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Complete Guide to Elasticsearch by Bo Andersen

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Description

Complete Guide to Elasticsearch

Find the needle in the haystack.

This course is available today, but this page has yet to be updated!

This means that it’s your lucky day, as you can still make use of the below coupon code!

Enroll today to get a 75% early bird discount.

Use the following coupon code at checkout to claim your discount.

What’s it all about?

Below is some of what you will learn within the course.

Understand the architecture of Elasticsearch
Understand how Elasticsearch works under the hood
Different types of search queries (full text, compound, …)
How to work with mappings
Analyzers, tokenizers, stemming, etc.
Fuzzy searches, pagination, filters, etc.
Auto-completion using suggesters
Using aggregations

…and much more!

30 day money back guarantee

Don’t like the course? Get your money back, no questions asked.

Your instructor

I am a web developer from Denmark who has more than 10 years of experience with software development and web development. I am a full-stack developer, meaning that I work with backend as well as frontend development. I have worked for a number of successful companies in the past, including as a backend developer on one of Denmark’s most popular websites. Now I work as a freelance consultant and teacher, and love teaching people what I have learned over the years.

Bo Andersen

Course Curriculum

Getting Started

Preview

Introduction to this course (5:41)
Preview

Introduction to Elasticsearch (5:33)
Preview

Overview of the Elastic Stack (ELK+) (6:05)
Start

Quiz

Architecture of Elasticsearch

Start

Introduction to this section (1:12)
Start

Nodes & Clusters (5:14)
Start

Quiz
Start

Indices & Documents (1:40)
Start

A word on types (1:21)
Start

Sharding (4:52)
Start

Quiz
Start

Replication (3:33)
Start

Quiz
Start

Keeping replicas synchronized (3:14)
Start

Searching for data (3:42)
Start

Distributing documents across shards (4:03)
Start

Wrap up (1:16)

Installing Elasticsearch & Kibana

Start

Running Elasticsearch and Kibana with Docker (5:10)
Preview

Installing Elasticsearch on Mac/Linux (5:20)
Preview

Installing Elasticsearch on Windows (5:36)
Start

Configuring Elasticsearch (3:43)
Preview

Installing Kibana on Mac/Linux (2:52)
Preview

Installing Kibana on Windows (2:42)
Start

Configuring Kibana (2:04)
Preview

Introduction to Kibana and dev tools (6:36)
Start

Using the MSI installer on Windows

Managing Documents

Start

Creating an index (1:34)
Start

Adding documents (3:49)
Start

Retrieving documents by ID (1:16)
Start

Replacing documents (1:29)
Start

Updating documents (3:42)
Start

Scripted updates (3:08)
Start

Upserts (2:32)
Start

Deleting documents (3:30)
Start

Deleting indices (0:49)
Start

Batch processing (5:56)
Start

Importing test data with cURL (2:51)
Start

Exploring the cluster (6:53)

Mapping

Start

Introduction to mapping (1:23)
Start

Dynamic mapping (4:27)
Start

Meta fields (2:50)
Start

Field data types (13:48)
Start

Adding mappings to existing indices (1:57)
Start

Changing existing mappings (3:51)
Start

Mapping parameters (8:02)
Start

Adding multi-fields mappings (2:40)
Start

Defining custom date formats (5:46)
Start

Picking up new fields without dynamic mapping (7:33)
Start

Wrap up (0:37)

Analysis & Analyzers

Start

Introduction to the analysis process (1:53)
Start

A closer look at analyzers (5:21)
Start

Using the Analyze API (3:30)
Start

Understanding the inverted index (4:31)
Start

Quiz
Start

Overview of character filters (2:36)
Start

Overview of tokenizers (8:36)
Start

Overview of token filters (6:26)
Start

Overview of built-in analyzers (5:00)
Start

Configuring built-in analyzers and token filters (4:43)
Start

Creating custom analyzers (3:13)
Start

Using analyzers in mappings (3:20)
Start

Adding analyzers to existing indices (3:30)
Start

A word on stop words (1:01)
Start

Wrap up (1:01)

Introduction to Searching

Start

Search methods (2:17)
Start

Searching with the request URI (3:50)
Start

Introducing the Query DSL (2:50)
Start

Understanding query results (1:57)
Start

Understanding relevance scores (10:30)
Start

Debugging unexpected search results (1:43)
Start

Query contexts (2:40)
Start

Full text queries vs term level queries (5:57)
Start

Quiz

Term Level Queries

Start

Introduction to term level queries (1:10)
Start

Searching for a term (2:28)
Start

Searching for multiple terms (1:48)
Start

Retrieving documents based on IDs (1:07)
Start

Matching documents with range values (3:46)
Start

Working with relative dates (date math) (7:37)
Start

Matching documents with non-null values (2:00)
Start

Matching based on prefixes (1:19)
Start

Searching with wildcards (2:34)
Start

Searching with regular expressions (3:03)
Start

Exercises (1:07)
Start

Exercises: Solutions (6:16)

Full Text Queries

Start

Introduction to full text queries (2:23)
Start

Flexible matching with match query (4:45)
Start

Matching phrases (1:38)
Start

Searching multiple fields (2:38)
Start

Exercises (0:40)
Start

Exercises: Solutions (2:29)

Adding Boolean Logic to Queries

Start

Introduction to compound queries (1:09)
Start

Querying with boolean logic (10:37)
Start

Debugging bool queries with named queries (3:16)
Start

How the “match” query works (6:27)

Relationship Queries

Start

Introduction to this section
Start

Querying nested objects (5:21)

Controlling Query Results

Start

Specifying the result format (3:01)
Start

Source filtering (4:26)
Start

Specifying the result size (1:36)
Start

Specifying an offset (2:09)
Start

Pagination (5:04)
Start

Sorting results (5:16)
Start

Sorting by multi-value fields (2:27)
Start

Filters (3:52)

Aggregations

Start

Introduction to aggregations (2:43)
Start

Metric aggregations (9:40)
Start

Introduction to bucket aggregations (6:25)
Start

Document counts are approximate (6:22)
Start

Nested aggregations (5:58)
Start

Filtering out documents (2:31)
Start

Defining bucket rules with filters (3:16)
Start

Range aggregations (7:54)
Start

Histograms (8:01)
Start

Global aggregation (2:59)
Start

Missing field values (2:27)
Start

Aggregating nested objects (2:16)

Improving Search Results

Start

Introduction to this section (0:27)
Start

Proximity searches (7:17)
Start

Affecting relevance scoring with proximity (5:34)
Start

Fuzzy match query (handling typos) (9:06)
Start

Fuzzy query (2:33)
Start

Adding synonyms
Start

Adding synonyms from file (5:40)
Start

Highlighting matches in fields (6:05)
Start

Stemming (5:26)

Salepage : Complete Guide to Elasticsearch by Bo Andersen

About Author

Bo Andersen

My name is Bo Andersen and I am a software engineer from Denmark.

I currently work as the lead developer and partner at a startup company, apart from teaching here at Udemy. I have previously worked at a very successful company, operating one of the largest websites in Denmark, before deciding to teach software engineering. I have worked with programming for a decade and have a bachelor’s degree in computer science. I started out learning to code by building websites in PHP, but have since worked with many other technologies such as Elasticsearch, Logstash, Kibana, Beats, Java, Python, Docker, AWS, etc.

I have also been blogging about programming subjects for a number of years, so I encourage you to have a look at my website if you are curious.