Abstract: An embodiment method for massively parallel processing includes initiating a management instance on an initial machine, the management instance generating an initial partition corresponding to the initial machine, determining a total number of partitions desired for processing a database, the total number of partitions including the initial partition, determining a number of additional machines available to process the database, grouping the initial machine and the additional machines together in a pod, and launching the management instance on the additional machines in the pod to generate the total number of partitions desired for the database. Additional embodiment methods and an embodiment system operable to perform such methods are also disclosed.

Abstract: An embodiment method for massively parallel processing includes assigning a primary key to a first table in a database and a foreign key to a second table in the database, the foreign key of the second table identical to the primary key of the first table, determining a number of partition groups desired for the database, partitioning the first table into first partitions based on the primary key assigned and the number of partition groups desired, partitioning the second table into second partitions based on the foreign key assigned and the number of partition groups desired, and distributing the first partitions and the second partitions to the partition groups as partitioned. An embodiment system for implementing the embodiment methods is also disclosed.

Abstract: A massively parallel processing (MPP) database can be re-partitioned/re-balanced while remaining on-line through a staged migration procedure. Staged migration may include a first stage and a second stage. During the first stage, entries in an existing partition are reallocated to the new partition, and the catalog is updated to associate the re-allocated entries with both the existing partition and the new partition such that queries for the re-allocated entries are directed toward the existing partition and the new partition. During the second stage, the re-allocated entries are migrated from the existing partition to the new partition, and after the migration is complete, the catalog is re-updated to associate the migrated entries with the new partition such that new queries are directed toward the new partition.

Abstract: A massively parallel processing (MPP) database can be re-partitioned/re-balanced while remaining on-line through a staged migration procedure. Staged migration may include a first stage and a second stage. During the first stage, entries in an existing partition are reallocated to the new partition, and the catalog is updated to associate the re-allocated entries with both the existing partition and the new partition such that queries for the re-allocated entries are directed toward the existing partition and the new partition. During the second stage, the re-allocated entries are migrated from the existing partition to the new partition, and after the migration is complete, the catalog is re-updated to associate the migrated entries with the new partition such that new queries are directed toward the new partition.

Abstract: An embodiment method for massively parallel processing includes assigning a primary key to a first table in a database and a foreign key to a second table in the database, the foreign key of the second table identical to the primary key of the first table, determining a number of partition groups desired for the database, partitioning the first table into first partitions based on the primary key assigned and the number of partition groups desired, partitioning the second table into second partitions based on the foreign key assigned and the number of partition groups desired, and distributing the first partitions and the second partitions to the partition groups as partitioned. An embodiment system for implementing the embodiment methods is also disclosed.

Abstract: A data management method is provided for storing a real-time history of a file system, or a component thereof, such as a directory or a file. The real-time history is stored as an object-oriented logical representation comprising at least a set of version metadata objects, and a set of one or more links that associate given objects of the set of version metadata objects. As one or more events occur in the real-time history, the logical representation is restructured dynamically. The logical representation is useful to provide any point-in-time reconstruction of the file system component on an as-needed basis.

Abstract: A data management system or “DMS” provides an automated, continuous, real-time, substantially no downtime data protection service to one or more data sources associated with a set of application host servers. To facilitate the data protection service, a host driver embedded in an application server captures real-time data transactions, preferably in the form of an event journal that is provided to other DMS components. The driver functions to translate traditional file/database/block I/O and the like into a continuous, application-aware, output data stream. The host driver includes an event processor that provides the data protection service, preferably by implementing a finite state machine (FSM). In particular, the data protection is provided to a given data source in the host server by taking advantage of the continuous, real-time data that the host driver is capturing and providing to other DMS components.

Abstract: A data management system that protects data into a continuous object store includes a management interface having a time control. The time control allows an administrator to specify a “past” time, such as a single point or range. When the time control is set to a single point, a hierarchical display of data appears on a display exactly as the data existed in the system at that moment in the past. Preferably, the visualization includes both the structure of the hierarchy (e.g., the identity of the directories, their files, databases, and the like) and also the contents of the data objects themselves (i.e., what was in the files and databases). The time control enables the management interface to operate within a history mode in which the display provides a visual representation of a “virtual” point in time in the past during which the data management system has been operative to provide the data protection service.

Abstract: A “forward” delta data management technique uses a “sparse” index associated with a delta file to achieve both delta management efficiency and to eliminate read latency while accessing history data. The invention may be implemented advantageously in a data management system that provides real-time data services to data sources associated with a set of application host servers. To facilitate a given data service, a host driver embedded in an application server connects an application and its data to a cluster. The host driver captures real-time data transactions, preferably in the form of an event journal that is provided to the data management system. In particular, the driver functions to translate traditional file/database/block I/O into a continuous, application-aware, output data stream.

Abstract: A data management system or “DMS” provides an automated, continuous, real-time, substantially no downtime data protection service to one or more data sources associated with a set of application host servers. To facilitate the data protection service, a host driver embedded in an application server captures real-time data transactions, preferably in the form of an event journal that is provided to other DMS components. The driver functions to translate traditional file/database/block I/O and the like into a continuous, application-aware, output data stream. The host driver includes an event processor that provides the data protection service, preferably by implementing a finite state machine (FSM). In particular, the data protection is provided to a given data source in the host server by taking advantage of the continuous, real-time data that the host driver is capturing and providing to other DMS components.

Abstract: A data management system or “DMS” provides a wide range of data services to data sources associated with a set of application host servers. The data management system typically comprises one or more regions, with each region having one or more clusters. A given cluster has one or more nodes that share storage. To facilitate the data service, a host driver embedded in an application server connects an application and its data to a cluster. The host driver provides a method and apparatus for capturing real-time data transactions in the form of an event journal that is provided to the data management system. The driver functions to translate traditional file/database/block I/O into a continuous, application-aware, output data stream. Using the streams generated in this manner, the DMS offers a wide range of data services that include, by way of example only: data protection (and recovery), disaster recovery (data distribution and data replication), data copy, and data query and access.

Abstract: A data management system or “DMS” provides a wide range of data services to data sources associated with a set of application host servers. The data management system typically comprises one or more regions, with each region having one or more clusters. A given cluster has one or more nodes that share storage. To facilitate the data service, a host driver embedded in an application server connects an application and its data to a cluster. The host driver provides a method and apparatus for capturing real-time data modifications and application state notifications and, in response, generating data transactions in the form of an event journal that is provided to the data management system. The driver functions to translate traditional file/database/block I/O into a continuous, application-aware, output data stream.

Abstract: A method and system for initializing a new node in a network. This initialization includes adding a new node to a network that has a plurality of nodes, and then sending a query automatically to the plurality of nodes to determine what content needs to be downloaded. Then, receiving a reply from a subset of the plurality of nodes that has the content needed for the new node. Lastly, downloading the desired portions of the content from the subset of the plurality of nodes that have the needed content.