Mô tả

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.

Bạn sẽ học được gì

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

Yêu cầu

  • Knowledge of JSON
  • Basic terminal skills is a plus

Nội dung khoá học

10 sections

Introduction

6 lectures
Introduction to the course
06:27
Introduction to Elasticsearch
06:36
Overview of the Elastic Stack
17:46
Understanding of the Elastic Stack
4 questions
Walkthrough of common architectures
10:57
Guidelines for the course Q&A
01:49

Getting Started

14 lectures
Overview of installation options
02:35
Running Elasticsearch & Kibana in Elastic Cloud
05:35
Setting up Elasticsearch & Kibana on macOS & Linux
07:50
Setting up Elasticsearch & Kibana on Windows
06:58
Understanding the basic architecture
06:57
Inspecting the cluster
07:40
Sending queries with cURL
08:15
Sharding and scalability
09:27
Sharding
3 questions
Understanding replication
17:40
Replication
6 questions
Adding more nodes to the cluster
12:21
Overview of node roles
09:59
Wrap up
01:10

Managing Documents

18 lectures
Creating & deleting indices
03:08
Indexing documents
04:06
Retrieving documents by ID
01:20
Updating documents
03:59
Scripted updates
07:44
Upserts
02:30
Replacing documents
01:26
Deleting documents
01:01
Understanding routing
05:18
How Elasticsearch reads data
02:34
How Elasticsearch writes data
08:03
Understanding document versioning
03:22
Optimistic concurrency control
06:32
Update by query
08:52
Delete by query
01:52
Batch processing
13:53
Importing data with cURL
07:14
Wrap up
00:52

Mapping & Analysis

33 lectures
Introduction to this section
00:42
Introduction to analysis
05:30
Using the Analyze API
05:12
Understanding inverted indices
06:40
Introduction to mapping
02:08
Overview of data types
08:35
How the "keyword" data type works
04:08
Understanding type coercion
05:59
Understanding arrays
05:04
Adding explicit mappings
05:32
Retrieving mappings
01:35
Using dot notation in field names
01:49
Adding mappings to existing indices
01:52
How dates work in Elasticsearch
06:05
How missing fields are handled
01:44
Overview of mapping parameters
14:35
Updating existing mappings
04:21
Reindexing documents with the Reindex API
12:46
Defining field aliases
03:31
Multi-field mappings
06:34
Index templates
12:22
Introduction to dynamic mapping
09:02
Combining explicit and dynamic mapping
01:34
Configuring dynamic mapping
08:02
Dynamic templates
13:22
Mapping recommendations
05:15
Stemming & stop words
04:08
Analyzers and search queries
04:22
Built-in analyzers
07:38
Creating custom analyzers
10:00
Adding analyzers to existing indices
06:11
Updating analyzers
07:08
Wrap up
00:28

Searching for Data

23 lectures
Introduction to searching
08:02
Introduction to term level queries
06:44
Searching for terms
06:02
Retrieving documents by IDs
02:00
Range searches
04:39
Prefixes, wildcards & regular expressions
09:20
Querying by field existence
06:17
Term level queries
6 questions
Introduction to full text queries
05:39
The match query
05:03
Introduction to relevance scoring
03:21
Searching multiple fields
07:37
Phrase searches
09:13
Full text queries
3 questions
Leaf and compound queries
02:42
Querying with boolean logic
21:24
Query execution contexts
05:34
Boosting query
07:26
Disjunction max (dis_max)
05:37
Querying nested objects
12:14
Nested inner hits
05:53
Nested fields limitations
04:56
Compound & nested queries
4 questions

Joining Queries

12 lectures
Introduction to this section
02:43
Add departments test data
00:09
Mapping document relationships
02:35
Adding documents
06:35
Querying by parent ID
02:52
Querying child documents by parent
05:14
Querying parent by child documents
05:55
Multi-level relations
09:42
Parent/child inner hits
02:00
Terms lookup mechanism
06:11
Join limitations
01:42
Join field performance considerations
04:20

Controlling Query Results

8 lectures
A word on document types
01:04
Specifying the result format
03:01
Source filtering
04:25
Specifying the result size
01:36
Specifying an offset
02:09
Pagination
05:04
Sorting results
05:16
Sorting by multi-value fields
02:27

Aggregations

12 lectures
Introduction to aggregations
02:43
Metric aggregations
09:40
Introduction to bucket aggregations
06:25
Document counts are approximate
06:22
Nested aggregations
05:58
Filtering out documents
02:31
Defining bucket rules with filters
03:16
Range aggregations
07:54
Histograms
08:01
Global aggregation
02:59
Missing field values
02:27
Aggregating nested objects
02:16

Improving Search Results

9 lectures
Introduction to this section
00:27
Proximity searches
07:17
Affecting relevance scoring with proximity
05:34
Fuzzy match query (handling typos)
09:06
Fuzzy query
02:33
Adding synonyms
12:11
Adding synonyms from file
05:40
Highlighting matches in fields
06:05
Stemming
05:26

Conclusion

1 lectures
Bonus Lecture: Discounts to my other courses
00:19

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