This chapter explains how to set up Hadoop to run on a cluster of machines. Running HDFS and MapReduce on a single machine is great for learning about these systems, but to do useful work they need to run on multiple nodes.
There are a few options when it comes to getting a Hadoop cluster, from building your own, to running on rented hardware or using an offering that provides Hadoop as a service in the cloud. This chapter and the next give you enough information to set up and operate your own cluster, but even if you are using a Hadoop service in which a lot of the routine maintenance is done for you, these chapters still offer valuable information about how Hadoop works from an operations point of view.
Hadoop is designed to run on commodity hardware. That means that you are not tied to expensive, proprietary offerings from a single vendor; rather, you can choose standardized, commonly available hardware from any of a large range of vendors to build your cluster.
“Commodity” does not mean “low-end.” Low-end machines often have cheap components, which have higher failure rates than more expensive (but still commodity-class) machines. When you are operating tens, hundreds, or thousands of machines, cheap components turn out to be a false economy, as the higher failure rate incurs a greater maintenance cost. On the other hand, large database-class machines are not recommended either, since they don’t score well on the price/performance ...