google books word frequency script; first experiment with sentiment analysis script (NEEDS SERIOUS PERFORMANCE IMPROVEMENTS)
updated twitter_sentiment.pig
twitter sentiment script mostly done (refactored to use macros)
twitter word freqs relative to twitter corpus instead of english, common crawl script first draft
min word frequency for twitter associations
twitter sentiment script complete
got rid of common_crawl script since that will go into a new branch
first draft of common crawl trending topics script
filter out pages with no html (either error with crawl itself or with loader)
improved crawl script, bug fixes, algorithm tuning, optimization. it produces decent output now provided it has sufficient (500MB+) input
documentation
fixed type that broke python udf register statement
added recommended cluster size to docs
something is rotten in the state of the common crawl script (not tokenizing properly I think)
fixed tokenization bug
fixed performance issues by reimplementing in pure pig + 1 java udf
got rid of unneeded import
updated nasa_logs to use mortar-example-output-data instead of hawk-example-output-data
added warning about illustrate possibly failing due to too much data per record
fixed inconsistent output path in nasa_logs