Topic

Lucene

1 post about Lucene. Every summary links to the original.

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MongoDB
Data Modeling and Schema Design for MongoDB Search Part 1: Practical Considerations
Data modeling for MongoDB Search requires balancing conceptual, logical, and physical schema decisions against workload demands and system constraints. The $search stage must be the first in an aggregation pipeline, queries a single Search index, and runs against a single collection, with results returned in relevancy order. The underlying Lucene engine supports two mappings for arrays of sub-documents: default document mapping flattens fields into one index object, while embeddedDocuments mapping creates separate Lucene index objects per sub-document. Embedded mapping enables cross-field matching within sub-documents but explodes the index object count and causes heavy reindexing on any update, as the entire block is deleted and re-added. This post establishes the foundational concepts and physical constraints that will inform schema patterns in Part 2.

The best engineering reads, once a week.

Topic

1 post about Lucene. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

MongoDB
Data Modeling and Schema Design for MongoDB Search Part 1: Practical Considerations
Data modeling for MongoDB Search requires balancing conceptual, logical, and physical schema decisions against workload demands and system constraints. The $search stage must be the first in an aggregation pipeline, queries a single Search index, and runs against a single collection, with results returned in relevancy order. The underlying Lucene engine supports two mappings for arrays of sub-documents: default document mapping flattens fields into one index object, while embeddedDocuments mapping creates separate Lucene index objects per sub-document. Embedded mapping enables cross-field matching within sub-documents but explodes the index object count and causes heavy reindexing on any update, as the entire block is deleted and re-added. This post establishes the foundational concepts and physical constraints that will inform schema patterns in Part 2.

The best engineering reads, once a week.