Abstract:
A system and method for transacting data using meta-models to express data relationships is provided. In some embodiments, the method comprises requesting, from a computing system, a meta-model expressing a data relationship. The data relationship relates to a topology of a deployed computing system, and the requesting specifies the meta-model from among a plurality of data models stored within the computing system. The requested meta-model is received from the computing system, and at least a portion of the meta-model is provided to an application. A data transaction based on the meta-model is received from the application and issued. In some such embodiments, a navigational interface is provided in order to navigate the meta-model and specify the portion to provide.
Abstract:
A system and method for mapping file block numbers (FBNs) to logical block addresses (LBAs) is provided. The system and method performs the mapping of FBNs to LBAs in a file system layer of a storage operating system, thereby enabling the use of clients in a storage environment that have not been modified to incorporate mapping tables. As a result, a client may send data access requests to the storage system utilizing FBNs and have the storage system perform the appropriate mapping to LBAs.
Abstract:
A storage server is coupled to a storage device that stores data blocks, and generates a fingerprint for each data block stored on the storage device. The storage server creates a master datastore and a plurality of datastore segments. The master datastore comprises an entry for each data block that is written to the storage device and a datastore segment comprises an entry for a new data block or a modified data block that is subsequently written to the storage device. The storage server merges the entries in the datastore segments with the entries in the master datastore in memory to free duplicate data blocks in the storage device. The storage server overwrites the master datastore with the entries in the plurality of datastore segments and the entries in the master datastore to create an updated master datastore in response to detecting that the number of datastore segments meets a threshold.
Abstract:
Example embodiments provide various techniques for distributing connections within a connectional parallelism architecture. In one embodiment, a method is provided where resource utilizations of connection groups are measured. Here, each connection group is assigned to one of multiple processors. A probability distribution is accessed that maps probabilities assigned to relative resource utilizations. A relative resource utilization of one of the connection groups is determined based on a resource utilization of the one connection group relative to other resource utilizations of other connection groups. A probability from the probability distribution is identified based on the determined relative resource utilization, and based on the identified probability, a connection is assigned to this connection group for execution by one of the processors assigned to this connection group.
Abstract:
A system and method for efficiently replicating data stored in a byte-addressable, persistent memory of a host computer. A user-level library of the host computer may configure the persistent memory as a software transactional memory (STM) system defined by operations, such as a STM commit operation, that ensure safe and consistent storage of the data within a region of the persistent memory. The library may then cooperate with an application executing on the host computer to control access to the data, e.g., to change the data, as a transaction using the STM commit operation. Within a context of the transaction, the library may precisely determine which bytes of the data have changed within the region, as well as how and when the data bytes have changed. Armed with precise knowledge of the context of the transaction, the library may efficiently replicate the changed data at the byte-addressable granularity.
Abstract:
The embodiments described herein provide a system and method for efficiently storing small, random modifications or changes to data on one or more storage devices, such as disks, of storage servers coupled to a host computer in a network environment. Illustratively, the data is stored in a region of a byte-addressable, persistent memory of the host computer and is replicated (i.e., copied) as changed data of the region on the disks at the granularity at which it was modified, e.g., at the byte-addressable granularity. To that end, each storage server employs a data structure (e.g., a Fibonacci array) that is configured to efficiently accumulate the small, random data changes into one or more large blocks of changed data for storage on the disks in a manner that realizes the streaming bandwidth of the disk.
Abstract:
Systems and methods which allow for one or more input/output (I/O) ports residing on a device in a storage network environment to be reconfigured in order to communicate using different protocols are provided. Embodiments may provide for dynamic reconfiguration of an I/O port while the device including the port is deployed in the storage network. In some instances, such reconfiguration may be managed locally and/or by a remote management processing resource in the storage network. In some embodiments, reconfiguration of an I/O port to communicate in a different protocol may be implemented, either manually or automatically, based on observed traffic data.
Abstract:
A modular block allocator includes a front end module and a back end module communicating with each another via an application programming interface (API). The front end module receives cleaner messages requesting dirty buffers associated with the cleaner messages be cleaned. The back end module provides low and high level data structures which are formed by examining bitmaps associated with data storage devices. A stripe set data structure mapping to the low level data structures are formed. The front end module cleans the dirty buffers by allocating data blocks in the high level data structures to the dirty buffers. The low level data structures are used to map the allocated data blocks to the stripe set and when the stripe set is full it is sent to the data storage devices.
Abstract:
A system and method for transparently compressing file system data using compression group descriptors is provided. When data contained within a compression group be compressed beyond a predefined threshold value, a compression group descriptor is included in the compression group that signifies that the data for the group of level 0 blocks is compressed into a lesser number of physical data blocks. When performing a read operation, the file system first determines the appropriate compression group that contains the desired data and determines whether the compression group has been compressed. If so, the file system decompresses the data in the compression group before returning the decompressed data. If the magic value is not the first pointer position, then the data within the compression group was previously stored in an uncompressed format, and the data may be returned without performing a decompression operation.
Abstract:
Exemplary embodiments provide various techniques for identifying a virtual application for backup in a cloud computing system. A cloud service layer of the cloud computing system is queried for a listing of virtual applications. In response to the querying, an attribute associated with the virtual application is received from the cloud service layer. The attribute associated with the virtual application is then transformed into an attribute associated with a hypervisor-managed virtual machine, and this transformation of the attribute exposes the hypervisor-managed virtual machine associated with the virtual application such that the hypervisor-managed virtual machine is identifiable for backup. As a result, the virtual application can be backed up based on the attribute of the hypervisor-managed virtual machine.