Boost Specific Results you own this product

This project is part of the liveProject series Elasticsearch for a Search API
basic Elasticsearch (different boosting mechanisms)
skills learned
analyze the results of different boosting mechanisms and tune them to work together
Jettro Coenradie
1 week · 4-6 hours per week · BEGINNER

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Look inside

Help Sneakers to the Max’s customers find the perfect sneakers! As a software engineer at the e-commerce company, your task is to improve its search engine—and hopefully sales—by fine-tuning the order of search results. You’ll adjust the index mapping to import data about sneaker release dates, popularity, and in-stock status. Then, you’ll write extensions to the Elasticsearch queries that boost recent and popular results, forcing out-of-stock sneakers lower. Finally, you’ll use everything you learned to return the most relevant sneakers using a judgment list provided by the product managers. When you’re finished, you’ll have the skills to enhance Elasticsearch queries, while Sneakers to the Max’s customers will easily find the perfect pair.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Jettro Coenradie

Jettro Coenradie has worked in the search domain for more than 15 years, currently as a search relevance engineer and software architect at Luminis. He’s designed and implemented search solutions for some of the biggest e-commerce companies in the Netherlands and is a valued member of the international Search Relevance Tech community. He served as the technical editor for Manning’s Elasticsearch in Action, 1st edition, and has developed his own Elasticsearch curriculum. He’s shared his expertise in numerous blog posts and conference presentations, including at Devcon and JFall.


This liveProject is for intermediate-level Elasticsearch practitioners who are interested in learning to boost specific search results. To begin these liveProjects you’ll need to be familiar with the following:

  • Basic Python knowledge
  • Basic Elasticsearch knowledge
  • Basic Kibana knowledge (use the developer console in Kibana to query special Elasticsearch endpoints)

you will learn

In this liveProject, you’ll learn to enhance Elasticsearch queries and search results relevance.

  • Use a date to boost more recent sneakers with an Elasticsearch query
  • Use an integer to boost more popular models with an Elasticsearch query
  • Use a boolean flag to negatively boost sneakers with an Elasticsearch query
  • Use the calculation of the mean average precision and a judgment list to tune the order of the returned sneakers


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book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.

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