Abstract: A system for transforming time series data into data that is accessible by a data warehouse identifies a data table comprising the time series data. The system creates a virtual view of the data table where the time series data is represented as at least one standard relational table in the virtual view, where the virtual view is presented as a virtual table. The system partitions the virtual table into a plurality of virtual partitions according to a time interval. The virtual table is partitioned across a data time range, where the data time range comprises at least one time interval, and where each of the plurality of virtual partitions has a respective partition time range that spans the time interval. The virtual partitions are created to optimize loading of the data into the data warehouse by incrementally refreshing the data according to the respective partition time range.

Abstract: A system for transforming time series data into data that is accessible by a data warehouse identifies a data table comprising the time series data. The system creates a virtual view of the data table where the time series data is represented as at least one standard relational table in the virtual view, where the virtual view is presented as a virtual table. The system partitions the virtual table into a plurality of virtual partitions according to a time interval. The virtual table is partitioned across a data time range, where the data time range comprises at least one time interval, and where each of the plurality of virtual partitions has a respective partition time range that spans the time interval. The virtual partitions are created to optimize loading of the data into the data warehouse by incrementally refreshing the data according to the respective partition time range.

Abstract: A system for transforming time series data into data that is accessible by a data warehouse identifies a data table comprising the time series data. The system creates a virtual view of the data table where the time series data is represented as at least one standard relational table in the virtual view, where the virtual view is presented as a virtual table. The system partitions the virtual table into a plurality of virtual partitions according to a time interval. The virtual table is partitioned across a data time range, where the data time range comprises at least one time interval, and where each of the plurality of virtual partitions has a respective partition time range that spans the time interval. The virtual partitions are created to optimize loading of the data into the data warehouse by incrementally refreshing the data according to the respective partition time range.

Abstract: A system for transforming time series data into data that is accessible by a data warehouse identifies a data table comprising the time series data. The system creates a virtual view of the data table where the time series data is represented as at least one standard relational table in the virtual view, where the virtual view is presented as a virtual table. The system partitions the virtual table into a plurality of virtual partitions according to a time interval. The virtual table is partitioned across a data time range, where the data time range comprises at least one time interval, and where each of the plurality of virtual partitions has a respective partition time range that spans the time interval. The virtual partitions are created to optimize loading of the data into the data warehouse by incrementally refreshing the data according to the respective partition time range.

Abstract: Embodiments of the invention generally relate to data processing systems and more particularly to high availability data processing systems. A primary server may share a storage device with one or more clone systems. Each clone generally replicates the state of the primary server, but relies on the same disk-based storage as the primary server. Thus, the clone systems may provide a shadow of the primary server, ready to take over should the primary server fail. The clone systems may access a log file that includes entries reflecting the actions performed by the primary system. The primary server may flush entries from a log buffer maintained on the primary server to a log file stored on the shared disk-based storage. The primary server may also send a log sequence number to the clone systems, and the clone systems periodically transmit a log sequence number back to the primary server indicating how far through the log file a clone system has progressed.

Abstract: Embodiments of the invention generally relate to data processing systems and more particularly to high availability data processing systems. A primary server may share a storage device with one or more clone systems. Each clone generally replicates the state of the primary server, but relies on the same disk-based storage as the primary server. Thus, the clone systems may provide a shadow of the primary server, ready to take over should the primary server fail. The clone systems may access a log file that includes entries reflecting the actions performed by the primary system. The primary server may flush entries from a log buffer maintained on the primary server to a log file stored on the shared disk-based storage. The primary server may also send a log sequence number to the clone systems, and the clone systems periodically transmit a log sequence number back to the primary server indicating how far through the log file a clone system has progressed.

Abstract: In a database system having a primary server side (10) and a secondary server side (30), a high availability data replicator (26, 46) transfers log entries from the primary side (10) to the secondary side (30) and replays the transferred log entries to synchronize the secondary side (30) with the primary side (10). R-tree index transfer threads (54, 56) copy user-defined routines, the user defined index, and index databases deployed on the primary server side (10) to the secondary server side (30) and deploy the copied user-defined routines, reconstruct the user-defined index, and copy data pages on the secondary side (30) to make the user-defined index consistent and usable on the secondary side (30).

Abstract: In a database system having a primary server side (10) and a secondary server side (30), a high availability data replicator (26, 46) transfers log entries from the primary side (10) to the secondary side (30) and replays the transferred log entries to synchronize the secondary side (30) with the primary side (10). R-tree index transfer threads (54, 56) copy user-defined routines, the user defined index, and index databases deployed on the primary server side (10) to the secondary server side (30) and deploy the copied user-defined routines, reconstruct the user-defined index, and copy data pages on the secondary side (30) to make the user-defined index consistent and usable on the secondary side (30).

Abstract: In a database system having a primary server side (10) and a secondary server side (30), a high availability data replicator (26, 46) transfers log entries from the primary side (10) to the secondary side (30) and replays the transferred log entries to synchronize the secondary side (30) with the primary side (10). R-tree index transfer threads (54, 56) copy user-defined routines, the user defined index, and index databases deployed on the primary server side (10) to the secondary server side (30) and deploy the copied user-defined routines, reconstruct the user-defined index, and copy data pages on the secondary side (30) to make the user-defined index consistent and usable on the secondary side (30).

Abstract: In a database system having a primary server side (10) and a secondary server side (30), a high availability data replicator (26, 46) transfers log entries from the primary side (10) to the secondary side (30) and replays the transferred log entries to synchronize the secondary side (30) with the primary side (10). R-tree index transfer threads (54, 56) copy user-defined routines, the user defined index, and index databases deployed on the primary server side (10) to the secondary server side (30) and deploy the copied user-defined routines, reconstruct the user-defined index, and copy data pages on the secondary side (30) to make the user-defined index consistent and usable on the secondary side (30).