Abstract: Several methods and a system of a workload management of a concurrently accessed database server are disclosed. In one embodiment, a method includes applying a weight to a service class. The method also includes generating a priority of the service class. In addition, the method includes selecting a group based on the weight of the service class. The method further includes determining a priority level based on the priority of the service class. The method also includes generating a characteristic of a shadow process through the weight and the priority of the service class. In addition, the method includes executing a query.

Abstract: A system and method of massively parallel data processing are disclosed. In an embodiment, a method includes generating an interpretation of a customizable database request which includes an extensible computer process and providing an input guidance to available processors of an available computing environment. The method further includes automatically distributing an execution of the interpretation across the available computing environment operating concurrently and in parallel, wherein a component of the execution may be limited to at least a part of an input data. The method also includes automatically assembling a response using a distributed output of the execution.

Abstract: A system and method of massively parallel data processing are disclosed. In an embodiment, a method includes generating an interpretation of a customizable database request which includes an extensible computer process and providing an input guidance to available processors of an available computing environment. The method further includes automatically distributing an execution of the interpretation across the available computing environment operating concurrently and in parallel, wherein a component of the execution may be limited to at least a part of an input data. The method also includes automatically assembling a response using a distributed output of the execution.

Abstract: In one embodiment, a method includes concurrently executing a set of multiple queries, through a processor, to improve a resource usage within a data warehouse system. The method also includes permitting a group of users of the data warehouse system to simultaneously run a set of queries. In addition, the method includes applying a high-concurrency query operator to continuously optimize a large number of concurrent queries for a set of highly concurrent dynamic workloads.

Abstract: A system and method of massively parallel data processing are disclosed. In an embodiment, a method includes generating an interpretation of a customizable database request which includes an extensible computer process and providing an input guidance to available processors of an available computing environment. The method further includes automatically distributing an execution of the interpretation across the available computing environment operating concurrently and in parallel, wherein a component of the execution may be limited to at least a part of an input data. The method also includes automatically assembling a response using a distributed output of the execution.

Abstract: A system and method for using failure casting to manage failures in computer system. In accordance with an embodiment, the system uses a failure casting hierarchy to cast failures of one type into failures of another type. In doing this, the system allows incidents, problems, or failures to be cast into a (typically smaller) set of failures, which the system knows how to handle. In accordance with a particular embodiment, failures can be cast into a category that is considered reboot-curable. If a failure is reboot-curable then rebooting the system will likely cure the problem. Examples include hardware failures, and reboot-specific methods that can be applied to disk failures and to failures within clusters of databases. The system can even be used to handle failures that were hitherto unforeseen—failures can be cast into known failures based on the failure symptoms, rather than any underlying cause.

Abstract: The present invention addresses the problem of partitioning database relations across a plurality of hosts in a shared-nothing cluster while minimizing communication costs. A new partitioning approach for database relations—join-partitioning—is introduced that focuses on relations and their dependencies to a priori partition the plurality of relations to the plurality of hosts such that each host can locally compute a large class of queries over its partitioned data in isolation at query time, independent of other hosts in the cluster. Such an approach thus overcomes the primary bottleneck, i.e., the network, in deploying database systems over shared-nothing clusters by allowing them to seamlessly scale linearly to tens of thousands of hosts and manage tens or hundreds of terabytes of data. This description is not intended to be a complete description of, or limit the scope of, the invention.

Abstract: An event tap associated with a server, such as a Web server, at a machine can transform a server event into a tuple, select a database node for the tuple, and place the tuple in a queue for that database node, and then flush the queue periodically directly into database notes. The use of an event tap can thus reduce the computational burden on the database while keeping the server event data in the database relatively fresh.