Using Elasticsearch and Kibana
Using Elasticsearch and Kibana
Elasticsearch wears two hats: It is both a powerful search engine built atop Apache Lucene, as well as a serious data warehousing/BI technology.
This course will help you use the power of ES in both contexts
ES as search engine technology:
- How search works, and the role that inverted indices and relevance scoring play
- The tf-idf algorithm and the intuition behind term frequency, inverse document frequency and field length
- Horizontal scaling using sharding and replication
- Powerful querying functionality including a query-DSL
- Using REST APIs - from browser as well as from cURL
ES as data warehouse/OLAP technology:
- Kibana for exploring data and finding insights
- Support for CRUD operations - Create, Retrieve, Update and Delete
- Aggregations - metrics, bucketing and nested aggs
- Python client usage
Scalable Search and Analytics for Document Data
Url: View Details
What you will learn
- Construct robust, scalable search for production use in web and enterprise apps
- Query ES using the ES Domain Specific Language
- Perform aggregations to extract insights and run analytics on ES
Rating: 4.15
Level: All Levels
Duration: 6 hours
Instructor: Loony Corn
Courses By: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
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