Live Elasticsearch Online Training starting on March 2! See all classes


Elasticsearch

Elasticsearch for Product Searches

Make Product Search Better

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

This 8-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.

See Course Outline

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 Enterprise search (e.g. E-commerce, book search, people search, etc).

What's Included

  • 8-hour online training
  • A digital copy of the training material
  • Docker Compose files, configs, scripts, etc.
  • Certificate of Completion

Next Class March 9-10, 2023

Upcoming Classes

Price $800

Register Now

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 attendees say

Sematext was an ideal training partner for Parse.ly. 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 Andrew Montalenti
CTO/Founder – Parse.ly

Not your typical by-the-book training. Radu was engaging and was a great guide in our journey through Elasticsearch.

Chris Hirsch Chris Hirsch
Staff Engineer - Wayfair

I had to leave before the last class ended unfortunately. But had I been there I would have given you a mini-speech to tell you how awesome you were! ☺️

Thank you so much for being such a fantastic, patient, and effective instructor throughout this 4-day training. Personally, I appreciated the clarity and expertise in the material and the class.
I also thought the class was meticulously structured over the 4 days, each day not feeling too long, and with the right number of breaks - this made me feel like I had the capacity to learn the things planned for the day without feeling too overwhelmed. Having the course material is great for the team to revisit later.

Overall, we really felt like we learned a lot. To put it in perspective, <name redacted for privacy> (who worked with <name redacted> and <name redacted>) already applied some of the lessons from the training in one of our customer throughput issues today. A big progress for the team. And, I am sure we will continue to apply in the future too – I just want you to know that you have clearly influenced us ☺️

Engineering Manager, Search-Infra at Twitter

Upcoming Classes

Pick from our 8h online classes, structured to correspond to different roles and Elasticsearch knowledge levels: for beginners to experienced developers or ops who want to learn quickly. Delivery method: Live Online. Time: 09:00 AM – 01:00 PM ET (2 sessions).

elasticsearch Elasticsearch for Product Searches
March 9-10, 2023
$800 / personSee Course OutlineRegister Now!

Course Outline

Finding the right documents
  • Using normalizers
  • Customizing analyzers
  • Using minimum should match
  • Lab
    • Use and analyzer with stemming
    • Add boolean logic to your queries
Tolerant search
  • Using ngrams and fuzzy
  • Folding non-ASCII characters
  • Using shingle and word delimiter token filter
  • Validating queries
  • Lab
    • Tolerate typos with ngrams
    • Match compound words using shingles
Changing ranking
  • BM25 and other similarity formulas
  • Query explain
  • Searching in the same text analyzed in multiple ways
  • DisMax, tie-breaker and boost tuning
  • Geo search
  • Function queries
  • Lab
    • Make more exact matches rank higher
    • Boost documents by the number of views
Aggregations
  • Relationship between queries and aggregations
  • Post-filters and filter aggregations
  • Significant terms for smart categorization
  • Multiple aggregations and nesting
  • Lab
    • Implement faceted search
    • Update facet counters when one of multiple facets is selected
Autocomplete
  • Prefix queries
  • Edge ngrams
  • Completion and context suggesters
  • Aggregation with a prefix filter
  • Lab
    • Suggest documents matching a prefix
    • Suggest categories matching a prefix
After Search
  • Did you mean: terms and phrase suggester
  • Highlighting implementations
  • Lab
    • Implement did-you-mean with the phrase suggester
    • Add highlighting, getting the most relevant fragment
Relational Data
  • Denormalization
  • Query-time joins
  • Objects
  • Nested documents
  • Parent-child relationships
  • Lab
    • Search in a single field of a sub-document
    • Search in multiple fields, accounting for cross-document boundaries
    • Show the matching sub-document

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

Course key takeaways

After taking this course you will:

  • Have a deep understanding of how Elasticsearch queries and analysis work together in order to match documents
  • Be able to manipulate queries and mappings so that relevant results come up on top
  • Understand the different ways - with advantages and disadvantages - of implementing functionality around search: faceting, autocomplete, did-you-mean, highlighting
  • Be able to model your data so that it performs well and you get relevant results

Things to remember

  • Participants must use their own computer with OSX, Linux, or Windows, with a container management tool installed (Docker Desktop, Podman, nerdctl)
  • Participants should be comfortable using a terminal/command line.

Sematext provides:

  • A digital copy of the training material, including slides and many sample requests
  • A docker-compose.yml file for the lab environment

About the trainer

Radu Gheorghe

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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