Complete Guide to Elasticsearch
Complete Guide to Elasticsearch, available at $109.99, has an average rating of 4.61, with 136 lectures, 6 quizzes, based on 22737 reviews, and has 135843 subscribers.
You will learn about 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 This course is ideal for individuals who are Developers who want to learn Elasticsearch. The course is intended for developers and not system administrators. It is particularly useful for Developers who want to learn Elasticsearch. The course is intended for developers and not system administrators.
Enroll now: Complete Guide to Elasticsearch
Summary
Title: Complete Guide to Elasticsearch
Price: $109.99
Average Rating: 4.61
Number of Lectures: 136
Number of Quizzes: 6
Number of Published Lectures: 132
Number of Published Quizzes: 6
Number of Curriculum Items: 142
Number of Published Curriculum Objects: 138
Original Price: $109.99
Quality Status: approved
Status: Live
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
Who Should Attend
- Developers who want to learn Elasticsearch. The course is intended for developers and not system administrators.
Target Audiences
- Developers who want to learn Elasticsearch. The course is intended for developers and not system administrators.
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:
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Building a full text search engine (e.g. similar to Google Search)
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Data analytics for large amounts of data with aggregations
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Using Elasticsearch as a time series database (TSDB)
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… and much more!
Combined with other products in the Elastic Stack, such as Logstash or Kibana, you will unlock several other features, such as:
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Log management and log analysis
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Observability (including server/service monitoring and APM (Application Performance Monitoring))
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Data visualization and reporting
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Security analysis (SIEM)
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… 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.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction to the course
Lecture 2: Introduction to Elasticsearch
Lecture 3: Overview of the Elastic Stack
Lecture 4: Walkthrough of common architectures
Lecture 5: Guidelines for the course Q&A
Chapter 2: Getting Started
Lecture 1: Elasticsearch vs OpenSearch
Lecture 2: Overview of installation & hosting options
Lecture 3: Hosting OpenSearch on Bonsai
Lecture 4: Hosting Elasticsearch & Kibana on Elastic Cloud
Lecture 5: Setting up Elasticsearch & Kibana on macOS & Linux
Lecture 6: Setting up Elasticsearch & Kibana on Windows
Lecture 7: Understanding the basic architecture
Lecture 8: Inspecting the cluster
Lecture 9: Sending queries with cURL
Lecture 10: Sharding and scalability
Lecture 11: Understanding replication
Lecture 12: Adding more nodes to the cluster
Lecture 13: Overview of node roles
Lecture 14: Wrap up
Chapter 3: Managing Documents
Lecture 1: Creating & deleting indices
Lecture 2: Indexing documents
Lecture 3: Retrieving documents by ID
Lecture 4: Updating documents
Lecture 5: Scripted updates
Lecture 6: Upserts
Lecture 7: Replacing documents
Lecture 8: Deleting documents
Lecture 9: Understanding routing
Lecture 10: How Elasticsearch reads data
Lecture 11: How Elasticsearch writes data
Lecture 12: Understanding document versioning
Lecture 13: Optimistic concurrency control
Lecture 14: Update by query
Lecture 15: Delete by query
Lecture 16: Batch processing
Lecture 17: Importing data with cURL
Lecture 18: Wrap up
Chapter 4: Mapping & Analysis
Lecture 1: Introduction to this section
Lecture 2: Introduction to analysis
Lecture 3: Using the Analyze API
Lecture 4: Understanding inverted indices
Lecture 5: Introduction to mapping
Lecture 6: Overview of data types
Lecture 7: How the "keyword" data type works
Lecture 8: Understanding type coercion
Lecture 9: Understanding arrays
Lecture 10: Adding explicit mappings
Lecture 11: Retrieving mappings
Lecture 12: Using dot notation in field names
Lecture 13: Adding mappings to existing indices
Lecture 14: How dates work in Elasticsearch
Lecture 15: How missing fields are handled
Lecture 16: Overview of mapping parameters
Lecture 17: Updating existing mappings
Lecture 18: Reindexing documents with the Reindex API
Lecture 19: Defining field aliases
Lecture 20: Multi-field mappings
Lecture 21: Index templates
Lecture 22: Introduction to dynamic mapping
Lecture 23: Combining explicit and dynamic mapping
Lecture 24: Configuring dynamic mapping
Lecture 25: Dynamic templates
Lecture 26: Mapping recommendations
Lecture 27: Stemming & stop words
Lecture 28: Analyzers and search queries
Lecture 29: Built-in analyzers
Lecture 30: Creating custom analyzers
Lecture 31: Adding analyzers to existing indices
Lecture 32: Updating analyzers
Lecture 33: Wrap up
Chapter 5: Searching for Data
Lecture 1: Introduction to searching
Lecture 2: Introduction to term level queries
Lecture 3: Searching for terms
Lecture 4: Retrieving documents by IDs
Lecture 5: Range searches
Lecture 6: Prefixes, wildcards & regular expressions
Lecture 7: Querying by field existence
Lecture 8: Introduction to full text queries
Lecture 9: The match query
Lecture 10: Introduction to relevance scoring
Lecture 11: Searching multiple fields
Lecture 12: Phrase searches
Lecture 13: Leaf and compound queries
Lecture 14: Querying with boolean logic
Lecture 15: Query execution contexts
Lecture 16: Boosting query
Lecture 17: Disjunction max (dis_max)
Lecture 18: Querying nested objects
Lecture 19: Nested inner hits
Lecture 20: Nested fields limitations
Instructors
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Bo Andersen
Lead Developer
Rating Distribution
- 1 stars: 142 votes
- 2 stars: 282 votes
- 3 stars: 2018 votes
- 4 stars: 8117 votes
- 5 stars: 12176 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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