Microsoft Technology Licensing, LLC

Dragan Tomic

Shankar Pal

Istvan Cseri

Oliver Nicholas Seeliger

Gideon Schaller

Michael Rys

Joseph Xavier

Wei Yu

Stefano Stefani

Ramachandran Venkatesh

Beysim Sezgin

Conor J Cunningham

Jose A Blakeley

Jonathan David Morrison

Mark Connolly Benvenuto

Stanislav A Oks

Bruno H M Denuit

Denis Y Altudov

Balaji Rathakrishnan

Denis Churin

The present invention provides 'XML Schema Collections' and methods and systems for using the same. XML data is typically stored as an XML instance, each of which should conform to a 'schema' according to a desired goal. An XML schema provides identification and organization for the data supplied by an XML instance. XML Schema Collections are collections of one or more XML schema namespaces. An storage location designated for storage of XML data, such as an XML column in a relational database, can be &#x201c;typed&#x201d; with an XML Schema Collection object, allowing that storage location to store XML instances that conform to more than one XML schema. XML Schema Collections provide increased data storage versatility, and facilitation of data searches.

XML schema collection objects and corresponding systems and methods

The present invention provides 'XML Schema Collections' and methods and systems for using the same. XML data is typically stored as an XML instance, each of which should conform to a 'schema' according to a desired goal. An XML schema provides identification and organization for the data supplied by an XML instance. XML Schema Collections are collections of one or more XML schema namespaces. A storage location designated for storage of XML data, such as an XML column in a relational database, can be &#x201c;typed&#x201d; with an XML Schema Collection object, allowing that storage location to store XML instances that conform to more than one XML schema. XML Schema Collections provide increased data storage versatility, and facilitation of data searches.

Modifying a portion of an XML document stored in a relational database includes converting operations on the document into an operator tree. The operator tree includes a first operator corresponding to a first portion of the schema for the modified data and a second operator corresponding to a parent portion of the schema for the modified data. A first and a second portion of the schema are extracted from the overall document schema. A first validation of the modified data using the first operator with the first portion of the schema is performed. This forms a partially validated XML document portion. Next, a second validation of the partially validated XML document portion with the second portion of the schema is performed using the second operator. The XML document constraints are verified and the modified data is merged into the XML document, thus avoiding a full validation of the XML document when certain XML Schema types are absent in the modified data.

Partial XML validation

Caching architecture that facilitates translation between schema data and relational structures. A schema translation component consumes schema data (e.g., XML schema data) having a schema structure. The schema structure is shredded into tables. A validation component interfaces to a memory management interface to facilitate loading only the necessary components to perform instance validation. During validation, only parts of the schema that are used are loaded and cached. A schema cache stores the in-memory representation of the schema optimized for instance validation. The schema components are loaded from metadata into the cache memory as read-only objects such that multiple users can use the in-memory objects for validation.

Memory cache management in XML/relational data mapping

Several embodiments of the present invention are directed to systems and methods for extending the UDT framework of an extended relational data store (ERDS) to include support for unordered collections (multisets) and ordered collection (lists). More specifically, several embodiments of the present invention use an UDT infrastructure, CLR generics, and a new UNNEST operator to create and utilize a special type abstraction for collections that is simultaneously a scalar and a relation. As a scalar, this collection type can be processed by all parts of the data store engine that understand scalars (including but not limited to the client stack) and, as a relation, this collection type is queriable like any other type of relation.

Systems and methods for the implementation of unordered and ordered collections in a data store

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Redmond, WA, United States of America

Dragan Tomic