Abstract: Detailed herein is a technology which, among other things, allows a search engine to utilize a user-defined relevance function. In one approach to the technology, a method of applying a user-defined relevance function is described. In this approach, a complex search query is decomposed into a simple operator. The simple operator is associated with the user-defined relevance function. A document which matches the search query is retrieved, and a rank is calculated for the document, using the user-defined relevance function.

Abstract: Detailed herein is a technology which, among other things, allows a search engine to utilize a user-defined relevance function. In one approach to the technology, a method of applying a user-defined relevance function is described. In this approach, a complex search query is decomposed into a simple operator. The simple operator is associated with the user-defined relevance function. A document which matches the search query is retrieved, and a rank is calculated for the document, using the user-defined relevance function.

Abstract: 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.

Abstract: An extensible markup language (XML) expression included in a query is parsed to yield an abstract syntax tree. The abstract syntax tree is then transformed into a unified tree including XML algebra operations. The unified tree is then converted into a relational tree including enhanced relational algebra operations. The relational tree is then forwarded to a query processor for optimization and execution of the query at the query processor.

Abstract: An update to a primary table is received. The primary table is read to determine the set of rows to be updated. The primary table is updated and XML objects stored in XML columns are overwritten according to the update. A pre-update node table comprising the nodes corresponding to the updated rows is created from an XML index table corresponding to the primary table. A post-update node table is created by shedding the updated XML objects. The post-update table and the pre-update table are merged according to their node identifiers. The resulting merged table can be inspected to determine which nodes have been, added, deleted, or updated. Based on this inspection, the necessary additions and deletions can be efficiently made to the XML index table.

Abstract: An extensible markup language (XML) expression included in a query is parsed to yield an abstract syntax tree. The abstract syntax tree is then transformed into a unified tree including XML algebra operations. The unified tree is then converted into a relational tree including enhanced relational algebra operations. The relational tree is then forwarded to a query processor for optimization and execution of the query at the query processor.

Abstract: 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.

Abstract: Storing and querying XML data in a primary table or document utilizes an index of XML data and includes creating a primary table structure, creating a primary XML index commensurate with the primary table structure, populating the primary table and the primary XML index, and running a query on the XML data in a primary table by utilizing the XML index. The XML index can be implemented as a node table. The node table may have a B+-tree structure and be populated by shredding the XML values in the primary table. The XML data may be stored as binary large objects in an XML column of the primary table. Secondary XML indexes may be created to assist in the search and retrieval of XML data stored in the primary table. Both the primary XML index and the secondary XML index tables may be created using data definition language statements.