Elasticsearch is a popular enterprise search engine, which allows you to build powerful search capability. This course focuses on understanding search components and algorithms from first principles, and applying these in practice using REST APIs.
Elasticsearch is one of the most popular open source technologies, which allows you to build and deploy efficient and robust search quickly. In this course, Searching and Analyzing Data with Elasticsearch: Getting Started, you'll be introduced to Elasticsearch by learning the basic building blocks of search algorithms, and how the basic data structure at the heart of every search engine works. First, you'll cover how to install and set up a single node server, index and update documents whose contents you want to search, perform a variety of search queries on these document contents, and run analysis to extract insights from your data. Next, you'll explore the TF/IDF algorithm for search ranking and relevance, and the important factors which determine how a document is scored for every search term. Finally, you'll learn how Elasticsearch handles a variety of searches, such as full-text queries, term queries, compound queries, and filters. You'll also run analytical queries on interesting data subsets specified by search terms. By the end of this course, you'll have the necessary knowledge to utilize Elasticsearch in practice.
A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.