This guide sets up a non-clustered Nutch crawler, which stores its data via HBase. We will not learn how to setup Hadoop et al., but just the bare minimum to crawl and index websites on a single machine.
| /*************************************************************************** | |
| * | |
| * This is a simple Monte Carlo simulation to see whether our sale | |
| * person should execute a strategy of 'many' big deals and 'few' small ones | |
| * or vis versa. | |
| * | |
| * Author: Ido Green | plus.google.com/+greenido | |
| * Date: 16 July 2013 | |
| * | |
| * *************************************************************************/ |
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| stratified = function(df, group, size) { | |
| # USE: * Specify your data frame and grouping variable (as column | |
| # number) as the first two arguments. | |
| # * Decide on your sample size. For a sample proportional to the | |
| # population, enter "size" as a decimal. For an equal number | |
| # of samples from each group, enter "size" as a whole number. | |
| # | |
| # Example 1: Sample 10% of each group from a data frame named "z", | |
| # where the grouping variable is the fourth variable, use: | |
| # |
