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Complete Guide to Elasticsearch
Getting Started
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
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)
Overview of the Elastic Stack (ELK+)
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