Elasticsearch for Developers Training Course

1. Introduction to Elasticsearch

• Overview of Elasticsearch
• Practical use cases for Elasticsearch
• Architectural design of Elasticsearch
• Key components of the Elastic Stack (Elasticsearch, Logstash, Kibana, Beats)
• Deploying and running Elasticsearch using containers
• Interacting with the REST API

2. Understanding Indices and Documents

• Document structure and JSON
• Indices and data organization methods
• Concepts of shards and replicas
• Index lifecycle management
• Operations for creating, updating, and removing indices
• CRUD operations for managing documents

3. Writing Search Queries

• Introduction to Query DSL
• Implementing match queries
• Using term queries
• Constructing boolean queries
• Defining range queries
• Prefix, wildcard, and fuzzy search techniques
• Handling pagination and sorting
• Distinguishing between filtering and querying

4. Performing Text Analysis

• Basics of full-text search
• Understanding analyzers
• Role of tokenizers
• Applying character filters
• Using token filters
• Configuring language analyzers
• Creating custom analyzers
• Strategies for enhancing search relevance

5. Defining Mappings

• Dynamic mapping behaviors
• Setting explicit mappings
• Understanding field data types
• Handling nested and object fields
• Managing date and numeric fields
• Best practices for mapping definition
• Safely updating existing mappings

6. Expanding Your Searches

• Multi-field search capabilities
• Utilizing multi-match queries
• Executing phrase searches
• Highlighting relevant search results
• Applying search boosting
• Using function score queries
• Implementing search templates

7. Understanding the Distributed Model

• Cluster architecture overview
• Node types and roles
• Primary and replica shard mechanics
• Monitoring cluster health
• Data distribution strategies
• Fault tolerance mechanisms
• High availability principles

8. Manipulating Search Results

• Pagination strategies for results
• Source filtering techniques
• Implementing field collapsing
• Using script fields
• Advanced sorting methods
• Highlighting search result snippets
• Optimizing search response payloads

9. Aggregations and Analytics

• Metric aggregation types
• Bucket aggregation concepts
• Pipeline aggregations
• Performing statistical calculations
• Generating histograms
• Date-based aggregations
• Constructing complex analytical queries
• Optimizing aggregation performance

10. Handling Data Relationships

• Managing object fields
• Working with nested documents
• Parent-child document relationships
• Denormalization strategies
• Selecting the optimal data model
• Querying interconnected data

11. Integrating Elasticsearch with Applications

• REST API integration patterns
• Using Elasticsearch client libraries
• Indexing application data
• Leveraging the Bulk API
• Utilizing Search APIs
• Error handling mechanisms
• Integration best practices

12. Performance Optimization

• Efficient indexing strategies
• Query optimization techniques
• Bulk indexing workflows
• Managing refresh intervals
• Caching strategies
• Memory management practices
• Monitoring performance metrics

13. Monitoring and Troubleshooting

• Monitoring overall cluster health
• Analyzing index statistics
• Diagnosing slow queries
• Addressing common indexing issues
• Resolving cluster-level problems
• Backup and snapshot management
• Logging and diagnostic tools

14. Hands-on Workshop and Summary

• Developing a searchable application
• Designing indices and mappings
• Implementing full-text search features
• Creating aggregations and analytics
• Optimizing search performance
• Review of core concepts
• Q&A session
• Best practices and future recommendations