Next, we wrote some JavaScript code to calculate PageRank on the graph stored in the database. The goal was to create a new collection `fpg_i` for every *i*th iteration of PageRank. Every iteration is a call on oneiteration() in [iteration.js](https://github.com/10gen-interns/big-data-exploration/blob/master/PageRank-Flights/src/iteration.js) co…

pagerank_calc.js

var map = function() {
    // For each node that is reachable from this node, give it the 
    // appropriate portion of my pagerank
    for (var toNode in this["value"]["prs"]) {
        emit(toNode, {totalNodes : 0.0
                  , pg : this["value"]["prs"][toNode] * this["value"]["pg"]
                  , prs : {}
                  , diff : 0.0
                  , prevpg : 0.0});
    }

    // Pass the previous pagerank and the probability matrix to myself
    emit(this["_id"], {totalNodes: this["value"]["totalNodes"]
                   , pg: 0.0
                   , prs: this["value"]["prs"]
                   , diff: 0.0
                   , prevpg: this["value"]["pg"]});

    // Reduce won't be called on a key unless there's more than one value for that key
    // So this is just an extra emit to make sure that reduce is called
    emit(this["_id"], {totalNodes: 0.0
                   , pg : 0.0
                   , prs : {} 
                   , diff : 0.0
                   , prevpg : 0.0});
};