Elasticsearch

Elasticsearch course is intended for those who want to learn how to use technology Elasticsearch to store and to retrieve large amounts of data to be easily scaled. Whether you're building a full-text search on the web for your customers to store, analyze and visualize large amounts of logs or clearly have access to all the data that are part of your business in one place for you designed just for this course. After its completion, you will understand the technology Elasticsearch and you will be able to use for your specific requirements.

The course is made up of several blocks, where each participant will understand the area and then try it immediately. At the same time for each circuit receives the material, which will make possible a given issue at any time to refresh.

Audience:

The course is focused on all IT professionals who need to solve the problem of storing large amounts of data in which they want to easily search and visualize it.

Prerequisites:

Basic knowledge of database systems.

Course goals:

Participants also learn:

  • Elasticsearch (2.x)
  • How to store and search unstructured data
  • Understand how it works full-text search, and how to create it
  • How to handle large amounts of data and easily scale horizontally
  • Warp

Course content:

Why Elasticsearch?

  • Introduction
  • Basic work with Elasticsearch
  • Familiarization with basic tools
  • CRUD
  • Indexation, bulk operations
  • Lab
  • Mapping

Mapping

  • Index, type, field
  • Data types
  • Dynamic properties
  • Templates indices
  • Lab

Introduction to text analysis

  • Unstructured data
  • Simple search relevance
  • Lab
  • Text analysis

Text analysis

  • Introduction to text analysis
  • Analyzers - Text token and filters
  • Working with Czech and other languages
  • Synonyms
  • Lab

Data search

  • Distributed Search
  • Queries, Filters
  • Query DSL
  • Searching in multiple fields
  • Best practices
  • Lab

Agregation

  • Basics aggregations
  • Calculations of data aggregation summary
  • The most widely used aggregation in depth
  • Best practices
  • Lab

Suggestions

  • Replenishment words and phrases
  • Context, phrase, term suggestors
  • As to the "Did You namysli"?
  • Best practices
  • Lab

Data modelling

  • How to model relationships between objects
  • Parent-child bond
  • Subdocuments
  • Best practices
  • Lab

Stored queries

  • Percolator
  • Warmer
  • Lab

Study materials:

  • Printed materials following the presentation and labs

About the instructor: Petr Novotny

Petr's knowledge goes from solution architecture to development (JavaScript, PHP) through Elasticsearch, Oracle, PL/SQL to agile methodology and SCRUM. At the same time, Petr has been working with Elasticsearch technology for several years and has become one of our main instructors.

 

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