an example of how it can work. One way of efficiently computing Fibonacci numbers in a language like Haskell is to construct an infinite list of the Fibonacci values. Fibs a b = a : fibs b (a b). The yield ...

3

Hotswapping Binaries - NathanWiegand.com

http://www.nathanwiegand.com/hotswapping_binaries.html

February 22, 2010. About a year ago I was having a discussion with my friend Crutcher when he suggested that one could hot-swap versions of a running program. This post describes my implementation of just such a thing. Why would you hot-swap? Before we begin discussing how this should work, let’s look at some of the problems. Sure we get file descriptors, but what about all of our state? So, let’s look at the important bits of the hot-swap (reader and writer are the file descriptors for the pipe):. Now, ...

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Ramblings of a mad engineer. Taking MapReduce to Monte Carlo. May 5, 2010. Before theses key-value pairs are passed to the Reducers, they are sorted and the keys are aggregated. A reduce instance will get all of the values associated with a single key. It will then compute some new value from this, emitting an answer (also as a key-value pair). Def Mapper(line): for x in line.split : emit(x, 1). Def Reducer(key, values): count = 0 for v in values: count = v emit(key, count). For example, you can calculat...

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