A tanfolyamról
With tasks that require rapid processing speeds and huge amounts of data, developers turn to Elasticsearch, the open-source, readily scalable, enterprise-grade search engine which is gaining acceptance as a reliable search engine application. Elasticsearch helps you manage clusters, ensure automatic node recovery, and provide full security to your networks.
We bring you a comprehensive course on Elasticsearch that will help you grasp all the fundamentals of this search engine. Learn from expert trainers about text analysis, mappings, queries and filters, document modeling, data analytics, and much more. Our workshop focuses on practical understanding and uses a hands-on approach to give you a thorough working knowledge of Elasticsearch concepts. You will learn of its applications in real-time indexing and full-text search.
Who Should Attend the Course
- Big Data Professionals
- Aspiring Big Data Professionals
- Database Administrators
- Aspiring Database Administrators
What You Will Learn
-
Why Elasticsearch
Explore topics like Topology and Clusters, CRUD, Bulk Operations, Character Filters, and Analyzers -
Mappings
Learn about CRUD and its relationship to documents/indices, Data Types, and Dynamic Field Mappings -
Queries and Filters
Explore topics like Distributed Search Fundamentals, Query DSL Deep Dive, Query Advice and its best practices -
Suggestions
Learn about Terms, Phrases, Completion, and Context Suggesters; also cover the fundamentals of Aggregations -
Document Modeling
Explore Nested Objects and Documents and learn about the impact of document structure on search -
Advice and Best Practices
Explore Relevancy and Scoring, Boost and Function Lab, Percolator and Notifications, and case studies
During this 24-hour course, a variety of topics will be covered with the aim of educating you on the open-source, enterprise-grade search engine that is Elasticsearch and the best practices of working on it. The following are the practical skills you’ll gain on course completion:
- Leveraging Elasticsearch to analyze, visualize and search data
- Implementing best practices for querying on Elasticsearch
- Understanding the use of the full text search, indexes, and mapping features of Elasticsearch
- Installing and deploying Elasticsearch
We provide the course in English
Tematika
Curriculum
Module 1 - Why Elasticsearch
- Topology and Clusters
- CRUD
- Index, Update, Re-index, and Delete documents
- Bulk Operations
- Lab
- Module: Text Analysis
- Analyzers - Tokenizers and Filters
- Character Filters
- Testing Analyzers
- Built-In Analyzers
- Synonym Handling
- Lab
Module 2 - Mappings
- CRUD and relationship to documents/indices
- Data Types
- Dynamic Field Mappings
- Index Templates
- Lab
Module 3 - Queries and Filters
- Distributed Search Fundamentals
- Query DSL Deep Dive
- Query Advice and Best Practices
- Lab
Module 4 - Suggestions
- Terms, Phrase, Completion, and Context Suggesters
- Best Practices
- Lab
- Module: Aggregations
- Fundamentals
- Deep dive of each aggregation
- Lab
Module 5 - Document Modeling
- Nested Objects and Documents
- Impact of document structure on search
Module 6 - Advice and Best Practices
- Relevancy and Scoring
- Fundamentals
- Boost and Function Lab
- Percolator and Notifications
- Client Libraries and Testing
- Case Studies
Kinek ajánljuk
Előfeltételek
Prerequisites
Participants need to have a basic understanding of:
- Linux/Unix System Concepts
- Command Line Interface (CLI)
- Text Editors
- RDBMS Concepts