Course Outline
1. Introduction to Elasticsearch
- Overview of Elasticsearch
- Application scenarios for Elasticsearch
- Elasticsearch architectural framework
- Core components of the Elastic Stack (Elasticsearch, Logstash, Kibana, Beats)
- Deployment and execution of Elasticsearch using containerized environments
- Exploration of the RESTful API interface
2. Understanding Indices and Documents
- Document structure and JSON formatting
- Indices and data organization principles
- Shards and replication mechanisms
- Concepts of index lifecycle management
- Procedures for creating, updating, and deleting indices
- Create, Read, Update, and Delete (CRUD) operations for documents
3. Writing Search Queries
- Overview of the Query DSL (Domain Specific Language)
- Match queries
- Term queries
- Boolean queries
- Range queries
- Prefix, wildcard, and fuzzy search implementations
- Pagination and sorting mechanisms
- Distinguishing between filtering and querying
4. Performing Text Analysis
- Fundamentals of full-text search
- Analyzers
- Tokenizers
- Character filters
- Token filters
- Language-specific analyzers
- Custom analyzer development
- Enhancing search relevance
5. Defining Mappings
- Dynamic mapping processes
- Explicit mapping configurations
- Field data types
- Nested and object field structures
- Date and numeric field definitions
- Mapping best practices for government
- Safe procedures for updating mappings
6. Expanding Your Searches
- Multi-field search techniques
- Multi-match queries
- Phrase-based searches
- Highlighting search results
- Search boosting mechanisms
- Function score queries
- Use of search templates
7. Understanding the Distributed Model
- Cluster architecture overview
- Nodes and designated roles
- Primary and replica shards
- Cluster health monitoring
- Data distribution strategies
- Fault tolerance mechanisms
- High availability principles
8. Manipulating Search Results
- Pagination strategies
- Source filtering techniques
- Field collapsing methods
- Scripted fields
- Sorting methodologies
- Search result highlighting
- Optimizing search response structures
9. Aggregations and Analytics
- Metric aggregations
- Bucket aggregations
- Pipeline aggregations
- Statistical calculations
- Histogram functions
- Date-based aggregations
- Constructing analytical queries for government operations
- Aggregation performance optimization
10. Handling Data Relationships
- Object field structures
- Nested documents
- Parent-child relationship modeling
- Denormalization strategies
- Selecting appropriate data models
- Querying related data sets
11. Integrating Elasticsearch with Applications
- REST API integration methods
- Elasticsearch client libraries
- Indexing application-generated data
- Bulk API utilization
- Search API implementations
- Error handling protocols
- Integration best practices for government systems
12. Performance Optimization
- Efficient indexing strategies
- Query optimization techniques
- Bulk indexing procedures
- Refresh interval configurations
- Caching mechanisms
- Memory management
- Performance monitoring protocols
13. Monitoring and Troubleshooting
- Monitoring cluster health status
- Analyzing index statistics
- Diagnosing slow query performance
- Addressing common indexing issues
- Resolving cluster operational problems
- Backup and snapshot management concepts
- Logging and diagnostic procedures
14. Hands-on Workshop and Summary
- Developing a searchable application infrastructure
- Designing indices and defining mappings
- Implementing full-text search capabilities
- Creating aggregations and analytical reports
- Optimizing search performance for government efficiency
- Review of key technical concepts
- Questions and answers session
- Best practices and future development steps
Requirements
- Demonstrated proficiency in software engineering practices.
- Working knowledge of command-line interface operations.
- Previous exposure to Elasticsearch is not a prerequisite.
Intended Audience
- Software engineers and developers responsible for government applications
Testimonials (7)
Plenty of knowledge.
Ireneusz - Inter Cars S.A.
Course - Elasticsearch for Developers
Trainer big knowledge and excersises part
Kamil Romankiewicz - Inter Cars S.A.
Course - Elasticsearch for Developers
- performance of prepared training environment - adequate examples and topics in accordance with needs
Blazej - Kyndryl Wroclaw
Course - Elasticsearch for Developers
I liked that we got a general overview of elastic and learned tons of things that could be applied in current project the first day. I also liked that we went through current project code with a code review and mention improvements or/and stuff to think about or take up for discussion in the project on the second day. I like that the training gave me a good base to continue delve into elastic search.
Mattias Hansson - Chalmers Tekniska Hogskola AB
Course - Elasticsearch for Developers
The content relevnt and to the point
Qiniso Mdletshe - Quidco
Course - Elasticsearch for Developers
Doing the exercises. I really enjoyed the practicals.
Warren Stephen - Quidco
Course - Elasticsearch for Developers
Marcin knew exactly what he talking about and had proper hands on in-depth experience with the tools. He had answers to all our questions and made some really strong recommendations that we could start working towards with future projects and uses.
