About the course
Quickly master big data with search and analytics from ElasticSearch
This course is a hands-on guide to using Elasticsearch used in conjunction with Elastic Stack, to ship, parse, store, and analyze data. You’ll start this course by getting an understanding of what Elasticsearch is, what it’s used for, and why it’s important. Then you’ll be introduced to the new features in Elasticsearch 6.
We’ll cover each of the fundamental components such as indices, documents, nodes and clusters, all which form the dichotomy of Elasticsearch. You’ll find out how to add more power to your searches using filters, ranges, and more. You’ll also see how Elasticsearch can be used with the other components of the Elastic Stack such as LogStash, Kibana, and Beats, to get data into an Elasticsearch cluster.
As well as learning how to add more power to your searches with filters, ranges, and more, you'll also see how to run advanced queries and aggregations on Elasticsearch 6. We’ll also implement Machine Learning in a step-by-step walk-through example of anomaly detection. We conclude by developing a quick working Elasticsearch application.
By the end of this course, you’ll have a firm understanding of all the fundamentals of Elasticsearch 6, along with sufficient knowledge to use it in the real world.
The code bundle for this course is available at: https://github.com/PacktPublishing/Learning-ElasticSearch-6
Style and Approach
This is a hands-on, example-based course designed to methodically walk you through the process of learning and understanding ElasticSearch.
What You Will Learn
- Get an introduction to Elasticsearch 6, what differentiates ver 6 from ver 5.5, setup/installation and understand the parts that make-up Elasticsearch that results in no single point of failure
- Find out about indices, documents, nodes, types, and clusters
- Dive deeper into Elasticsearch interactions with filers, ranges, matches along with aggregations
- Go into ElasticStack and use Kibana, logstash and filebeats, to develop a pipeline to get data from an external source into ElasticSearch
- Dispel myths about Elasticsearch and get use case examples
- Run more advanced DSL queries
- Find out about Machine Learning in Elasticsearch
- Build an Elasticsearch application
Ethan Anthony is a San Francisco based Data Scientist who specializes in distributed data-centric technologies. He is also the Founder of XResults, where the vision is to harness the power of big data to deliver intuitive customer-facing solutions, largely to non-technical professionals.
Ethan is Harvard-educated in the areas of data science and software engineering. He began using ElasticSearch in 2012 and has since delivered solutions based on the Elastic Stack to a broad range of clientele. Ethan has also consulted globally with firms in a cross-section of industry verticals, from the U.S. to the Far East.
All-in-One Introduction to Programming [Video]