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dimroc / repository
Count the number of times certain words were said in a particular neighborhood. Performed as a basic MapReduce job against 25M tweets. Implemented with different programming languages as a educational exercise.
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Analyses and discussions done here have led to the following language pull requests:
This repo implements the same map reduce ETL (Extract-Transform-Load) task in multiple languages in an effort to compare language productivity, terseness and readability. The performance comparisons should not be taken seriously. If anything, it is a bigger indication of my skillset in that language rather than their performance capabilities.
Count the number of tweets that mention 'knicks' in their message and bucket based on the neighborhood of origin. The ~1GB dataset for this task, sampled below, contains a tweet's message and its NYC neighborhood.
Simply run fetch_tweets in the repo directory or downloaded here.
91 west-brighton Brooklyn Uhhh
121 turtle-bay-east-midtown Manhattan Say anything
175 morningside-heights Manhattan It feels half-cheating half-fulfilling to cite myself.
Below you will find the languages run. Note that frameworks also play a big role, for example the Scala implementation compares the parallel collection to futures and the Akka framework. Click through on each language to read more.
Selected from shared topics, language and repository description—not editorial ratings.
shjassal /
A function that counts the total number of uppercase vowels in a given string, and another that counts the number of occurrences of each uppercase vowel in a string.
27/100 health