Core ElasticSearch Developer Training | Learn Distributed Search Application Development with ElasticSearch

Core ElasticSearch for Developers Course Description

Get to learn the internals of Elasticsearch from a developer’s perspective, including how to write search queries, perform text analysis, define mappings, perform aggregations, and model data.

This interactive instructor-led, hands-on course is focused on teaching Elasticsearch fundamentals so that you can effectively design and build applications that leverage it. The course starts with an introduction to Elasticsearch and its API, and then moves into detailed concepts like search, aggregations, and much more. Best practices and examples for document design, testing, and other software development design considerations are also covered.

Core ElasticSearch for Developers Course Learning Outcomes

  • Understanding fundamental concepts
  • Uncover best practices & key features
  • Learn distributed search application development with Elasticsearch

Core ElasticSearch for Developers Training - Suggested Audience

This Core elastic search training is intended for developers who would like to build real-time search solutions & analytics solutions. Suggested attendees based on our past programs are:
  • Developers
  • Engineers
  • Software Architects

Core ElasticSearch for Developers Training Duration

  • Open-House F2F (Public): 2/3/4 days
  • In-House F2F (Private): 2/3/4 days, for commercials please send us an email with group size to

Core ElasticSearch for Developers Training - Prerequisites

  • No prior knowledge of Elasticsearch is required.
  • Participants should be software developers familiar with programming concepts
  • Participants should be familiar with running commands from a command line or terminal.
  • Exposure to or interest in Elasticsearch, relational databases, distributed systems, or information retrieval. 

System Setup Requirements

  • Participants shall bring their own laptop with at least 20% free disk space.
  • Java version 1.7u55 and above should be installed prior to the course.
  • Laptop with connectivity to Wi-Fi
  • Mac, Linux OS, or Windows 7 or later
  • A modern web browser

Core ElasticSearch for Developer training outline includes:

1. Elasticsearch Overview 
  • What and Why
  • Terminology: Documents, Index, Shards, Node, Cluster

  • Index, Re-Index, Update and Delete APIs Under the Hood 
  • Multi Get and Bulk Operations 
  • Write Consistency 
  • Versioning 
  • Sense Console

3. Text Analysis
  • Inverted Index
  • Analysis Fundamentals 
  • Filters, Tokenizers, and Analyzers 
  • Analysis Testing 
  • Configuration 
  • Synonyms 
  • Lab

4. Mappings
  • What and Why 
  • Dynamic Mapping 
  • Data Types 
  • Multi Fields 
  • Dynamic Field Mapping 
  • Index Templates 
  • Lab

5. Search
  • Query and Filter Context
  • Query DSL (Match, Term, Bool, etc.)
  • Multi Search
  • Rescoring
  • Highlighting
  • Lab

6. Search Internals
  • Pagination and Deep Pagination
  • Search Types and Internals
  • Search Performance Under the Hood 
  • Search Best Practices 
  • Lab

7. Suggestions
  • What and Why 
  • “Did you mean?” (Terms and Phrase Suggesters)
  • Auto-Complete Functionality (Completion Suggester) 
  • Best Practices 
  • Lab

8. Aggregations
  • What and Why 
  • Aggregations Scope 
  • Buckets and Metrics 
  • Deep Dive Into More Than 20 Aggregations 
  • Collect Mode 
  • Pipeline Aggregations 
  • Lab

9. Document Modeling
  • What and Why
  • Relationships in Elasticsearch (Nested Documents and Parent/Child) 
  • Organizing Your Data 
  • Impact of Document Structure on Search 
  • Best Practices and Examples for Document Design

10. Relevancy 
  • What and Why 
  • Vector Space Model, TF/IDF, and Lucene Ranking Formula 
  • Boosting and Custom Score 
  • Lab

11. Percolator 
  • What and Why 
  • Percolate API 
  • Percolate Internals 
  • Percolate Filtering, Scoring, Highlight, Aggregations 
  • Strategies and Best Practices

12. Clients, Testing, Integrations 
  • Elasticsearch Clients Overview 
  • Testing Considerations 
  • RDBMS and NoSQL Integrations
Keny White


Keny White is Professor of the Department of Computer Science at Boston University, where he has been since 2004. He also currently serves as Chief Scientist of Guavus, Inc. During 2003-2004 he was a Visiting Associate Professor at the Laboratoire d'Infomatique de Paris VI (LIP6). He received a B.S. from Cornell University in 1992, and an M.S. from the State University of New York at Buffalo.


After working as a software developer and contractor for over 8 years for a whole bunch of companies including ABX, Proit, SACC and AT&T in the US, He decided to work full-time as a private software trainer. He received his Ph.D. in Computer Science from the University of Rochester in 2001. "What I teach varies from beginner to advanced and from what I have seen, anybody can learn and grow from my courses".


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