Learning ElasticSearch 5.0
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Learning ElasticSearch 5.0

Store, search, and analyze your data with ease using ElasticSearch 5.0
3.9 (111 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
576 students enrolled
Created by Packt Publishing
Last updated 3/2017
Current price: $10 Original price: $125 Discount: 92% off
5 hours left at this price!
30-Day Money-Back Guarantee
  • 3 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Understand why you should implement Elastic Search in your next project & beyond
  • Add and remove indices & documents
  • Add data in JSON format & interact via RESTful API using http GET & DELETE calls.
  • Use filters, ranges and matching, along with other advanced features, is covered.
  • Learn about Kibana and Logstash to serve as an excellent starting point for building the Elastic search Stack.
  • How to perform an full analysis, with ElasticSearch, Logstahs and Kibana on Apache web logs
  • Run some more advanced DSL search queries.
  • Learn the differences between Solr from Elastic Search.
View Curriculum
  • No previous knowledge of ElasticSearch 5.0 is required.

This course is a step-by-step guide to using Elasticsearch in combination with the rest of the ELK stack (now called Elastic Stack) to ship, parse, store, and analyze logs.

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 5.0. We’ll go through each of the fundamental concepts of ElasticSearch such as queries, indices, and aggregation.

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. Finally, we’ll take a walk through getting ElasticSearch up and running on the popular logstash Apache web log analysis.

Aside from learning how to add more power to your searches with 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. Finally, we’ll build, test and run our first Logstash pipeline to analyze Apache web logs. This step combines all the understanding of ElasticSearch, Logstash, Kibana and the lightweight data shipper FileBeat that we acquired from previous sections.

By the end of this course, you will have a firm understanding of all the fundamentals of ElasticSearch 5.0, along with knowledge of practical real world usage.

About The Author

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 data to innovate and deliver intuitive customer facing solutions, largely to non-technical professionals. Ethan has over 10 combined years of experience in cloud based technologies such as Amazon webservices and OpenStack, as well as the data centric technologies of Hadoop, Mahout, Spark and ElasticSearch. He began using ElasticSearch in 2011 and has since delivered solutions based on the Elastic Stack to a broad range of clientele. Ethan has also consulted worldwide, speaks fluent Mandarin Chinese and is insanely curious about human cognition, as related to cognitive dissonance.

Who is the target audience?
  • If you're a developer who wants to analyze and manipulate data, then this is the course for you.
Compare to Other Elasticsearch Courses
Curriculum For This Course
35 Lectures
Getting Started with ElasticSearch
6 Lectures 26:45

To get a feel for the course we do an end-to-end overview of what will be covered.

Preview 03:08

Gaining a holistic view of a new technology is the first necessary step to learning how it works. ElasticSearch is introduced with accompanying use cases.

What Is ElasticSearch?

Setting up a new technology is often a challenging affair. By walking through the simple process of installing ElasticSearch, developers can quickly move along the learning process.

Installing ElasticSearch

Before diving into any new technology, it is all too important to understand what the subject technology was designed for and the best use cases. Peering into the objectives of ElasticSearch solves this.

Goal of ElasticSearch

Version 5.0 of ElasticSearch has some key changes. Highlighting these changes help developers to get a better understanding of what's new.

What's New in Version 5.0?

As is the case with any new technology, developers seek compelling use cases for implementing ElasticSearch. ElasticSearch answers the call by being a fairly straight forward, developer friendly analytics engine.

Why Use ElasticSearch?
Dichotomy of ElasticSearch
4 Lectures 20:12

The indices are easily the cornerstone of ElasticSearch. As such, understanding indices and how they work is key.

Preview 02:31

Documents hold data in ElasticSearch. Understanding the workings of documents put one on the path to better understanding ElasticSearch.

Documents in ElasticSearch

The concept of a cluster can be broad and sometimes confusing. Understanding an ElasticSearch cluster is an important step in the learning process.

What Is a Cluster?

Distributed technology is extremely challenging to understand. Understanding how to set shards and replicas in ElasticSearch is therefore a necessary first step.

