Searching and Analyzing Data with Elasticsearch: Getting Started

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.
Course info
Rating
(158)
Level
Intermediate
Updated
Jun 16, 2017
Duration
2h 46m
Table of contents
Description
Course info
Rating
(158)
Level
Intermediate
Updated
Jun 16, 2017
Duration
2h 46m
Description

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.

About the author
About the author

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.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi! My name is Janani Ravi, and welcome to this course on Searching and Analyzing Data Using Elasticsearch. I'll introduce myself. I have a Master's in electrical engineering from Stanford and have worked at companies such as Microsoft, Google, and Flipkart. At Google, I was one of the first engineers working on real-time collaborative editing in Google Docs, and I hold four patents for its underlying technologies. I currently work on my own startup, Loonycorn, a studio for high-quality video content. The search feature is a cool part of any product today. Elasticsearch is one of the most popular open source technologies which allows you to build and deploy efficient and robust search quickly. This course helps you understand the basic building blocks of search algorithms and focuses on the inverted index, the detail structure at the heart of every search engine. Learn Elasticsearch from first principles. Install and set up a single node search server. Index and update documents whose contents you want to search. Perform a variety of search queries on these documents. And, finally, run analysis to extract insights from your data. Implement all of these using queries specified in JSON notation on Elasticsearch's REST APIs. Understand the theory behind search, the TF/IDF algorithm for search ranking and relevance, and the important factors which determine how a document is called for every search term. Learn how Elasticsearch handles a variety of searches, such as full-text queries, term queries, compound queries, and filters. Finally, we'll run analytical queries on interesting data subsets specified by search terms. Experience the full power of Elasticsearch as a search and analytical engine.