Bo Andersen – Complete Guide to Elasticsearch

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Bo Andersen – Complete Guide to Elasticsearch

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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 ed

Introduction to this course (5:41)

Introduction to Elasticsearch (5:33)

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

Quiz

Architecture of Elasticsearch

Introduction to this section (1:12)

Nodes & Clusters (5:14)

Quiz

Indices & Documents (1:40)

A word on types (1:21)

Sharding (4:52)

Quiz

Replication (3:33)

Quiz

Keeping replicas synchronized (3:14)

Searching for data (3:42)

Distributing documents across shards (4:03)

Wrap up (1:16)

Installing Elasticsearch & Kibana

Running Elasticsearch and Kibana with Docker (5:10)

Installing Elasticsearch on Mac/Linux (5:20)

Installing Elasticsearch on Windows (5:36)

Configuring Elasticsearch (3:43)

Installing Kibana on Mac/Linux (2:52)

Installing Kibana on Windows (2:42)

Configuring Kibana (2:04)

Introduction to Kibana and dev tools (6:36)

Using the MSI installer on Windows

Managing Documents

Creating an index (1:34)

Adding documents (3:49)

Retrieving documents by ID (1:16)

Replacing documents (1:29)

Updating documents (3:42)

Scripted updates (3:08)

Upserts (2:32)

Deleting documents (3:30)

Deleting indices (0:49)

Batch processing (5:56)

Importing test data with cURL (2:51)

Exploring the cluster (6:53)

Mapping

Introduction to mapping (1:23)

Dynamic mapping (4:27)

Meta fields (2:50)

Field data types (13:48)

Adding mappings to existing indices (1:57)

Changing existing mappings (3:51)

Mapping parameters (8:02)

Adding multi-fields mappings (2:40)

Defining custom date formats (5:46)

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

Wrap up (0:37)

Analysis & Analyzers

Introduction to the analysis process (1:53)

A closer look at analyzers (5:21)

Using the Analyze API (3:30)

Understanding the inverted index (4:31)

Quiz

Overview of character filters (2:36)

Overview of tokenizers (8:36)

Overview of token filters (6:26)

Overview of built-in analyzers (5:00)

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

Creating custom analyzers (3:13)

Using analyzers in mappings (3:20)

Adding analyzers to existing indices (3:30)

A word on stop words (1:01)

Wrap up (1:01)

Introduction to Searching

Search methods (2:17)

Searching with the request URI (3:50)

Introducing the Query DSL (2:50)

Understanding query results (1:57)

Understanding relevance scores (10:30)

Debugging unexpected search results (1:43)

Query contexts (2:40)

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

Quiz

Term Level Queries

Introduction to term level queries (1:10)

Searching for a term (2:28)

Searching for multiple terms (1:48)

Retrieving documents based on IDs (1:07)

Matching documents with range values (3:46)

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

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

Matching based on prefixes (1:19)

Searching with wildcards (2:34)

Searching with regular expressions (3:03)

Exercises (1:07)

Exercises: Solutions (6:16)

Full Text Queries

Introduction to full text queries (2:23)

Flexible matching with match query (4:45)

Matching phrases (1:38)

Searching multiple fields (2:38)

Exercises (0:40)

Exercises: Solutions (2:29)

Adding Boolean Logic to Queries

Introduction to compound queries (1:09)

Querying with boolean logic (10:37)

Debugging bool queries with named queries (3:16)

How the “match” query works (6:27)

Relationship Queries

Get Bo Andersen – Complete Guide to Elasticsearch download

Introduction to this section

Querying nested objects (5:21)

Controlling Query Results

Specifying the result format (3:01)

Source filtering (4:26)

Specifying the result size (1:36)

Specifying an offset (2:09)

Pagination (5:04)

Sorting results (5:16)

Sorting by multi-value fields (2:27)

Filters (3:52)

Aggregations

Introduction to aggregations (2:43)

Metric aggregations (9:40)

Introduction to bucket aggregations (6:25)

Document counts are approximate (6:22)

Nested aggregations (5:58)

Filtering out documents (2:31)

Defining bucket rules with filters (3:16)

Range aggregations (7:54)

Histograms (8:01)

Global aggregation (2:59)

Missing field values (2:27)

Aggregating nested objects (2:16)

Improving Search Results

Introduction to this section (0:27)

Proximity searches (7:17)

Affecting relevance scoring with proximity (5:34)

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

Fuzzy query (2:33)

Adding synonyms

Adding synonyms from file (5:40)

Highlighting matches in fields (6:05)

Stemming (5:26)

Got any questions?

If you have any questions about this course, then you are more than welcome to ask. You can contact me by filling out the contact form or by using the chat at the bottom right of this page. I look forward to hearing from you!

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Bo Andersen|Bo Andersen – Complete Guide to Elasticsearch|Complete Guide to Elasticsearch

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