Expand/ improve big data class tutorials

[in progress]

Plan:
-start with a detailed explanation of the WordCount example (+clearly layout the different possible implementations)
-Math exercise. Explain the Pi estimation theorem. Provide a basic (no map reduce) java implementation of the problem. Ask for a Flink implementation
-Keep the Tf-Idf example
-Turn the Triangle enumeration algo. example into a graph exercise.
-(Potencially) Also try another algorithm (eg. Apriori or NaiveBayes) or some work with the meetup.com API.
Thanks I will fix it.

Von meinem iPhone gesendet

> Am Aug 12, 2014 um 2:12 PM schrieb Robert Metzger <notifications@github.com>:
> 
> In basics_WC.md:
> 
> > +  }
> > +}
> > +
> > +// [...]
> > +DataSet<WC> words = // [...]
> > +DataSet<WC> wordCounts = words
> > +                         // DataSet grouping with inline-defined KeySelector function
> > +                         .groupBy(
> > +                           new KeySelector<WC, String>() {
> > +                             public String getKey(WC wc) { return wc.word; }
> > +                           })
> > +                         // apply ReduceFunction on grouped DataSet
> > +                         .reduce(new WordCounter());
> > +```   
> > +
> > +For more details, please refer to the [Flink Java API guide](http://example.com/ "Flink Java API guide")
> The URL is wrong here.
> 
> —
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