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    INTELLIGENT PREPROCESSING OF MULTI-DIMENSIONAL TIME-SERIES DATA
    51.
    发明申请
    INTELLIGENT PREPROCESSING OF MULTI-DIMENSIONAL TIME-SERIES DATA 审中-公开

    公开(公告)号：US20190286725A1

    公开(公告)日：2019-09-19

    申请号：US15925427

    申请日：2018-03-19

    Applicant: Oracle International Corporation

    Inventor： Dieter Gawlick ,  Kenny C. Gross ,  Zhen Hua Liu ,  Adel Ghoneimy

    IPC: G06F17/30 ,  G06N99/00 ,  G06N5/04

    Abstract: The disclosed embodiments relate to a system that preprocesses sensor data to facilitate prognostic-surveillance operations. During operation, the system obtains training data from sensors in a monitored system during operation of the monitored system, wherein the training data comprises time-series data sampled from signals produced by the sensors. The system also obtains functional requirements for the prognostic-surveillance operations. Next, the system performs the prognostic-surveillance operations on the training data and determines whether the prognostic-surveillance operations meet the functional requirements when tested on non-training data. If the prognostic-surveillance operations do not meet the functional requirements, the system iteratively applies one or more preprocessing operations to the training data in order of increasing computational cost until the functional requirements are met.

    Predicate offload of large objects
    52.
    发明授权
    Predicate offload of large objects 有权

    公开(公告)号：US10409795B2

    公开(公告)日：2019-09-10

    申请号：US13831137

    申请日：2013-03-14

    Applicant: ORACLE INTERNATIONAL CORPORATION

    Inventor： Vineet Marwah ,  Amit Ganesh ,  Teck Hua Lee ,  Hui Joe Chang ,  Zhen Hua Liu

    IPC: G06F16/22

    Abstract: In an approach, the database server generates a request for data representing rows of a table, the request identifying one or more data blocks stored on a storage system. The database server then generates metadata describing one or more filtering conditions to be applied to the rows and sends the metadata along with the request to the storage system. The storage system, when applying filtering conditions to a column containing a LOB, determines whether the LOB is stored in-line or out-of-line. If the column contains an out-of-line LOB, the storage system skips the filtering conditions on the column. If the column contains an in-line LOB, the storage system applies the filtering conditions to the column. Upon obtaining the filtered data from the storage system, the database server retrieves the data blocks for out-of-line LOBs and applies the skipped filtering conditions to create a final result set.

    MULTIVARIATE MEMORY VECTORIZATION TECHNIQUE TO FACILITATE INTELLIGENT CACHING IN TIME-SERIES DATABASES
    53.
    发明申请
    MULTIVARIATE MEMORY VECTORIZATION TECHNIQUE TO FACILITATE INTELLIGENT CACHING IN TIME-SERIES DATABASES 审中-公开

    公开(公告)号：US20190236162A1

    公开(公告)日：2019-08-01

    申请号：US15885600

    申请日：2018-01-31

    Applicant: Oracle International Corporation

    Inventor： Kenny C. Gross ,  Mengying Li ,  Dieter Gawlick ,  Zhen Hua Liu

    IPC: G06F17/30

    CPC classification number: G06F16/1744 ,  G06F16/2237 ,  G06F16/2453 ,  G06F16/24561

    Abstract: The disclosed embodiments relate to a system that caches time-series data in a time-series database system. During operation, the system receives the time-series data, wherein the time-series data comprises a series of observations obtained from sensor readings for each signal in a set of signals. Next, the system performs a multivariate memory vectorization (MMV) operation on the time-series data, which selects a subset of observations in the time-series data that represents an underlying structure of the time-series data for individual and multivariate signals that comprise the time-series data. The system then performs a geometric compression aging (GAC) operation on the selected subset of time-series data. While subsequently processing a query involving the time-series data, the system: caches the selected subset of the time-series data in an in-memory database cache in the time-series database system; and accesses the selected subset of the time-series data from the in-memory database cache.

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