Abstract: A system, method, and program storage device implementing the method, for integrating data in a database management system, wherein the method comprises grouping data sources and replicas of the data sources that provide analogous data into a common logical domain; writing application queries against the common logical domain; selecting a correct set of replicas of the data sources and a query-execution strategy for combining a content of the correct set of replicas of the data sources in order to answer the application queries according to query-cost-based optimization; selecting a correct set of data sources according to run-time constraints; shielding the application queries from changes to the data sources by dynamically binding the application queries against the correct sets of data sources and replicas of the data sources; and processing the application queries by generating an optimum query result based on the steps of grouping and shielding.

Abstract: A grid-based approach for enterprise-scale data mining that leverages database technology for I/O parallelism and on-demand compute servers for compute parallelism in the statistical computations is described. By enterprise-scale, we mean the highly-automated use of data mining in vertical business applications, where the data is stored on one or more relational database systems, and where a distributed architecture comprising of high-performance compute servers or a network of low-cost, commodity processors, is used to improve application performance, provide better quality data mining models, and for overall workload management. The approach relies on an algorithmic decomposition of the data mining kernel on the data and compute grids, which provides a simple way to exploit the parallelism on the respective grids, while minimizing the data transfer between them.

Abstract: Embodiments herein present a method, computer program product, etc. for masking data failures. The method comprises storing a single master copy of data and a replica copy of the data. Next, the method performs writes to the master using a middleware component. Reads are then performed from either the master or the replica using the middleware component. When the master is unavailable, the writes are stored in a table located in the middleware component as stored write requests, wherein the stored write requests comprise UDI's to be made to the master. The reads are also performed from the table and the replica when the master is unavailable. When the master becomes available, the stored write requests are propagated to the master. Thus, by storing the write requests in the table, the middleware allows the writes to run during times when the master is unavailable.

Abstract: Disclosed are a method and a system for executing a query that requires an expensive process, such as a join, between two or more datasets. If each dataset has multiple partitions that are located at multiple sources, then each of the multiple partitions for each dataset must be unioned prior to completing execution of the query. The method and system develop both a query execution plan and at least one alternative query execution plan to indicate when the process should be pushed down below the unions and when the process should be pulled up above the unions based on collocation of partitions. The query execution plan and the alternative query execution plan(s) are embedded in a composite query execution plan which is evaluated and re-evaluated at run time to determine which of the query execution plan and the alternative query execution plan is currently the most efficient plan and the query is executed, accordingly.

Abstract: Disclosed are embodiments of a system for optimizing query processing in a federated information system. The system may be used to identify alternative query plans in a simulated environment and to calculate cost estimates associated with the alternative query plans, based not only on database statistics and query statements, but also based on workload and processing latencies associated with specific data source and with the federated information system as a whole. In addition the calculated cost estimates may also factor in data source availability and reliability. The system may use the alternative query plans and the associated cost estimates to influence query processing in a federated information system by feeding to the federated information system query plans that allow for cost-efficient query plan-level load distribution, cost-efficient query fragment plan-level load distribution, and load distribution based upon quality of service cost constraints.

Abstract: A system, method, and program storage device implementing the method, for integrating data in a database management system, wherein the method comprises grouping data sources and replicas of the data sources that provide analogous data into a common logical domain; writing application queries against the common logical domain; selecting a correct set of replicas of the data sources and a query-execution strategy for combining a content of the correct set of replicas of the data sources in order to answer the application queries according to query-cost-based optimization; selecting a correct set of data sources according to run-time constraints; shielding the application queries from changes to the data sources by dynamically binding the application queries against the correct sets of data sources and replicas of the data sources; and processing the application queries by generating an optimum query result based on the steps of grouping and shielding.

Abstract: A system and a computer program product are disclosed for maintaining consistency of object content (252) and metadata (204) related to the object (252) in a loose transaction model, preferably using SQL Mediated Object Manipulation (SMOM), for object and meta-data updates. The related meta-data (204) and a reference to the object (252) are stored in a table of a database. The object is stored externally to the database in an object store. The reference is used to obtain a handle for directly accessing or manipulating the external object. A version number embedded in the handle is then obtained. The embedded version number is then compared with a version number of a latest committed version of the externally stored object to determine if the handle refers to a current version of the externally stored object. Next, the last modification timestamp of the file is compared with the last modification timestamp of the latest committed version, in order to detect uncommitted updates.

Abstract: A system and method of lightweight asynchronous data replication that avoids the need for any persistent store at the replication source or communication channel, and is independent of the underlying data formats, wherein the method of data replication comprises replicating deltas from a source, embedding replication tracking information in the replicated deltas, wherein the tracking information comprises a timestamp and a sequence number, and applying deltas at a target. The tracking information is used to ensure that each delta is applied exactly once. In the event of a crash in the system, the target analyzes the tracking information to determine which deltas have been applied, and requests retransmission of replicated data from the source starting from the earliest unapplied delta. The source and target are treated as only delta producers and consumers, and as such the invention is applicable to replication between arbitrary data source formats.

Abstract: A system and method to automatically and dynamically optimize available resources to meet application data availability and business objectives. In one embodiment, a backup and data recovery system continually and dynamically adjust to the backup and recovery or restore process depending on the customer's environment, workload, and business objectives. Acceptable tolerance of downtime due to recovery and backup impacts the customer's business or system operation. From this high-level business requirement, the present system determines the backup and recovery plan details. The present system accepts application data availability policies based on business objectives, and devises, executes and refines a resource optimal backup and recovery strategy required to deliver the desired quality of service in the environments that have dynamically changing application workloads, business objectives, and hardware/software infrastructure technologies.