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Proposal for nested document support in Lucene

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• 1. Nested Documents in Lucene
High-performance support for parent/child document relations
mark@searcharea.co.uk
• 2. Problem:
The Lucene data model is based on Documents, Fields and Terms. However many real-world data structures cannot be properly represented when collapsed into a single Lucene document.
Single
Lucene
document
• 3. Problem: “Cross-matching”
When two or more data structures of the same type are jumbled up into a single Lucene field, matching logic becomes confused e.g. >1 qualification in a resume
John
Name
John
A1 in Maths
A1, E1
E1 in Science
Subject
Maths, Science
!
False match for query:
• 4. Unacceptable solution #1
One modeling approach is to store related items in the same field and use proximity operators in queries
Name
John
A1 Maths….E1 Science
John
Example query:
A1 in Maths
E1 in Science
!
Slow
!
Not scalable with number of fields
• Loss of fieldnames as context in query
• 5. Proximity distances must grow.
• 6. Only one choice of Analyzer for given field
• Unacceptable solution #2
Use numbered fieldnames to group related structures
Name
John
Example query:
Subject1:Science)
OR
Subject2:Science )

A1
Maths
Subject1
E1
John
Subject2
Science
A1 in Maths
E1 in Science
!
Slow
!
Not scalable with number of nested structures
• More numbered fieldnames = more query complexity and more unique tokens in index
• Solution: Nested documents
The existing Lucene codebase can be used to simply store multiple “nested” documents to represent arbitrarily complex structures. Related documents are just added in sequence
John
Name
John
A1 in Maths
A1
E1
E1 in Science
Subject
Maths
Subject
Science
?
But how to query?....
• 7. Solution: Nested Document Queries
Nested documents need to be queried using new NestedDocumentQuery class which understands document relationships
John
Name
A1
E1
docType
resume
Subject
Maths
Subject
Science
New NestedDocumentQuery
• Executes child search using any arbitrary Lucene Query object e.g. Boolean, fuzzy, numeric etc
• 8. Reports any matches as a match on the parent document not the child
• 9. Super-fast evaluation of joins between child and parent
• 10. Requires an indexed field to identify parent documents
?
• 11. Solution: Example Query
Find resume of person called “John” with A1 grade in Maths
John
Name
E1
A1
resume
docType
Subject
Science
Subject
Maths
The NestedDocumentQuery wrapper simply translates the stream of reported matches from the child-level query criteria into matches on the parent for evaluation of all the parent-level logic
• 12. Solution: Join speed
Unlike a database, the cost of a join (child to parent) is blisteringly fast
3) Find first prior set bit e.g. position #356,670
100000100000000100000001000000010000001000010000000001000000100000100001
2) Index directly into cached BitSet at position #356,675
1) Match reported on document #356,675
ParentQuery
4) Attribute match to doc #356,670
NestedDocumentQuery
ChildQuery
The BitSet for defining parents is obtained from a Filter and can be cached aggressively with minimal memory cost (one bit per document in the index)
Parent-child document relationships can also be used to limit child results from any one parent (e.g. efficiently control the max number of pages returned from any one website)
Nesting levels can be arbitrarily deep
Very powerful multi-child queries possible e.g. find people likely to know person X using resume’s employment histories (multiple employer names/urls and related date-ranges)
• 14. “Lucene is not a database”, but…..
Structure matters
Many data sources are a mix of structured and unstructured content (e.g. microformats). This is unlikely to change. Lucene has historically been about unstructured text but has steadily been adding structured capability (Trie, spatial, facets) and become a great solution for hybrid data. However support for modeling and querying non-trivial data structures is missing currently.
Relationships matter
This proposal is not to recreate the full capabilities of a SQL database with arbitrary relationships. However we can benefit greatly from providing simple parent-child relationships
We have some unique capabilities
Parent-child joins are very fast
Unlike SQL we can return partial, relevance-ranked matches
Probably more akin to XML databases than SQL databases
• 15. Next steps
Existing code/unit tests can be released to Lucene project if there is sufficient interest. This software has been deployed in production on large datasets.
The matching approach is reliant on parents and children being held in the same Lucene index segment. Additional control is needed to enforce this more rigorously - either by
Adding more user-control over IndexWritersegment creation where applications understand/control parent-child dependencies OR
Making Lucene aware of parent-child relationships e.g. new method Document.add(Document)
Query parser support
XML Query Parser support is available
End-user Query parser could add new syntax e.g. +candidateLocale:UK +child(grade:A1 AND subject:music)
• 16. Thoughts?
Feedback encouraged on dev@lucene.apache.org