Wai-Tak Wong - Advanced Elasticsearch 7. 0 : a Practical Guide to Designing, Indexing, and Querying Advanced Distributed Search Engines.

, Overview of Elasticsearch 7 , takes beginners through some basic features in minutes. We just take a few steps to launch the new version of the Elasticsearch server. An architectural overview and a core concept introduction will make it easy to understand the workflow in Elasticsearch.

, Index APIs , discusses how to use index APIs to manage individual indices, index settings, aliases, and templates. It also involves monitoring statistics for operations that occur on an index. Index management operations including refreshing, flushing, and clearing the cache are also discussed.

, Document APIs , begins with the basic information about a document and its life cycle. Then we learn how to access it. After that, we look at accessing multiple documents with the bulk API. Finally, we discuss migrating indices from the old version to version 7.0.

, Mapping APIs , introduces the schema in Elasticsearch. The mapping rules for both dynamic mappings and explicit static mappings will be discussed. It also provides the idea and details of creating static mapping for an index. We also step into the details of the meta fields and field data types in index mapping.

, Anatomy of an Analyzer , drills down in to the anatomy of the analyzer and in-depth practice different analyzers. We will discuss different character filters, tokenizers, and token filters in order to understand the building blocks of the analyzer. We also practice how to create a custom analyzer and use it in the analyze API.

, Search APIs , covers different types of searches, from terms-based to full-text, from exact search to fuzzy search, from single-field search to multi-search, and then to compound search. Additional information about Query DSL and search-related APIs such as tuning, validating, and troubleshooting will be discussed.

, Modeling Your Data in the Real World , discusses data modeling with Elasticsearch. It focuses on some common issues users may encounter when working with different techniques. It helps you understand some of the conventions and contains insights from real-world examples involving denormalizing complex objects and using nested objects to handle relationships.

, Aggregation Framework , discusses data analytics using the aggregation framework. We learn how to perform aggregations with examples and delve into most of the types of aggregations. We also use IEX ETF historical data to plot a graph for different types of moving averages, including forecasted data supported by the model.

, Preprocessing Documents in Ingest Pipelines , discusses the preprocessing of a document through predefined pipeline processors before the actual indexing operation begins. We also learn about data accessing to documents through the pipeline processor. Finally, we cover exception handling when an error occurs during pipeline processing.