In this chapter, we will cover:
Graph and machine learning problems are hard to solve using the MapReduce framework. Most of these problems require iterative steps and/or knowledge of complex algorithms, which can be cumbersome to implement in MapReduce. Luckily, there are two frameworks available to help with graph and machine learning problems in the Hadoop environment. Apache Giraph is a graph-processing framework designed to run large-scale algorithms. Apache Mahout is a framework that provides implementations of distributed machine learning algorithms.
This chapter will introduce readers to these two frameworks, which are capable of leveraging the distributed power of MapReduce.