The talk is about designing Solr schema and different use cases in e-commerce world. It shares our experience with Solr Schema and how it evolved while building multi-tenant search platform.

1. Solr Schema Learnings
Mohit Jain, Staff Engineer
BloomReach
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2. Solr Schema
• Schema.xml – Solr 4.6.1
 Fields – stored, indexed, single/multi etc.
<field name="text" type="text_general" indexed="true"
stored="false" multiValued="true"/>
 FieldTypes
• Primitive, e.g. int, string
• Analyzed, e.g. text, ngrams
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3. Solr Schema
• Text Search
 Dump everything to text
 Store structured fields if needed
• E-commerce
 Multiple applications per field
 Facets, n-gram search, natural text
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4. Schema in e-commerce world
• Brand
 One Base field – Facet
 Multiple Copy Fields – text, n-gram,
hierarchical paths etc.
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Field Name Stored Indexed Type
Brand True True Facet (=String)
Brand_text False True text
Brand_ngra
m
False True ngram
• Facet = String = Stored
• Store a copy of every field for debugging

5. Multi Tenant
• More customers = more fields
• Common fields + merchant Fields
 Field names
• brand, color, title
• debshops_*, e.g. color_group
 Operational overhead for indexer and
deployment
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6. Common Schema
• One schema.xml to rule them all
• Optimization cost v/s simplicity in early
stages
• Indexer, ranking etc.
• Solrcore.properties – Solrconfig.xml
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7. Customers
• Common schema is not scalable
 f_* = MultiValued + String
• Customer requests for Filters
 f_oven_type
• Different Use cases and 100+ fields
 Range queries = String vs Number, e.g.
Range
 Sort = single-valued vs multi-valued, e.g.
Ratings
 Stored ??7

8. Dynamic Fields
• Ranking cannot depend on dynamic fields
• Indexer and Search-Consumers –
common lib
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DYN_S_S DYN_S_M DYN_N_S DYN_N_M
Sort, facet facet Sort, range Range
dept oven_type ratings item_length
• Dynamic Fields – DYN_<S/N>_<S/M>
• Datatype – String (S), Number(N)
• Single Valued(S), Multi-Valued (M)

9. Questions
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