Summary

We covered a lot of ground in this chapter, in regards to getting a Hadoop cluster up and running and executing MapReduce programs on it.

Specifically, we covered the prerequisites for running Hadoop on local Ubuntu hosts. We also saw how to install and configure a local Hadoop cluster in either standalone or pseudo-distributed modes. Then, we looked at how to access the HDFS filesystem and submit MapReduce jobs. We then moved on and learned what accounts are needed to access Elastic MapReduce and other AWS services.

We saw how to browse and create S3 buckets and objects using the AWS management console, and also how to create a job flow and use it to execute a MapReduce job on an EMR-hosted Hadoop cluster. We also discussed other ways of accessing AWS services and studied the differences between local and EMR-hosted Hadoop.

Now that we have learned about running Hadoop locally or on EMR, we are ready to start writing our own MapReduce programs, which is the topic of the next chapter...