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Elasticsearch for Product Searches

Make Product Search Better


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

This 2-hour online course focuses on E-commerce or similar product search use-cases (e.g. searching for phones, books, people, blog posts). Because relevancy is important for product search: Elasticsearch shouldn’t return “phone accessories” on a query for “phone”. Other challenges might come up as well, for example dealing with relational data, providing autocomplete or did-you-mean functionality. This course provides solutions to these challenges. Radu Gheorghe, a seasoned Elasticsearch instructor, and consultant from Sematext, author of “Elasticsearch in Action”, and frequent conference speaker will be your trainer.

Why attend?

  • Small, interactive, instructor-led classes
  • Lots of hands-on exercises
  • Customized learning experience
  • More flexible – no need to travel
  • Certificate of Completion included

What’s Included

  • 2-hour 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:

  • Has a basic understanding of Elasticsearch’s core concepts (documents, shards, basic queries)
  • Is looking to implement product search.

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

Relevancy tuning
  • Using ngrams and shingles to tolerate typos, while boosting relevant matches
  • How is relevancy score calculated?
  • Searching across fields to detect user intent
  • Balance precision and recall by using different variants of the same field
  • Using the Function Score Query to boost documents by recency, region and other business criteria
  • Lab
    • Using ngrams and shingles to boost more exact matches
    • Boosting documents based on recency
    • Dealing with stopwords efficiently
Relational data in Elasticsearch
  • Arrays and objects: fastest way to deal with one-to-one relations
  • Nested documents: quick searches for low-velocity data
  • Parent-child relationships: fastest way to update
  • Dealing with many-to-many relationships via application-side joins
  • Lab
    • Searching across a relationship between two documents
    • Showing both sides of the relationship in the results
  • Term suggester: providing did-you-mean for each word
  • Phrase suggester: did-you-mean for the whole query
  • Quick autocomplete with the completion suggester
  • Filter autocomplete results with the context suggester
  • Lab
    • Implementing did-you-mean functionality
    • Implementing autocomplete functionality
Highlighting query results
  • Default highlighting: fast and flexible for short fields
  • Term offsets: quick highlighting for content fields
  • Term vectors: paying with storage to get the best of both worlds
  • Lab
    • Add highlighting for query results

Main Topics

  • Balance precision and recall through analysis tweaks
  • Using DisMax and Function Score to make relevant documents rank higher
  • Suggesters for did-you-mean and autocomplete functionality
  • Highlighting query results

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 problems 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 reduce production Elasticsearch and ingestion pipeline costs by as much as 10x

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