SNAPSHOT METADATA ARRANGEMENT FOR EFFICIENT CLOUD INTEGRATED DATA MANAGEMENT

    公开(公告)号:US20230334013A1

    公开(公告)日:2023-10-19

    申请号:US18333627

    申请日:2023-06-13

    申请人: NetApp. Inc.

    IPC分类号: G06F16/11 G06F16/13 G06F11/14

    摘要: A storage appliance arranges snapshot data and snapshot metadata into different structures, and arranges the snapshot metadata to facilitate efficient snapshot manipulation, which may be for snapshot management or snapshot restore. The storage appliance receives snapshots according to a forever incremental configuration and arranges snapshot metadata into different types of records. The storage appliance stores these records in key-value stores maintained for each defined data collection (e.g., volume). The storage appliance arranges the snapshot metadata into records for inode information, records for directory information, and records that map source descriptors of data blocks to snapshot file descriptors. The storage appliance uses a locally generated snapshot identifier as a key prefix for the records to conform to a sort constrain of the key-value store, which allows the efficiency of the key-value store to be leveraged. The snapshot metadata arrangement facilitates efficient snapshot restore, file restore, and snapshot reclamation.

    Snapshot capacity estimation
    42.
    发明授权

    公开(公告)号:US11789900B1

    公开(公告)日:2023-10-17

    申请号:US17657339

    申请日:2022-03-30

    申请人: VAST DATA LTD.

    CPC分类号: G06F16/128 G06F16/1748

    摘要: A method for determining size information related one or more snapshots related to file systems stored in a storage system, the method may include (a) sampling one or more combinations of points in time and logical spaces, the logical spaces are associated with the one or more file systems to provide sampled combinations of sampled portions of file system entities (FSEs) and sampled points in time; (b) searching for relevant snapshots that are relevant to the sampled combinations to provide relevant snapshots at the sampled points in time; and (c) determining physical sizes of the relevant snapshots at the sampled point in time; wherein a number of samples per sampled FSE is indicative of a size of the sampled FSEs.

    EFFICIENT FILE RECOVERY FROM TIERED CLOUD SNAPSHOTS

    公开(公告)号:US20230325286A1

    公开(公告)日:2023-10-12

    申请号:US17714408

    申请日:2022-04-06

    申请人: Rubrik, Inc.

    摘要: A file system in a user space partition of virtual memory may be mounted by a computing device that runs a virtual machine which includes a set of storage disks. The file system in user space may then expose one or more virtual files associated with one or more storage disks that correspond to one or more loop devices configured to map files of the virtual machine to the one or more virtual files. The computing device may then receive a request to read a data block stored at the virtual machine and may identify a file and corresponding virtual file that stores the requested data block based on a set of metadata provided by the loop devices. The computing device may then determine the location of the data block stored at the virtual machine, and may read the data block from the determined location.

    MANAGING ARTIFACT INFORMATION INCLUDING FINDING A SEARCHED ARTIFACT INFORMATION ITEM

    公开(公告)号:US20230281009A1

    公开(公告)日:2023-09-07

    申请号:US18114408

    申请日:2023-02-27

    IPC分类号: G06F8/73 G06F16/14 G06F16/11

    摘要: A computer-implemented method for an improved management of artifact information is provided, particularly for facilitating finding a searched artifact information item in a plurality of artifact documents. The method includes receiving a user's input corresponding to searching a searched artifact information item; determining a document identifier of the artifact document; determining a closest lower snapshot preceding or corresponding to the revision of interest; determining a searched snapshot by appending to the closest lower snapshot; determining the respective document identifier of the respective artifact document including a latest version of the respective searched artifact information item at the revision of interest by intersecting the determined respective document identifier of the respective artifact document with the determined searched snapshot; and displaying information relating to the searched artifact information item at the revision of interest using the respective artifact document corresponding to the determined respective document identifier to the user.

    Distributed write journals that support fast snapshotting for a distributed file system

    公开(公告)号:US11741048B2

    公开(公告)日:2023-08-29

    申请号:US17725346

    申请日:2022-04-20

    申请人: Cohesity, Inc.

    发明人: Apurv Gupta

    IPC分类号: G06F17/00 G06F7/00 G06F16/11

    CPC分类号: G06F16/128

    摘要: Embodiments presented herein disclose techniques for capturing a snapshot of a file system object (e.g., a file or a directory) that is associated with a write journal having outstanding data. A bridge process in a storage server receives a request to capture a snapshot of a file system object. The snapshot is a backup of a state of the file system object in a given point in time. Upon determining that the file system object has one or more outstanding updates recorded in a write journal, the bridge process generates a copy of the write journal. The bridge process captures the snapshot of the file system object. The bridge process also associates the copy of the write journal with the snapshot of the file system object.

    SYSTEMS, METHODS, AND STORAGE MEDIA FOR IDENTIFYING AN OBJECT IN A PHOTOGRAPH USING A MACHINE LEARNING SYSTEM

    公开(公告)号:US20230267378A1

    公开(公告)日:2023-08-24

    申请号:US17848989

    申请日:2022-06-24

    申请人: Earthsnap, Inc.

    发明人: Eric Ralls

    摘要: Systems, methods, and storage media for operating a machine learning system for identifying an object in a photograph are disclosed. The system is configured to prepare a plurality of data files for training the machine learning system by associating a label with each of the plurality of data files, splitting the plurality of data files into different data sets, including full, training, testing, and validation data sets, creating a final machine learning model based on metrics and/or artifacts associated with training on the full data set, and deploying the final machine learning model to a machine learning system endpoint. The system is further configured to identify at least one object in a user uploaded photograph based on invoking a first or a second trained model, the first or second trained model associated with the final machine learning model.