Abstract:
Methods and apparatuses for efficiently migrating deduplicated data are provided. In one example, a data management system includes a data storage volume, a memory including machine executable instructions, and a computer processor. The data storage volume includes data objects and free storage space. The computer processor executes the instructions to perform deduplication of the data objects and determine migration efficiency metrics for groups of the data objects. Determining the migration efficiency metrics includes determining, for each group, a relationship between the free storage space that will result if the group is migrated from the volume and the resources required to migrate the group from the volume.
Abstract:
A system and method for providing customer guidance in deploying a modular computing system is provided. In some embodiments, the method comprises receiving a shipping container identifier. A computing system is used to determine, based on the shipping container identifier, that a component of the modular computing system has been received by a customer. It is determined whether the modular computing system can be deployed based on the component having been received by the customer. An indicator is provided of whether the modular computing system can be deployed. An instruction is provided for deploying the modular computing system, and a diagnostic procedure is performed on a deployed component of the modular computing system. In one such embodiment, the diagnostic procedure determines whether the instruction was correctly performed.
Abstract:
In addition to caching I/O operations at a host, at least some data management can migrate to the host. With host side caching, data sharing or deduplication can be implemented with the cached writes before those writes are supplied to front end storage elements. When a host cache flush to distributed storage trigger is detected, the host deduplicates the cached writes. The host aggregates data based on the deduplication into a “change set file” (i.e., a file that includes the aggregation of unique data from the cached writes). The host supplies the change set file to the distributed storage system. The host then sends commands to the distributed storage system. Each of the commands identifies a part of the change set file to be used for a target of the cached writes.
Abstract:
In addition to caching I/O operations at a host, at least some data management can migrate to the host. With host side caching, data sharing or deduplication can be implemented with the cached writes before those writes are supplied to front end storage elements. When a host cache flush to distributed storage trigger is detected, the host deduplicates the cached writes. The host aggregates data based on the deduplication into a “change set file” (i.e., a file that includes the aggregation of unique data from the cached writes). The host supplies the change set file to the distributed storage system. The host then sends commands to the distributed storage system. Each of the commands identifies a part of the change set file to be used for a target of the cached writes.
Abstract:
Technology is disclosed for managing data in a distributed file system (“the technology”). The technology can gather metadata information associated with the data stored within the distributed file system, create a secondary namespace within a local file system of a local host using the gathered metadata information and store the gathered metadata information as files within the secondary namespace. Further, when a request to create a PPI of the distributed file system is received, the technology can create a PPI of the secondary namespace using a PPI creation feature of the local file system.
Abstract:
Technology is disclosed for managing data in a distributed processing system (“the technology”). In various embodiments, the technology pushes “cold” data from a primary storage of the distributed processing system to a backup storage thereby maximizing the usage of the space on the primary storage to store “hot” data on which most data processing activities are performed in the distributed processing system. The cold data is retrieved from the backup storage into the primary storage on demand, for example, upon receiving an access request from a client. While the primary storage stores the data in a format specific to the distributed processing system, the backup storage stores the data in a different format, for example, format corresponding to the type of backup storage.
Abstract:
In addition to caching I/O operations at a host, at least some data management can migrate to the host. With host side caching, data sharing or deduplication can be implemented with the cached writes before those writes are supplied to front end storage elements. When a host cache flush to distributed storage trigger is detected, the host deduplicates the cached writes. The host aggregates data based on the deduplication into a “change set file” (i.e., a file that includes the aggregation of unique data from the cached writes). The host supplies the change set file to the distributed storage system. The host then sends commands to the distributed storage system. Each of the commands identifies a part of the change set file to be used for a target of the cached writes.
Abstract:
In addition to caching I/O operations at a host, at least some data management can migrate to the host. With host side caching, data sharing or deduplication can be implemented with the cached writes before those writes are supplied to front end storage elements. When a host cache flush to distributed storage trigger is detected, the host deduplicates the cached writes. The host aggregates data based on the deduplication into a “change set file” (i.e., a file that includes the aggregation of unique data from the cached writes). The host supplies the change set file to the distributed storage system. The host then sends commands to the distributed storage system. Each of the commands identifies a part of the change set file to be used for a target of the cached writes.
Abstract:
Technology is disclosed for managing data in a distributed file system (“the technology”). The technology can gather metadata information associated with the data stored within the distributed file system, create a secondary namespace within a local file system of a local host using the gathered metadata information and store the gathered metadata information as files within the secondary namespace. Further, when a request to create a PPI of the distributed file system is received, the technology can create a PPI of the secondary namespace using a PPI creation feature of the local file system.
Abstract:
In addition to caching I/O operations at a host, at least some data management can migrate to the host. With host side caching, data sharing or deduplication can be implemented with the cached writes before those writes are supplied to front end storage elements. When a host cache flush to distributed storage trigger is detected, the host deduplicates the cached writes. The host aggregates data based on the deduplication into a “change set file” (i.e., a file that includes the aggregation of unique data from the cached writes). The host supplies the change set file to the distributed storage system. The host then sends commands to the distributed storage system. Each of the commands identifies a part of the change set file to be used for a target of the cached writes.