OpenSearch for Product Searches
Make Enterprise Search Better
This 8-hour online course focuses on E-commerce or similar enterprise search use-cases (e.g. searching for phones, books, people, blog posts). Because relevancy is important for enterprise search: OpenSearch 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 OpenSearch instructor, consultant from Sematext and frequent conference speaker will be your trainer.
What's Included
- 8-hour online training
- A digital copy of the training material, cheat-sheets, slides
- Docker Compose files, configs, scripts, etc.
- Certificate of Completion
Who should attend?
This OpenSearch online course is designed for anyone who:
- Has a basic understanding of OpenSearch's core concepts (documents, shards, basic queries)
- Is looking to implement Enterprise search (e.g. E-commerce, book search, people search, etc).
Why attend?
- Small, interactive, instructor-led classes
- Lots of hands-on exercises
- Customized learning experience
- Flexible - no need to travel
- Certificate of Completion included
Get Certified Upon Course Completion
Enroll in our course and take the next step in your professional journey.
Complete the course and receive a certificate that showcases your newly acquired skills.
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).
OpenSearch for Product Searches
June 3-4, 2024 | $800 / person | See Course Outline | Register 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 OpenSearch 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) as well as Zoom.
- Participants should be comfortable using a terminal/command line.
- Participants need a working audio and video setup for labs, which are done in groups.
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](https://sematext.com/wp-content/themes/sematext-next/inc/images/team/radu-gheorghe.png)
Your trainer is an active OpenSearch consultant who worked with clients from many different industries on OpenSearch, Elasticsearch and Solr projects for 10+ years.