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


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