Abstract: A method and apparatus for selective removal of user data changes is provided. In one embodiment, the methodology is implemented by a logical recovery mechanism. Upon receiving a request to selectively remove user data changes stored in a database, the mechanism creates an empty set of transactions to be populated for selective removal, identifies one or more transactions and places them in the causal set of transactions. The mechanism further identifies other transactions that logically depend on any transaction already in the causal set of transactions. Finally, either while the causal set of transactions is being identified or after the identification is completed, the mechanism also determines user data changes made by the causal set of transactions. One or more compensating transactions may be generated by the logical recovery mechanism, which when executed, reverse the user data changes.

Abstract: Techniques are described herein for automatically selecting the compression techniques to be used on tabular data. A compression analyzer gives users high-level control over the selection process without requiring the user to know details about the specific compression techniques that are available to the compression analyzer. Users are able to specify, for a given set of data, a “balance point” along the spectrum between “maximum performance” and “maximum compression”. The point thus selected is used by the compression analyzer in a variety of ways. For example, in one embodiment, the compression analyzer uses the user-specified balance point to determine which of the available compression techniques qualify as “candidate techniques” for the given set of data. The compression analyzer selects the compression technique to use on a set of data by actually testing the candidate compression techniques against samples from the set of data.

Abstract: A database server stores compressed units in data blocks of a database. A table (or data from a plurality of rows thereof) is first compressed into a “compression unit” using any of a wide variety of compression techniques. The compression unit is then stored in one or more data block rows across one or more data blocks. As a result, a single data block row may comprise compressed data for a plurality of table rows, as encoded within the compression unit. Storage of compression units in data blocks maintains compatibility with existing data block-based databases, thus allowing the use of compression units in preexisting databases without modification to the underlying format of the database. The compression units may, for example, co-exist with uncompressed tables. Various techniques allow a database server to optimize access to data in the compression unit, so that the compression is virtually transparent to the user.

Abstract: A method and apparatus for selective removal of user data changes is provided. In one embodiment, the methodology is implemented by a logical recovery mechanism. Upon receiving a request to selectively remove user data changes stored in a database, the mechanism creates an empty set of transactions to be populated for selective removal, identifies one or more transactions and places them in the causal set of transactions. The mechanism further identifies other transactions that logically depend on any transaction already in the causal set of transactions. Finally, either while the causal set of transactions is being identified or after the identification is completed, the mechanism also determines user data changes made by the causal set of transactions. One or more compensating transactions may be generated by the logical recovery mechanism, which when executed, reverse the user data changes.

Abstract: A bulk delete operation with reduced latency allows for retrieval of deleted data. Each database object holds a Delete SCN indicating when a bulk delete operation was last performed. Each row in the database object holds a Row Modification SCN indicating when the row was last updated. A bulk delete is performed by writing the old value of the Delete SCN to the undo tablespace and updating the Delete SCN. No undo information is stored for the rows. A write is performed by finding a deleted row, storing undo information for the deleted row and writing over the deleted row. To read from the database object, a rollback operation is performed, if necessary. Those rows are then retrieved for which the Row Modification SCN is higher than the Delete SCN and is less than or equal to the timestamp for the requested data.

Abstract: Embodiments of the present invention that pertain to methods and systems for the calculation of resource requirements for a composite application are described. In one embodiment, information describing what component applications are associated with the composite application is received. Information describing metrics that are to be measured for the component applications is received. Information describing interrelationships between the component applications associated with the composite application is received. Information describing rules for calculating the resource requirements for the component applications is received. The rules are based on the interrelationships between the component applications and the metrics that are to be measured.

Abstract: Embodiments of the present invention are described which pertain to methods and systems of generating and evaluating potential resource allocations for an application. In one embodiment, metrics are associated with an application. Measurements for the metrics of the application are calculated. Potential resource allocations are generated based on the measurements of the metrics. A subset of the potential resource allocations are evaluated using a statistical model of the operation of the application.