Elasticsearch for product searches
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13+
years of experience
100+
enterprise clients
30%
Avg cost reduction
15k+
clusters optimized
About the course
This 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.
Get certified upon 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.
Course curriculum
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