Презентация «Introduction to ElasticSearch , показать реальные примеры из сайта ElasticSearch . Связь ElasticSearch и Kibana» — шаблон и оформление слайдов
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Содержание презентации
- Introduction to ElasticSearch & Kibana
- Introduction to ElasticSearch
- Nodes, Clusters, and Indices
- Setting Up ElasticSearch
- Indexing Data in ElasticSearch
- Searching in ElasticSearch
- Real-world Example from Elastic.co
- Advanced Features of ElasticSearch
- Introduction to Kibana
- ElasticSearch and Kibana Integration
- Benefits and Future of ElasticSearch
Introduction to ElasticSearch & Kibana
Слайд 1Explore the fundamentals of ElasticSearch, its real-world applications from the Elastic site, and the integration with Kibana for powerful data visualization.
Introduction to ElasticSearch
Слайд 2ElasticSearch is a powerful search engine known for its distributed nature and scalability.
It is widely used for data indexing and search capabilities across various applications.
Nodes, Clusters, and Indices
Слайд 3Clusters: Backbone of ElasticSearch
Clusters consist of multiple nodes working together to provide high availability and scalability.
Nodes: Individual Units
Nodes are individual servers that store data and participate in the cluster operations.
Indices: Data Organization
Indices are collections of documents, similar to tables in a database, used for storing data.
Setting Up ElasticSearch
Слайд 4Installation Process
ElasticSearch can be set up using various package managers or Docker.
Configuration Essentials
Configuration files are crucial for defining cluster settings and performance.
Initial Cluster Setup
Initial setup includes defining cluster name and node roles for efficiency.
Indexing Data in ElasticSearch
Слайд 5Document Storage
ElasticSearch stores data as JSON documents in indices for flexible schema.
Indexing Process
Indexing involves adding documents to indices, making them searchable.
Schema Flexibility
The schema-less nature of ElasticSearch allows dynamic data types.
Searching in ElasticSearch
Слайд 6Basic Queries
Includes match, term, and range queries for basic search operations.
Compound Queries
Combine multiple queries using bool, dis_max, and boosting queries.
Full-text Search
Full-text search capabilities allow for natural language processing.
Real-world Example from Elastic.co
Слайд 7E-commerce Search
ElasticSearch powers search functionality in e-commerce platforms.
Log Monitoring
Used for log analysis and monitoring in IT infrastructure setups.
Data Analytics
Facilitates real-time data analytics across various domains.
Advanced Features of ElasticSearch
Слайд 8Aggregations
Aggregations offer powerful data analysis capabilities for summarizing trends.
Custom Analyzers
Define custom analyzers for specific text processing needs.
Scalability
ElasticSearch scales horizontally, handling large volumes of data.
Introduction to Kibana
Слайд 9Data Visualization
Kibana provides interactive visualizations for ElasticSearch data.
Intuitive Dashboards
Create custom dashboards to monitor and analyze data trends.
Real-time Analysis
Offers real-time data exploration and analysis capabilities.
ElasticSearch and Kibana Integration
Слайд 10Seamless Integration
Kibana seamlessly integrates with ElasticSearch for real-time insights.
Data Exploration
Users can explore ElasticSearch data through Kibana's visual interface.
Enhanced Analysis
Combines search engine power with visualization tools for enhanced analysis.
Benefits and Future of ElasticSearch
Слайд 11Scalable and Reliable
ElasticSearch offers scalability and reliability for various applications.
Comprehensive Toolset
Combines search engine capabilities with powerful analysis tools.
Future Prospects
Continuous development and community support ensure a bright future.
