In this chapter, we started by understanding how Elasticsearch works in the distributed environment. We understood how Elasticsearch ensures failover and parallelism for near real-time query responses. You learned how ES-Hadoop leverages the topology of Hadoop and Elasticsearch deployments to gain maximum performance and provide failover.

Further, you learned the essentials of production, including the hardware, the cluster topology, and the much recommended configurations for deploying any production cluster. We looked at the advanced configurations for some of the common deployment scenarios. We now have a checklist that can be very handy to take a quick look before any production deployment. Finally, we ended the chapter with a brief overview of how to administer the cluster.

In the next chapter, you will learn the various widely used Hadoop ecosystem technologies, such as Pig, Hive, Cascading, and Spark. We will see how to get the data to and from Elasticsearch with these technologies...