single source shortest path using spark

The purpose of this project is to develop a program to solve the single source shortest distance problem using Spark. solve the single source shortest distance problem using Spark: for each node in a directed graph, calculate the shortest distance from the node with id=0 to this node. The input directed graph is a dataset of edges, where an edge from the node i to the node j is represented in the input text file as: i,d,j where d is the distance from node i to node j. (Numbers i,j, and d are long integers.) Let distance[i] be the shortest distance from the node with id=0 to the node with id=i. The pseudo-code to calculate distance[i] is as follows: distance[0] = 0 for each node i <> 0: distance[i] = Long.MAX_VALUE repeat 4 times: for each edge (i,d,j): if distance[j] > distance[i]+d distance[j] = distance[i]+d Your code that calculates the new distances from the old must be repeated 4 times only. Hint: You may want to group edges by their destination as a triple (j,distance[j],{(i1,d1),(i2,d2),...}), which are derived from the edges (i1,d1,j),(i2,d2,j),... , where distance[j] is initially Long.MAX_VALUE.