A task generator runs on a data storage system in which multiple compute nodes allocate portions of local memory to a remotely accessible shared memory. The task generator is responsive to a primary task to be performed on a storage object to generate separate, per-compute node secondary tasks corresponding to the primary task. Each of the separate secondary tasks specifies at least one attribute of metadata associated with the storage object and at least one task logic function. Each of the plurality of compute nodes performs the separate secondary task generated for that compute node by scanning the local portion of the shared memory based on the attribute to identify matching pages of the metadata associated with the storage object and performs the task logic function on the identified matching pages of the metadata associated with the storage object to generate a local result. The task generator combines the local results to perform the primary task.

Various implementations described herein relate to creating a namespace in response to determining that a sum of namespace sizes of a plurality of namespaces is less than a first threshold for the point of thin-provisioning. A write command and data are received from a host. The write command and the data are received in response to determining that a sum of namespace utilization of the plurality of namespaces is less than a second threshold. The data is compressed and stored in the created namespace.

According to one embodiment, a memory system includes nonvolatile memory including a plurality of memory areas and a memory controller. A read operation includes a first operation of reading data from a memory cell array and a second operation of transmitting at least a part of the read data to the memory controller. The memory controller determines, when executing the read operation in a first memory area and a second memory area in parallel, priorities of the second operation in the first memory area and the second operation in the second memory area based on a result of comparison between (A) a first total time period of the read operation in the first memory area and (B) a second total time of the read operation in the second memory area.

Disclosed is a storage system comprising: receiving a first data segment and first metadata associated with the first data segment to be stored in the storage system; storing the first data segment and the first metadata in a persistent storage device of the storage system; compressing the first data segment using a predetermined compression algorithm to generate a first compressed data segment; and storing the first metadata and the first compressed data segment in a solid state drive (SSD) cache device of the storage system, including aligning the first metadata and the first compressed data segment to a page boundary of the SSD device to reduce a number of input and output (IO) operations required for accessing the first metadata and the first compressed data segment from the SSD cache device.

Managing input/output (‘I/O’) queues in a data storage system, including: receiving, by a host that is coupled to a plurality of storage devices via a storage network, a plurality of I/O operations to be serviced by a target storage device; determining, for each of a plurality of paths between the host and the target storage device, a data transfer maximum associated with the path; determining, for one or more of the plurality of paths, a cumulative amount of data to be transferred by I/O operations pending on the path; and selecting a target path for transmitting one or more of the plurality of I/O operations to the target storage device in dependence upon the cumulative amount of data to be transferred by I/O operations pending on the path and the data transfer maximum associated with the path.

Techniques described herein relate to systems and methods of data storage, and more particularly to providing layering of file system functionality on an object interface. In certain embodiments, file system functionality may be layered on cloud object interfaces to provide cloud-based storage while allowing for functionality expected from a legacy applications. For instance, POSIX interfaces and semantics may be layered on cloud-based storage, while providing access to data in a manner consistent with file-based access with data organization in name hierarchies. Various embodiments also may provide for memory mapping of data so that memory map changes are reflected in persistent storage while ensuring consistency between memory map changes and writes. For example, by transforming a ZFS file system disk-based storage into ZFS cloud-based storage, the ZFS file system gains the elastic nature of cloud storage.

The invention discloses an aggregation optimized processing method for time-series data, characterized by comprising the following steps: writing a time-series data record into a database, forming a time-series database file, wherein the time-series database file comprises a data file and an index file, the data file comprises multiple data blocks, the index file comprises index blocks, and each index block correspond to one data block; by scanning an index file according to a start time period and a stop time period, extracting all index blocks of the time series that need to be aggregated that meet the time period conditions, and then sorting the index blocks according to the data block offset recorded in the index block; and by scanning the data file according to a data block offset order recorded in sorted index blocks, performing specified reading and calculating on each data block, and aggregating calculation results. According to the method, the reading of a single time series data or the aggregation operation of multiple time-series data can be completed by only opening a data file once for scanning such that the overall performance is greatly improved.

A storage device is disclosed. The storage device may include storage to store data and a controller to manage reading data from and writing data to the storage. The controller may also include a receiver to receive a plurality of requests, information determination logic to determine information about the plurality of requests, storage for the information about a plurality of requests, and sharing logic to share the information with a management controller.

A method of performing partial redundant array of independent disks (RAID) stripe parity calculations is disclosed. The method includes receiving a last portion of a RAID stripe among multiple portions of the RAID stripe, all portions for a successful write of the RAID stripe being previously received except for the last portion. The method also includes calculating a parity value based on the last portion of the RAID stripe and a previous parity value without calculating the parity value using a previous portion of the RAID stripe. The method further includes writing of the RAID stripe.

A computer-implemented method according to one embodiment includes identifying a request to migrate data associated with a volume from a first storage pool to a second storage pool; identifying entries in a first table corresponding to rank extents in the first storage pool containing the data; allocating and synchronizing a plurality of second tables for the identified entries of the first table that are located in the volume; transferring the data associated with the volume from the rank extents in the first storage pool containing the data to one or more rank extents in the one or more ranks of the second storage pool; and updating the second tables to correspond to the transferred data in the one or more rank extents in the one or more ranks of the second storage pool.