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 Grade E1 in Science Subject Maths, Science ! False match for query: Grade:A1 AND Subject:Science
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 Grade docType Grade 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)
13. Other advantages 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)
