Abstract: Techniques for history enabling a table in a database system so that past versions of rows of the history-enabled table are available for temporal querying. The table is history enabled by adding a start time column to the table and creating a history table for the history-enabled table. The start time field's value in a row of the history-enabled table indicates when the contents of the row last changed. The rows of the history table are copies of rows of the history-enabled table that have been deleted or updated. The rows include end time fields whose values indicate when the row was updated or deleted. A history table's row thus indicates a period in which the history table's row was in the history-enabled table. Temporal queries are performed on a view which is the union of the history-enabled table and the history table.

Abstract: Techniques for history enabling a table in a database system so that past versions of rows of the history-enabled table are available for temporal querying. The table is history enabled by adding a start time column to the table and creating a history table for the history-enabled table. The history table's rows are copies of rows of the history-enabled table that have changed and include start time and end time fields whose values indicate a period in which the history table's row was in the history-enabled table. Temporal queries are performed on a view which is the union of the history-enabled table and the history table. The temporal queries are speeded up by period of time indexes in which the leaves are grouped based on time period size, identifiers are assigned to the groups, and the keys of the index include the group identifiers.

Abstract: Systems, methods, and other embodiments associated with sequence matching with no more than a number E errors are disclosed. A test fragment to be located within a target sequence with at most a number E errors is received. The test fragment is broken into E+1 test sub-fragments. If one test sub-fragment is located within the target sequence with no errors; a determination is made as to whether the other test sub-fragments are located within the target sequence adjacent to the one test sub-fragment with a total of at most E errors. If the other test sub-fragments are located within the target sequence adjacent the one test sub-fragment with at most E errors, a location of the test fragment within the target sequence is returned.

Abstract: Techniques are provided for freeing up resources before operations that change the resources have successfully completed. Resources are freed up by committing database transactions that perform portions of operations before the operations themselves have successfully completed. If the operations fail to complete successfully, then “compensation information” is used to remove the effects of the committed changes that were performed as part of the operation. Techniques are also provided for allowing database transactions to update values without retaining exclusive locks on those values. Operational constraints set forth conditions that must be satisfied before an update is allowed to proceed. If an attempt is made to update a particular value that has changes that may be undone, then the database server determines a plurality of “possible result values” for the particular value. If the possible result values satisfy the operational constraint conditions, then the update is allowed to proceed.

Abstract: Systems, methods, and other embodiments associated with access control for graph data at the instance-level are described. One example method includes accepting data access constraints that are expressed as match and apply pattern pairs to enforce security policies. A user query on graph data with a security policy restricts the returned data to data that the user is authorized to access. For this purpose, a user query that includes query selection criteria corresponding to one or more match pattern criteria based on the resource referenced in the query is rewritten to include security conditions specified in the associated apply pattern to restrict access to the graph data.

Abstract: Systems, methods, and other embodiments associated with resource description framework (RDF) security are described. One example method includes generating, based on sensitivity labels associated with the contents of a triple in an RDF record, a sensitivity label. The example method may also include comparing the sensitivity label to an access label associated with an entity requesting an action associated with the record to be performed. The example method may also include performing the action upon determining that the entity has sufficient permission to request the action.

Abstract: Techniques are provided for freeing up resources before operations that change the resources have successfully completed. Resources are freed up by committing database transactions that perform portions of operations before the operations themselves have successfully completed. If the operations fail to complete successfully, then “compensation information” is used to remove the effects of the committed changes that were performed as part of the operation. Techniques are also provided for allowing database transactions to update values without retaining exclusive locks on those values. Operational constraints set forth conditions that must be satisfied before an update is allowed to proceed. If an attempt is made to update a particular value that has changes that may be undone, then the database server determines a plurality of “possible result values” for the particular value. If the possible result values satisfy the operational constraint conditions, then the update is allowed to proceed.

Abstract: Techniques for history enabling a table in a database system so that past versions of rows of the history-enabled table are available for temporal querying. The table is history enabled by adding a start time column to the table and creating a history table for the history-enabled table. The history table's rows are copies of rows of the history-enabled table that have changed and include start time and end time fields whose values indicate a period in which the history table's row was in the history-enabled table. Temporal queries are performed on a view which is the union of the history-enabled table and the history table. The temporal queries are speeded up by period of time indexes in which the leaves are grouped based on time period size, identifiers are assigned to the groups, and the keys of the index include the group identifiers.

