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Using Elasticsearch and Kibana

6 hours on-demand video

$ 11.99

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Brief Introduction

Scalable Search and Analytics for Document Data

Description

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

Requirements

Requirements
A basic understanding of HTTP and JSON (Javascript Object Notation)
Python is helpful for the portions of the course that deal with the ES Python client

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