A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
Lecture Notes in Electrical Engineering
With the evolution of IT technologies, large-scale graph data have lately become a growing interest. As a result, there are a lot of research results in large-scale graph analysis on Hadoop. The graph analysis based on Hadoop provides parallel programming models with data partitioning and contains iterative phases of MapReduce jobs. Therefore, the effectiveness of data partitioning depends on how the data partitioning maintains data locality in each node of cluster. In this paper, we propose adoi:10.1007/978-3-642-40675-1_46 fatcat:it43m6erj5e2pmwbspoz34zqsy