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MARKLOGIC DATABASE (Storing Data in MarkLogic (URI ( each document has a…
MARKLOGIC DATABASE
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Indexes
- provides real-time queries on extremely large databases
- baseline (default) indexes: as a document gets loaded into a database, MarkLogic creates an index of all of the words in the document, as well as the structure of the document
- additional indexes: depends on application
- adding additional indexes takes up additional disk space and makes the loading the documents take longer
- some MarkLogic features (facets, semantics etc.) requires that supporting indexes exist
Adding an Index
- indexes are added to a MarkLogic database via the Admin interface
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Using Semantics
- MarkLogic can be used to store RDF triples and process SPARQL queries
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- like LinkedIn - "you know somebody, he/she knows somebody else maybe you know"
- semantic data is stored in RDF (Resource Description Framework) triples which are composed of a subject, predicate and object
- RDF triples relate one item to another
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Search Feature
- search feature is included in the core of MarkLogic
- MarkLogic is able to offer powerful search abilities in real-time
To allow an application to search the documents in a MarkLogic database, there are a number of programming interfaces available:
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2) Search API
- available in XQuery through the use of the search:search() functon (functions needs to first be imported)
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Read Data
Query Console
- using either fn.doc() or fn:doc() without an argument returns all of the documents in a database
- to access an individual document, the URI of the document can be included in the fn.doc() function (e.g. fn.doc('/patents/waterski_drone.json');)
- for retrieving documents in a database, the JavaScript fn.doc() function, or the XQuery fn:doc() function, can be used.
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