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Elasticsearch Fundamentals Course

Get Started with Elasticsearch


Our Elasticsearch training classes have a 4.74/5 rating based on 20 reviews

This is the fastest way to get started with Elasticsearch. A quick 2-hour course that will get you up to speed on all core Elasticsearch concepts and how to spin up a cluster, index data, run searches and aggregations. This Elasticsearch 101 video training is taught by Radu Gheorghe‌‌, a seasoned Elasticsearch instructor, developer and consultant from Sematext, author of “Elasticsearch in Action”, and frequent conference speaker.

Why attend?

  • Small, interactive, instructor-led classes
  • Lots of hands-on exercises, tutorials and training materials
  • Customized learning experience
  • More flexibility – no need to travel
  • Real-world use cases and scenarios
  • Certificate of Completion included

What’s Included

  • 2 hours online training
  • A digital copy of the training material
  • Docker Compose files, configs, scripts, etc.
  • Certificate of Completion

Next Class: TBA See Upcoming Classes

$200.00 -10% Early Bird Register Now

Full day classes available upon request

Looking for a more general and extended knowledge-based Elasticsearch training?

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Who should attend?

This Elasticsearch online course is designed for anyone who:

  • Wants to quickly understand Elasticsearch basics and how it works
  • Is getting started with setting up Elasticsearch for either search or log aggregation

What attendees say

Sematext was an ideal training partner for We had just recently adopted Elasticsearch on a new project, and they gave us two days of solid training that was tailored to our team’s needs. The material was built atop strong foundations and moved quickly into advanced areas around querying, Lucene internals, and cluster performance. It was clear that it was all informed by real-world experience operating these systems at scale.

Andrew Montalenti CTO/Founder –

Course Outline

Basic flow of data in Elasticsearch
  • What is Elasticsearch, strengths and weaknesses and typical use-cases.
  • 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 is the difference between stored and indexed fields. 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
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

Main Topics

  • What is Elasticsearch?
  • Elasticsearch Basic Concepts
  • Elasticsearch Strengths and Weaknesses
  • Elasticsearch Installation
  • Elasticsearch CRUD operations
  • How to Run Searches and Aggregations
  • Field Types in the Mapping
  • Text Analysis
  • Clustering, Failover, Distributed Search

Elasticsearch Training

Upcoming Classes

Pick from a wide range of short (2h), use case focused classes to match your exact needs. Delivery method: Live Online. Time: 11:00 AM to 1:00 PM ET.

To be announced
Radu Gheorghe

About the trainer

Radu Gheorghe

Your trainer is an active Elasticsearch consultant. Radu has worked with clients from 20+ different industries and is the author of Elasticsearch in Action. Here are some issues that Radu solved for Sematext clients recently:

  • Improved search relevancy using Learning to Rank
  • Optimized multiple petabyte-scale clusters. Some up to 400 nodes.
  • Designed Elasticsearch index and cluster architecture for dozens of clients
  • Optimized log ingestion pipelines to parse and enrich 100K+ events/second
  • Helped clients and DevOps teams reduce production Elasticsearch and ingestion pipeline costs by as much as 10x

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