Summary

In this chapter, we briefly looked at three core aspects of Elasticsearch.

First, we looked at the internals of an index in Elasticsearch. We explored how settings can be applied to indices and learned how to configure mappings for document fields. We also looked at a range of different data types that are supported and how they can be leveraged for various use cases.

We then looked at how nodes on Elasticsearch host indices and data. We understood the different roles a node plays as part of a cluster, as well as the concept of data tiers, to take advantage of different hardware profiles on nodes, depending on how the data is used.

Lastly, we ingested some sample data and learned how to ask questions about our data using the search API.

In the next chapter, we will dive a little bit deeper into how to derive statistical insights, use ingest pipelines to transform data, create entity-centric indices by pivoting on incoming data, manage time series sources using...