Abstract:
To prioritize repopulation of in-memory compression units (IMCU), a database server compresses, into an IMCU, a plurality of data units from a database table. In response to changes to any of the plurality of data units within the database table, the database server performs the steps of: (a) invalidating corresponding data units in the IMCU; (b) incrementing an invalidity counter of the IMCU that reflects how many data units within the IMCU have been invalidated; (c) receiving a data request that targets one or more of the plurality of data units of the database table; (d) in response to receiving the data request, incrementing an access counter of the IMCU; and (e) determining a priority for repopulating the IMCU based, at least in part, on the invalidity counter and the access counter.
Abstract:
A method and system for replicating database data is provided. One or more standby database replicas can be used for servicing read-only queries, and the amount of storage required is scalable in the size of the primary database storage. One technique is described for combining physical database replication to multiple physical databases residing within a common storage system that performs de-duplication. Having multiple physical databases allows for many read-only queries to be processed, and the de-duplicating storage system provides scalability in the size of the primary database storage. Another technique uses one or more diskless standby database systems that share a read-only copy of physical standby database files. Notification messages provide consistency between each diskless system's in-memory cache and the state of the shared database files. Use of a transaction sequence number ensures that each database system only accesses versions of data blocks that are consistent with a transaction checkpoint.
Abstract:
Techniques are provided for using an intermediate cache between the shared cache of an application and the non-volatile storage of a storage system. The application may be any type of application that uses a storage system to persistently store data. The intermediate cache may be local to the machine upon which the application is executing, or may be implemented within the storage system. In one embodiment where the application is a database server, the database system includes both a DB server-side intermediate cache, and a storage-side intermediate cache. The caching policies used to populate the intermediate cache are intelligent, taking into account factors that may include which object an item belongs to, the item type of the item, a characteristic of the item, or the type of operation in which the item is involved.
Abstract:
No-loss rapid recovery performs resynchronization efficiently while concurrently allowing availability to mirrored data on the storage device. No-loss rapid recovery has two stages and involves storage devices that have both a non-volatile cache and primary storage and that operate as mirror buddies. The first stage is referred to herein as the buddy-retention stage. During the buddy-retention stage, writes to mirrored data are not performed on the offline mirror buddy but are performed on the online mirror buddy. The mirrored data changed in the online mirrored buddy is retained in the non-volatile cache of the retention buddy. The next stage is referred to herein as the rapid resynchronization stage. In this stage, the changed mirrored data retained by the retention buddy for no-loss rapid recovery is used to resynchronize the offline buddy. The storage device is resynchronized using the changed mirrored data retained in the cache of the mirror buddy.
Abstract:
Techniques for maintaining a cascading index are provided. In one approach, one or more branch node compression techniques are applied to the main index of a cascading index. In an approach, a Bloom filter is generated and associated with, e.g., a branch node in the main index. The Bloom filter is used to determine whether, without accessing any leaf blocks, a particular key value exists, e.g., in leaf blocks associated with the branch node. In an approach, a new redo record is generated in response to a merge operation between two levels of the cascading index. The new redo record comprises (a) one or more addresses of blocks that are affected by the merge operation, (b) data is that being “pushed down” to a lower level of the cascading index, and (c) one or more addresses of blocks that are written to storage as a result of the merge operation.