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).
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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
Your trainer is an active OpenSearch consultant who worked with clients from many different industries on OpenSearch, Elasticsearch and Solr projects for 10+ years.