Chapter 7. Utilizing data structures and algorithms at scale

This chapter covers

  • Representing and using data structures such as graphs, HyperLogLog, and Bloom filters in MapReduce
  • Applying algorithms such as PageRank and semi-joins to large amounts of data
  • Learning how social network companies recommend making connections with people outside your network

In this chapter we’ll look at how you can implement algorithms in MapReduce to work with internet-scale data. We’ll focus on nontrivial data, which is commonly represented using graphs.

We’ll also look at how you can use graphs to model connections between entities, such as relationships in a social network. We’ll run through a number of useful algorithms that can be performed over graphs, ...

Get Hadoop in Practice, Second Edition now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.