Setting Shards and Replicas
Get Going with Documents and Indices
3 Lectures 22:26

Index and Mapping set the stage for data search and analysis. Knowledge of how each work is important for effective ElasticSearch usage.

Preview 08:09

Document addition and deletion in ElasticSearch controls the flow of data. The ability to add and delete documents in ElasticSearch is necessary.

Adding and Deleting Documents

Since adding documents is among the most commonly performed tasks in ElasticSearch, there needs to be a way to add multiple documents simultaneously. The bulk API solves this problem.

Using Bulk API
Querying with RESTful API
3 Lectures 16:34

Interfacing with technology from external systems can be challenging and often requires a high degree of expertise. The REST API in ElasticSearch solves this problem.

Preview 03:21

Using REST API requires knowledge of how to run desired queries. Hands-on experience makes this possible.

Using REST API to Search

One common point of confusion in REST technology is differentiating between PUT and POST. Gaining a clear understanding of PUT versus POST in updates is therefore key.

Using REST API to Update
Power Your Searches with DSL
7 Lectures 31:27

Accessing the power of ElasticSearch necessitates understanding of its query language, DSL. A breakdown of DSL and how it works is essential.

Preview 04:10

Moving beyond the basics in DSL can be challenging. Going beyond the basic to take a deeper look into DSL helps.

Understanding DSL

Understanding the type of queries required to gain optimal results is necessary in ElasticSearch. Knowledge of term queries and boosting helps to optimize query results.

Term Queries and Boosting

Sometimes you will want to search a range of values. Range queries are the solution to this challenge.

Range Query

At times you will need to know when a given field exists. This is when you should turn to exist queries. 

Exist Query

Generating analytics can be a challenging task. Built-in aggregation based analytics in ElasticSearch take the pain out of analytics.

Aggregation Based Analytics

The process of running aggregation based analytics in ElasticSearch can get confusing. Experience is the best teacher.

Aggregations: Implementation
What ElasticSearch is NOT
1 Lecture 08:39

Not understanding the intended use of a technology can lead to bad implementations or even worse. It is imperative to understand what ElasticSearch is NOT designed for.

Preview 08:39
Getting More with ElasticStack
5 Lectures 17:51

ElasticSearch alone doesn't provide security, cluster management, log analysis and so on. Thus, ElasticStack was created.

Preview 01:47

Data aggregation is the first of many steps in the analysis process. Kibana facilitates data visualization and acts as a cluster management interface.


Log analysis is an involved process that moves unstructured log data into the ElasticSearch cluster. Logstash was created for this very reason.


Prior to ElasticSearch 5.0, security, monitoring, alerting, reporting, graph and so on. were all separate components. Version 5.0 combined these to form X-Pack.


The complexity of moving data from external systems to ElasticSearch presents many challenges. Beats was created to simplify the process of moving data into ElasticSearch.

Apache Log Analysis
2 Lectures 15:05

Log analysis is a multi-step process that requires attention to detail. Clear understanding of the process is essential.

Preview 05:40

It's not enough to know the steps to the log analysis process. Practical experience is also necessary for true understanding.

Running Log Analysis
Advanced ElasticSearch Queries
3 Lectures 11:48

In the world of data management, sorting is an absolute must have feature. Learning to sort in ElasticSearch can greatly improve search results

Preview 04:33

The ability to query Geo data highly ranks in modern use cases. ElasticSearch simplifies the process of geo searching.

Geo Searching

User generated queries for text search can be filled with colloquialism, abbreviations etc. Synonyms in ElasticSearch aim to help minimize this challenge.

Getting into Synonyms
ElasticSearch versus Apache Solr
1 Lecture 04:45

ElasticSearch isn't the only high-octane text search engine in existence. Understanding a competing technology helps to identify where ElasticSearch stands.

Preview 04:45
About the Instructor
Packt Publishing
3.9 Average rating
8,229 Reviews
58,992 Students
687 Courses
Tech Knowledge in Motion

Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.

With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.