Chapter 1, Introduction to Elastic Stack, will give you a brief history and background on Elasticsearch. We will also get introduced to log analysis and will cover some of the core components of the Elastic Stack architecture.
Chapter 2, Installing Elasticsearch, will cover the installation process of Elasticsearch in different environments. We will also look into installation using the Debian and rpm packages, followed by installation on Windows using the MSI installer of Elasticsearch.
Chapter 3, Many as One – the Distributed Model, will cover how to interact with Elasticsearch using REST calls to call different operations. We will also look at how we can handle multiple indices, followed by looking at some of the common options for the API response. We will also learn how to create, delete, and retrieve indices.
Chapter 4, Prepping Your Data – Text Analysis and Mapping, will walk through the details of how full text is analyzed and indexed in Elasticsearch, followed by looking into some of the various analyzers and filters and how they can be configured. We will also learn how Elasticsearch mappings are used for defining documents and fields and storing and indexing them, including how to define multi-fields and custom analyzers.
Chapter 5, Let's Do a Search!, will go into further detail regarding data searches, where we will cover URI search and body search. We will also cover some query examples using term, from/size, sort, and source filtering. Following that, we will also cover highlighting, rescoring, search type, and named queries.
Chapter 6, Performance Tuning, will cover data sparsity and how to improve the performance of Elasticsearch. We will also cover how to adjust the search speed by means of allocating memory to the filesystem cache, faster hardware, document modeling, pre-index data, avoiding replicas, and so on.
Chapter 7, Aggregating Datasets, will cover how to aggregate datasets and will explain the different types of aggregations that Elasticsearch supports.
Chapter 8, Best Practices, will cover the best practices we can follow in order to manage an Elasticsearch cluster.
