Complete Guide to Elasticsearch

Learn Elasticsearch from scratch and begin learning the ELK stack (Elasticsearch, Logstash & Kibana) and Elastic Stack.

4.56 (21975 reviews)
Udemy
platform
English
language
Software Engineering
category
instructor
Complete Guide to Elasticsearch
129,772
students
12.5 hours
content
Apr 2024
last update
$109.99
regular price

What you will learn

How to build a powerful search engine with Elasticsearch

The theory of Elasticsearch and how it works under-the-hood

Write complex search queries

Be proficient with the concepts and terminology of Elasticsearch

Why take this course?

Do you want to learn Elasticsearch from the beginning and become a professional in no time? This course is an excellent way for you to quickly learn Elasticsearch and to put your knowledge to work in just a few hours! This online course is the most comprehensive Elasticsearch tutorial that you will find anywhere! It is a great starting point for anyone who wants to learn the Elastic Stack and ELK stack, as Elasticsearch is at the center of both stacks.

Elasticsearch is an extremely popular search engine and will be an excellent addition to your CV - even if you are already familiar with other search engines or frameworks such as Apache Lucene, Apache Solr, Algolia, etc.

This Elasticsearch course is a combination of theory and learning by doing. Before giving examples of how to perform certain queries, you will have been equipped with the necessary theory in advance. This ensures that you not only know how to write powerful Elasticsearch queries, but that you also understand the relevant theory. Throughout this tutorial, you will get a deep understanding of how Elasticsearch works under the hood.

The course starts from the absolute beginning, and no knowledge or prior experience with Elasticsearch is required. We will walk through all of the most important aspects of Elasticsearch. After completing this course, you will be able to utilize Elasticsearch for a number of use cases and purposes, such as:

  • Building a full text search engine (e.g. similar to Google Search)

  • Data analytics for large amounts of data with aggregations

  • Using Elasticsearch as a time series database (TSDB)

  • ... and much more!

Combined with other products in the Elastic Stack, such as Logstash or Kibana, you will unlock several other features, such as:

  • Log management and log analysis

  • Observability (including server/service monitoring and APM (Application Performance Monitoring))

  • Data visualization and reporting

  • Security analysis (SIEM)

  • ... and much more!

* These features are not specifically covered in this course. Some of them are covered in my Logstash and Kibana courses.

So, join me in this online course and learn how to build amazing things with Elasticsearch!



Please note that this course is intended for developers who want to interact with an Elasticsearch cluster in one way or another and not system administrators looking to maintain an Elasticsearch cluster in production. The course focuses on functionality relevant to utilize the capabilities of Elasticsearch as a developer. It also covers Elasticsearch in favor of OpenSearch, but most of the core features are identical or similar. So even if you wish to learn OpenSearch, this course should still be a good starting point.

Note that this course does not cover Logstash and Kibana. This is so that I can go into much greater detail with Elasticsearch and focus on that exclusively. This course is therefore dedicated to Elasticsearch. For courses on Logstash and Kibana, please see my other courses.

Content

Introduction

Introduction to the course
Introduction to Elasticsearch
Overview of the Elastic Stack
Understanding of the Elastic Stack
Walkthrough of common architectures
Guidelines for the course Q&A

Getting Started

Overview of installation options
Running Elasticsearch & Kibana in Elastic Cloud
Installing Elasticsearch on macOS and Linux
Installing Elasticsearch on Windows
Exploring the Elasticsearch directory
Installing Kibana on macOS and Linux
Installing Kibana on Windows
Understanding the basic architecture
Inspecting the cluster
Sending queries with cURL
Sharding and scalability
Sharding
Understanding replication
Replication
Adding more nodes to the cluster (for development)
Overview of node roles
Wrap up

Managing Documents

Creating & deleting indices
Indexing documents
Retrieving documents by ID
Updating documents
Scripted updates
Upserts
Replacing documents
Deleting documents
Understanding routing
How Elasticsearch reads data
How Elasticsearch writes data
Understanding document versioning
Optimistic concurrency control
Update by query
Delete by query
Batch processing
Importing data with cURL
Wrap up

Mapping

A word on document types
Introduction to mapping
Dynamic mapping
Meta fields
Field data types
Adding mappings to existing indices
Updated query
Changing existing mappings
Mapping parameters
Adding multi-fields mappings
Defining custom date formats
Picking up new fields without dynamic mapping
Wrap up

Analysis & Analyzers

Introduction to the analysis process
A closer look at analyzers
Using the Analyze API
Understanding the inverted index
Analyzers
Overview of character filters
Overview of tokenizers
Overview of token filters
Overview of built-in analyzers
Configuring built-in analyzers and token filters
Creating custom analyzers
Using analyzers in mappings
Adding analyzers to existing indices
A word on stop words
Wrap up

Introduction to Searching

Search methods
Searching with the request URI
Introducing the Query DSL
How searching works
Understanding query results
Understanding relevance scores
Debugging unexpected search results
Query contexts
Full text queries vs term level queries
Basics of searching

Term Level Queries

Introduction to term level queries
Searching for a term
Searching for multiple terms
Retrieving documents based on IDs
Matching documents with range values
Working with relative dates (date math)
Matching documents with non-null values
Matching based on prefixes
Searching with wildcards
Searching with regular expressions

