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TweetSentimentParallelization

Multiple python multiprocessing library techniques were experimented with, including Multiprocesses and Multiprocessing pools and were paired with message passing strategies, such as using ZeroMQ PUSH/PULL protocol, in order to try and achieve the best speedup.

Environment used was DigitalOcean quad-core high-CPU VM.

Instruction

Tests can be run by running the run_tweets_test.sh bash script in /ParallelProcessing.

Results

Average Fetch Time of 500 Tweets:

Serial: 48.424s Parallel: 12.691s

Average Sentiment Analysis Time:

Serial:0.596s Parallel:0.183s

Total Program Time:

Serial: 49.959s Parallel: 14.414s

Speedup Achieved: 3.466

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