Elasticsearch Fundamentals

Overview

This is the fastest way to get started with Elasticsearch. A quick 2-hour session that will get you updated on core Elasticsearch concepts and how to spin up a cluster, index data, run searches and aggregations.

Who Should Attend

This Elasticsearch online course is designed for anyone who wants to understand how Elasticsearch works, or to get started in setting it up for either product search or log aggregation.

Why Attend

The virtual Elasticsearch training gives you and your team a quick, yet deep dive into using Elasticsearch and how it works under the hood. Further benefits:

  • A customized learning experience, targeted for solving specific use-cases
  • Classes are instructor-led and exercises are derived from years of working with clients.
  • Small class sizes allowing for more interaction and more time to discuss what matters to you in practice.
  • More flexible – no need to travel, a short class is easier to fit in your schedule
  • Same high-quality instruction as our public or private Elasticsearch classes

Things to Remember

For the online training, all participants must use their own computer with OSX, Linux, or Windows, with the latest version of Docker installed. A modern browser is needed to join the virtual classroom, as well as a working headset, microphone and camera.

Participants should also be comfortable using a terminal/command line. Sematext provides:

  • A digital copy of the training material, including exercises
  • An archive with Docker Compose files, configs, scripts, etc.

Course Outline

  1. Basic flow of data in Elasticsearch
    • What is Elasticsearch and typical use-cases. Strengths and weaknesses
    • How to install Elasticsearch and what are the main configuration files
    • Indexing a document: what is an index, type and ID
    • Field types in your mapping: text, keyword, numeric and geo
    • What’s the difference between a stored and and indexed field. What is _source?
    • How text analysis influences what matches and what doesn’t
    • Getting a document by ID. Why is it so expensive?
    • Anatomy of a search
    • Adding aggregations to a search
    • Doc values and why you need to store the same data a third time (in addition to indexed fields and _source)
    • How updates work and why you should avoid them if possible
    • Why deletes are soft and when data is really expunged
    • Lab
      • CRUD operations
      • Running a full-text search
      • Running aggregations on query results
      • Pagination
  2. Working with an Elasticsearch cluster
    • What are primary and replica shards. How failover works
    • How searches are distributed to multiple shards (of one or multiple indices)
    • Configuring unicast to tell nodes how to join a cluster
    • Using Cat APIs to get the current state of the cluster
    • Lab
      • Creating indices with different numbers of shards
      • Checking the health of the overall cluster and specific indices
      • Adding new nodes to the cluster