Full Text Queries

Introduction to full text queries
Flexible matching with the match query
Matching phrases
Searching multiple fields

Adding Boolean Logic to Queries

Introduction to compound queries
Querying with boolean logic
Debugging bool queries with named queries
How the “match” query works

Joining Queries

Introduction to this section
Querying nested objects
Nested inner hits
Mapping document relationships
Adding documents
Querying by parent ID
Querying child documents by parent
Querying parent by child documents
Multi-level relations
Parent/child inner hits
Terms lookup mechanism
Join limitations
Join field performance considerations

Controlling Query Results

Specifying the result format
Source filtering
Specifying the result size
Specifying an offset
Pagination
Sorting results
Sorting by multi-value fields
Filters

Aggregations

Introduction to aggregations
Metric aggregations
Introduction to bucket aggregations
Document counts are approximate
Nested aggregations
Filtering out documents
Defining bucket rules with filters
Range aggregations
Histograms
Global aggregation
Missing field values
Aggregating nested objects

Improving Search Results

Introduction to this section
Proximity searches
Affecting relevance scoring with proximity
Fuzzy match query (handling typos)
Fuzzy query
Adding synonyms
Adding synonyms from file
Highlighting matches in fields
Stemming

Building a Web Application Search Engine

A quick note
Introducing Application & Client Libraries
Adding a simple query
Paginating search results
Adding fuzziness
Aggregations & Filters
Adding product details page

Conclusion

Bonus Lecture: Discounts to my other courses

Screenshots

Complete Guide to Elasticsearch - Screenshot_01Complete Guide to Elasticsearch - Screenshot_02Complete Guide to Elasticsearch - Screenshot_03Complete Guide to Elasticsearch - Screenshot_04

Our review

🏫 **Overview of the Course:** The Elasticsearch for Beginners course has garnered a global rating of 4.56, with all recent reviews reflecting a positive reception. The course is well-structured and covers comprehensive theoretical backgrounds, accompanied by practical examples. It is recommended for newcomers, individuals preparing for the Elastic Certified Engineer exam, and those looking to understand the ELK stack, particularly Elasticsearch. **Pros:** - 🚀 **Comprehensive Coverage:** The course effectively covers all the basics of Elasticsearch and provides a solid foundation for beginners. - 📚 **Theoretical Foundation:** It offers detailed explanations that are crucial for understanding how Elasticsearch works. - 🎓 **Well Organized:** The course is structured in a way that makes learning progressive and digestible. - 🌍 **Global Appeal:** Reviews from diverse learners indicate the course's universal appeal and effectiveness across different contexts. - 🛠️ **Real-world Applications:** Learners appreciate the practical examples that demonstrate how to apply concepts in real-life scenarios. - ✅ **Actionable Insights:** The course provides clear guidance and step-by-step instructions, which is particularly useful for those new to Elasticsearch. - 📚 **Additional Resources:** Some learners found the supplementary reading materials helpful for further exploration of topics covered in the course. - 💎 **Clear Language:** For non-native English speakers, the clear pronunciation and subtitles made understanding easier. - 🚀 **Engaging Content:** A few learners highlighted that the content was engaging and built upon previous knowledge to enhance understanding. - 🛠️ **Practical Application in Work:** Some users found the course invaluable for applying theoretical concepts to their frequent use of Elasticsearch at work. **Cons:** - 🤖 **Robot-like Voice:** A few reviews mentioned that the instructor's voice seemed robotic and unnatural, making it harder to grasp the material. - ⏱️ **Pacing Concerns:** Some learners felt that the course started off slow and suggested a more dynamic pacing. - 🖥️ **Technical Issues:** A couple of reviews indicated that some techniques demonstrated in the course may not align with newer versions of Elasticsearch (e.g., version 8.10). - 🚫 **Confusing Transitions and Visual Effects:** Some distractions were reported due to unnecessary visual effects and zooming on screen parts, which required learners to frequently rewind to catch up. **Learner Suggestions:** - 📝 **Roadmap for Beginners:** A learner suggested that the instructor could update a roadmap within the course to guide new beginners more effectively. - 🛠️ **Technical Updates:** It was recommended that the course content be updated to reflect the latest versions of Elasticsearch to avoid confusion and ensure relevance. - ✍️ **Clear Documentation:** Some learners proposed including direct links to the exact needed documents per lecture, enhancing the practical applicability of the course. **Conclusion:** The Elasticsearch for Beginners course is a valuable resource for those seeking to understand the intricacies of Elasticsearch and its role within the ELK stack. While there are some areas that could be improved for clarity and relevance, the overall sentiment from learners is highly positive. With a well-rounded curriculum, real-world examples, and a strong focus on foundational knowledge, this course stands out as a beneficial tool for anyone looking to explore or expand their expertise in Elasticsearch.

Coupons

DateDiscountStatus
12/7/202183% OFF
expired
1/8/202384% OFF
expired

Charts

Price

Complete Guide to Elasticsearch - Price chart

Rating

Complete Guide to Elasticsearch - Ratings chart

Enrollment distribution

Complete Guide to Elasticsearch - Distribution chart

Related Topics

693188
udemy ID
12/9/2015
course created date
7/23/2019
course indexed date
root
course submited by