Abstract: Techniques for history enabling a table in a database system so that past versions of rows of the history-enabled table are available for temporal querying. The table is history enabled by adding a start time column to the table and creating a history table for the history-enabled table. The start time field's value in a row of the history-enabled table indicates when the contents of the row last changed. The rows of the history table are copies of rows of the history-enabled table that have been deleted or updated. The rows include end time fields whose values indicate when the row was updated or deleted. A history table's row thus indicates a period in which the history table's row was in the history-enabled table. Temporal queries are performed on a view which is the union of the history-enabled table and the history table.

Abstract: A version control system is described for use in connection with a database management system to facilitate versioning of a database table, the system including a database table and a version control module. The database table comprises a plurality of records, each record including at least one data field for storing user data and at least some of the records including a version control field including version control information. The version control module is configured to, in response to a user query related to the database table and related to a version, generate an augmented query for processing by the data base management system, the augmented query relating to the user query and the version control information.

Abstract: A system and method for indexing and storing multi-dimensional or multi-attribute data. Data items are recursively sorted in a selected dimension (e.g., the dimension having the greatest variance) and divided until each subdivision fits into a leaf node having a specified fanout. Intermediate nodes and a root node are constructed to complete the index. Each node of the index is stored in a database as a separate object or record and may include a node identifier of the unique, an identifier of a parent and/or a sibling node and an entry for each child of the node, which may be data items or other nodes. Each record entry for a child includes an associated bounding area encompassing descendant data items. Another database table or module may store information about the index, such as the dimensionality of the data, the index fanout and an identifier of a root of the index.

Abstract: Methods are provided for buffering nodes of a hierarchical index (e.g., R-tree, bang file, hB-tree) during operations on multi-dimensional data represented by the index. The methods are particularly suited for query operations, and a different method may be more suitable for one pattern of queries than another. Where queries are distributed in a relatively uniform manner across the domain or dataspace of an index, a node-area buffering method is provided. In this method nodes are cached or buffered in order of their respective areas (e.g., their minimum bounding areas), and a node having a smaller area will be replaced in cache before a node having a larger area. When, however, queries are not uniformly distributed, then a least frequently accessed buffering technique may be applied. According to this method statistics are maintained concerning the frequency with which individual index nodes are accessed. Those accessed less frequently are replaced in cache before those accessed more frequently.

Abstract: A system and method for indexing and storing multi-dimensional or multi-attribute data. Data items are recursively sorted in a selected dimension (e.g., the dimension having the greatest variance) and divided until each subdivision fits into a leaf node having a specified fanout. Intermediate nodes and a root node are constructed to complete the index. Each node of the index is stored in a database as a separate object or record and may include a node identifier of the unique, an identifier of a parent and/or a sibling node and an entry for each child of the node, which may be data items or other nodes. Each record entry for a child includes an associated bounding area encompassing descendant data items. Another database table or module may store information about the index, such as the dimensionality of the data, the index fanout and an identifier of a root of the index.

Abstract: A method and apparatus for efficiently storing and retrieving data in a database using index-only tables is disclosed. Storing a row of data in a database using index-only tables involves storing in a leaf node an index entry that includes a key value along with all other values in the row of data. If the row of data exceeds a predetermined size, then a portion of the row of data is stored in a user specified overflow area. Retrieving a row of data from an index-only table for a user-supplied key involves identifying a leaf node for the key, and reading a row of data from the index entry and any remaining portion from the overflow area when the row exceeds the predetermined size.

Abstract: A method and apparatus for building, maintaining, and using a multi-level index is provided. The multi-level index is accessed using a key. The key is divided into multiple portions referred to as sub-keys. The first level of the multi-level index is built on a first-level sub-key. Each index entry at the first-level is for a particular first-level sub-key value, and either includes sub-entries associated with second-level sub-key values or a reference to a second-level data retrieval structure. All second-level data retrieval structures are built on the portion of the key that has been designated as the second-level sub-key. As the vocabulary of the first-level sub-key becomes exhausted, fewer maintenance operations will have to be performed to maintain the first-level data retrieval structure. This decreases the overhead and increases the concurrency in a database system that uses the multiple-level index.