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    Pluggable architecture for embedding analytics in clustered in-memory databases
    141.
    发明授权
    Pluggable architecture for embedding analytics in clustered in-memory databases 有权

    公开(公告)号：US09659108B2

    公开(公告)日：2017-05-23

    申请号：US14558055

    申请日：2014-12-02

    Applicant: QBASE, LLC

    Inventor： Scott Lightner ,  Franz Weckesser

    IPC: G06F17/30 ,  G06F11/34

    CPC classification number: G06F17/30545 ,  G06F11/3055 ,  G06F11/3409 ,  G06F17/30371 ,  G06F17/30867 ,  G06F17/30964 ,  G06F2201/80

    Abstract: Disclosed are pluggable, distributed computing-system architectures allowing for embedding analytics to be added or removed from nodes of a system hosting an in-memory database. The disclosed system includes an API that may be used to create customized, application specific analytics modules. The newly created analytics modules may be easily plugged into the in-memory database. Each user query submitted to the in-memory database may specify different analytics be applied with differing parameters. All analytics modules operate on the in-memory image of the data, inside the in-memory database platform. All the analytics modules, may be capable of performing on-the-fly analytics, which may allow a dynamic and comprehensive processing of search results.

    Delta store giving row-level versioning semantics to a non-row-level versioning underlying store
    142.
    发明授权
    Delta store giving row-level versioning semantics to a non-row-level versioning underlying store 有权

    公开(公告)号：US09659050B2

    公开(公告)日：2017-05-23

    申请号：US13960335

    申请日：2013-08-06

    Applicant: Mihnea Andrei ,  Colin Florendo ,  Anil Kumar Goel

    Inventor： Mihnea Andrei ,  Colin Florendo ,  Anil Kumar Goel

    IPC: G06F17/30 ,  G06F11/14

    CPC classification number: G06F17/30362 ,  G06F11/1448 ,  G06F17/30309 ,  G06F17/30312 ,  G06F17/30315 ,  G06F17/30339 ,  G06F17/30368 ,  G06F17/30371 ,  G06F2201/80 ,  G06F2201/825 ,  G06F2201/84 ,  G06F2201/87

    Abstract: A delta store giving row-level versioning semantics to a non-row-level versioning underlying store is described. An example method includes establishing a column-based in-memory database including a main store and a delta store, where the main store does not allow concurrent transactions on a same table and the delta store has a plurality of row-visibility bitmaps implementing a row-level versioning mechanism that allows concurrent transactions on the same table. A transaction associated with the column-based in-memory database is received. For each table read by the transaction, a version of the table in the delta store that represents a transaction-consistent snapshot of the database visible to the transaction is determined. Each table is represented in the main store and the delta store; and each version of the table is represented by one or more bitmaps. Upon execution of a DML as part of the transaction, for each table written by the transaction, the data changes generated by the transaction is recorded in the one or more bitmaps that represent a private version of the table. Upon commit of the transaction, for each table written by the transaction, a new public version of the table is generated based on the private version of the table, and the public version represents a new transaction-consistent snapshot of the database visible to subsequent transactions.

    Data consistency and rollback for cloud analytics
    146.
    发明授权
    Data consistency and rollback for cloud analytics 有权

    公开(公告)号：US09646042B2

    公开(公告)日：2017-05-09

    申请号：US14862007

    申请日：2015-09-22

    Applicant: Dell Products L.P.

    Inventor： Ketan Bengali ,  Kaniska Mandal ,  Alex J. Chen

    IPC: G06F17/00 ,  G06F17/30 ,  G06F11/14

    CPC classification number: G06F17/30371 ,  G06F11/1469 ,  G06F17/30563 ,  G06F2201/80

    Abstract: An extract-transform-load (ETL) platform fetches consistent datasets in a batch for a given period of time and provides the ability to rollback that batch. The batch may be fetched for an interval of time, and the ETL platform may fetch new or changed data from different cloud/on-premise applications. It will store this data in the cloud or on-premise to build data history. As the ETL platform fetches new data, the system will not overwrite existing data, but rather will create new versions so that change history is preserved. For any reason, if businesses would like to rollback data, they could rollback to any previous batch.

    Opportunistic execution of secondary copy operations
    147.
    发明授权
    Opportunistic execution of secondary copy operations 有权

    公开(公告)号：US09645891B2

    公开(公告)日：2017-05-09

    申请号：US14561046

    申请日：2014-12-04

    Applicant: CommVault Systems, Inc.

    Inventor： Jun H. Ahn ,  Waqas Ashraf ,  Anup Kumar ,  Brahmaiah Vallabhaneni

    IPC: G06F11/14 ,  G06F11/30 ,  G06F11/34

    CPC classification number: G06F11/1461 ,  G06F11/1451 ,  G06F11/1453 ,  G06F11/3034 ,  G06F11/3485 ,  G06F2201/80 ,  G06F2201/81 ,  G06F2201/88

    Abstract: Rather than relying on pre-defined scheduling of secondary copy operations such as backup jobs, the illustrative opportunistic approach initiates secondary copy operations based on changing operational conditions in a storage management system. An adaptive backup readiness score is based on a number of backup-readiness operational factors. An illustrative enhanced data agent which is associated with the target database application (or other executable component) may monitor the operational factors and determine the backup readiness score based on weights assigned to the respective operational factors. The enhanced data agent may evaluate recent backup jobs to determine which of the operational factors that contributed to the backup readiness score may have been most relevant. Based on the most-relevant analysis, the enhanced data agent may adapt the weights assigned to the monitored operational factors, so that the backup readiness score may be more suitable and responsive to ongoing operational conditions in the system.

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