Abstract: A method is disclosed. The method includes receiving, from a receiver institution computer, an interaction request message for an interaction with a sender identifier associated with a sender and interaction details. The method also includes transmitting a plurality of notifications comprising the sender identifier to a plurality of sender institution computers. The method also includes receiving a plurality of responses from the plurality of sender institution computers, one or more responses indicating that the sender identifier is stored at the sender institution computers, and then providing the interaction details and/or additional interaction details to one or more of the sender institution computers that store the sender identifier.

Abstract: The embodiments relate to assigning data to processors of a file system. Metadata associated with respective blocks of data, and an initial batch of the blocks is assigned to nodes of a file system based on the metadata. Unassigned blocks are selectively assigned to one or more of the nodes. The selective assignment includes constructing a linear regression model based on node data, and determining a value for each node based on the linear regression model. Each value is associated with a predicted load corresponding to a new assignment of one or more unassigned blocks.

Abstract: A storage engine may selectively maintain a spatial index for accessing spatial data. A spatial query may be received and the portions of the spatial index to evaluate may be determined by replacing those portions associated with regions identified for the query that do not exist in the spatial index with portions that do exist in the spatial index and are associated with a region that includes the identified regions. When inserting spatial objects into the spatial index, a determination may be made whether to create a new portion in the index if none currently exist that match a spatial index value for a new spatial object or to modify the spatial index value of the spatial object to insert the spatial object into an existing portion of the spatial index.

Abstract: The embodiments relate to assigning data to processors of a file system. Metadata associated with respective blocks of data, and an initial batch of the blocks is assigned to nodes of a file system based on the metadata. Unassigned blocks are selectively assigned to one or more of the nodes. The selective assignment includes constructing a linear regression model based on node data, and determining a value for each node based on the linear regression model. Each value is associated with a predicted load corresponding to a new assignment of one or more unassigned blocks.

Abstract: The embodiments relate to assigning data to processors of a file system. Metadata associated with respective blocks of data, and an initial batch of the blocks is assigned to nodes of a file system based on the metadata. Unassigned blocks are selectively assigned to one or more of the nodes. The selective assignment includes constructing a linear regression model based on node data, and determining a value for each node based on the linear regression model. Each value is associated with a predicted load corresponding to a new assignment of one or more unassigned blocks.

Abstract: The embodiments relate to assigning data to processors of a file system. Metadata associated with respective blocks of data, and an initial batch of the blocks is assigned to nodes of a file system based on the metadata. Unassigned blocks are selectively assigned to one or more of the nodes. The selective assignment includes constructing a linear regression model based on node data, and determining a value for each node based on the linear regression model. Each value is associated with a predicted load corresponding to a new assignment of one or more unassigned blocks.

Abstract: Embodiments of the invention relate to a multi-level database compression technique to compress table data objects stored in pages. A compact dictionary structure is encoded that represents frequent values of data at any level of granularity. More than one level of compression is provided, wherein input to a finer level of granularity is an output of a coarser level of granularity. Based upon the encoded dictionary structure, a compression technique is applied to a stored page to compress each row on the page. Similarly, a de-compression technique may be applied to decompress the compressed data, utilizing the same dictionary structures at each level of granularity.

Abstract: Embodiments of the invention relate to a multi-level database compression technique to compress table data objects stored in pages. A compact dictionary structure is encoded that represents frequent values of data at any level of granularity. More than one level of compression is provided, wherein input to a finer level of granularity is an output of a coarser level of granularity. Based upon the encoded dictionary structure, a compression technique is applied to a stored page to compress each row on the page. Similarly, a de-compression technique may be applied to decompress the compressed data, utilizing the same dictionary structures at each level of granularity.

Abstract: A system and method is provided for processing XQuery Updates on an Extensible Markup Language (XML) document. The XQuery Updates are processed in three phases. The first phase includes creating a pending update list (PUL) including all update operations to be performed on nodes in a fragment of the Extensible Markup Language (XML) document. The second phase includes sorting the PUL. The third phase includes applying the sorted PUL to each node in the XML fragment during a single traversal of the XML fragment.

Abstract: A system and method is provided for processing XQuery Updates on an Extensible Markup Language (XML) document. The XQuery Updates are processed in three phases. The first phase includes creating a pending update list (PUL) including all update operations to be performed on nodes in a fragment of the Extensible Markup Language (XML) document. The second phase includes sorting the PUL. The third phase includes applying the sorted PUL to each node in the XML fragment during a single traversal of the XML fragment.