@@ -118,7 +118,7 @@ The format of the log entries should be self-explanatory, but here are more deta
-**Task 6 (4pt)**: On the logsRDD, for two given times, use a 'cogroup' to create the following RDD: the key of the RDD will be a host, and the value will be a 2-tuple, where the first element is a list of all URLs fetched from that host before the first time, and the second element is the list of all URLs fetched from that host after the second time. Use filter to first create two RDDs from the input logsRDD.
-**Task 7 (8pt)**: [Bigrams](http://en.wikipedia.org/wiki/Bigram) are sequences of two consecutive words. For example, the previous sentence contains the following bigrams: "Bigrams are", "are simply", "simply sequences", "sequences of", etc. Your task is to write a bigram counting application for counting the bigrams in the `motivation`s of the Nobel Prizes (i.e., the reason they were given the Nobel Prize). The return value should be a PairRDD where the key is a bigram, and the value is its count, i.e., in how many different `motivations` did it appear. Don't assume 'motivation' is always present.
-**Task 7 (8pt)**: Your task is to write a name counting application for counting the first names in the motivations of the Nobel Prizes for each category. The return value should be a PairRDD where the key is a string, of which the format is "[Category]:[Firstname]" (i.e., "chemistry:Michael"), and the value is its count, i.e., in how many times did that combination appear.
-**Task 8 (8pt)**: [Maximal Matching] `task8` should implement one iteration of a greedy algorithm for finding a maximal matching in a bipartite graph.
A *matching* in a graph is a subset of the edges such that no two edges share a vertex (i.e., every vertex is part of at most 1 edge in the matching). A *maximal* matching
