What this book covers

Chapter 1, Introduction to Elasticsearch, guides you through how Apache Lucene works and will reintroduce you to the world of Elasticsearch, describing the basic concepts and showing you how Elasticsearch works internally.

Chapter 2, Power User Query DSL, describes how the Apache Lucene scoring works, why Elasticsearch rewrites queries, what query templates are, and how we can use them. In addition to that, it explains the usage of filters and which query should be used in a particular use case.

Chapter 3, Not Only Full Text Search, describes queries rescoring, multimatching control, and different types of aggregations that will help you with data analysis—significant terms aggregation and top terms aggregation that allow us to group documents with a certain criteria. In addition to that, it discusses relationship handling in Elasticsearch and extends your knowledge about scripting in Elasticsearch.

Chapter 4, Improving the User Search Experience, covers user search experience improvements. It introduces you to the world of Suggesters, which allows you to correct user query spelling mistakes and build efficient autocomplete mechanisms. In addition to that, you'll see how to improve query relevance by using different queries and the Elasticsearch functionality with a real-life example.

Chapter 5, The Index Distribution Architecture, covers techniques for choosing the right amount of shards and replicas, how routing works, how shard allocation works, and how to alter its behavior. In addition to that, we discuss what query execution preference is and how it allows us to choose where the queries are going to be executed.

Chapter 6, Low-level Index Control, describes how to alter the Apache Lucene scoring and how to choose an alternative scoring algorithm. It also covers NRT searching and indexing and transaction log usage, and allows you to understand segment merging and tune it for your use case. At the end of the chapter, you will also find information about Elasticsearch caching and request breakers aiming to prevent out-of-memory situations.

Chapter 7, Elasticsearch Administration, describes what the discovery, gateway, and recovery modules are, how to configure them, and why you should bother. We also describe what the Cat API is, how to back up and restore your data to different cloud services (such as Amazon AWS or Microsoft Azure), and how to use tribe nodes—Elasticsearch federated search.

Chapter 8, Improving Performance, covers Elasticsearch performance-related topics ranging from using doc values to help with field data cache memory usage through the JVM garbage collector work, and queries benchmarking to scaling Elasticsearch and preparing it for high indexing and querying scenarios.

Chapter 9, Developing Elasticsearch Plugins, covers Elasticsearch plugins' development by showing and describing in depth how to write your own REST action and language analysis plugin.