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    KEEPING STABLE LEADERSHIP IN RAFT-BASED PROTOCOL WITH FAST AUTOMATIC FAILOVER
    51.
    发明公开
    KEEPING STABLE LEADERSHIP IN RAFT-BASED PROTOCOL WITH FAST AUTOMATIC FAILOVER 审中-公开

    公开(公告)号：US20240134879A1

    公开(公告)日：2024-04-25

    申请号：US18227288

    申请日：2023-07-27

    Applicant: Oracle International Corporation

    Inventor： Leonid Novak ,  Lik Wong ,  Sampanna Salunke

    IPC: G06F16/27

    CPC classification number: G06F16/27

    Abstract: A node within a group of participant nodes begins an election by sending a vote request to the other nodes in the group. The vote request sets an input term argument to a future term value without incrementing the actual current term value. The current term value at each participant node is only incremented in response to a successful leadership change. At startup time, a candidate node issues a vote request with a non-disruptive election type. An established leader automatically rejects a non-disruptive vote request. A heartbeat loss vote request is rejected by each receiving node if its own heartbeat timeout does not exceed a predetermined limit. A mandatory vote request informs the leader node that it should stop requesting new workload. This is used in manual leadership transition to make sure that the old leader does not accept new transactions during the leadership transition.

    Correlation-based analytic for time-series data
    54.
    发明授权
    Correlation-based analytic for time-series data 有权

    公开(公告)号：US10970186B2

    公开(公告)日：2021-04-06

    申请号：US16213152

    申请日：2018-12-07

    Applicant: Oracle International Corporation

    Inventor： Sampanna Salunke ,  Dustin Garvey ,  Uri Shaft ,  Lik Wong

    IPC: G06F11/00 ,  G06F11/34 ,  G06F11/07

    Abstract: Techniques are described for modeling variations in correlation to facilitate analytic operations. In one or more embodiments, at least one computing device receives first metric data that tracks a first metric for a first target resource and second metric data that tracks a second metric for a second target resource. In response to receiving the first metric data and the second metric data, the at least one computing device generates a time-series of correlation values that tracks correlation between the first metric and the second metric over time. Based at least in part on the time-series of correlation data, an expected correlation is determined and compared to an observed correlation. If the observed correlation falls outside of a threshold range or otherwise does not satisfy the expected correlation, then an alert and/or other output may be generated.

    UNSUPERVISED METHOD FOR CLASSIFYING SEASONAL PATTERNS
    56.
    发明申请
    UNSUPERVISED METHOD FOR CLASSIFYING SEASONAL PATTERNS 审中-公开

    公开(公告)号：US20200258005A1

    公开(公告)日：2020-08-13

    申请号：US16862496

    申请日：2020-04-29

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong

    IPC: G06N20/00

    Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.

    Supervised method for classifying seasonal patterns
    57.
    发明授权
    Supervised method for classifying seasonal patterns 有权

    公开(公告)号：US10699211B2

    公开(公告)日：2020-06-30

    申请号：US15057060

    申请日：2016-02-29

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong

    IPC: G06F15/18 ,  G06N20/00

    Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal. Based on the noise signal, a first classification is generated for a plurality of seasonal instances within the set of time series data, where each respective instance of the plurality of instances corresponds to a respective sub-period within the season and the first classification associates a first set of one or more instances from the plurality of instances with a particular class of seasonal pattern. Based on the dense signal, a second classification is generated that associates a second set of one or more instances with the particular class. Based on the first classification and the second classification, a third classification is generated, where the third classification associates a third set of one or more instances with the particular class.

    Eager replication of uncommitted transactions
    58.
    发明授权
    Eager replication of uncommitted transactions 有权

    公开(公告)号：US10678808B2

    公开(公告)日：2020-06-09

    申请号：US15692141

    申请日：2017-08-31

    Applicant: ORACLE INTERNATIONAL CORPORATION

    Inventor： Edwina Ming-Yue Lu ,  Nimar Singh Arora ,  Lik Wong

    IPC: G06F16/20 ,  G06F16/27 ,  G06F16/23

    Abstract: Techniques are provided for eager replication of uncommitted transactions. In embodiments, a replication client receives, in a data stream, change records corresponding to database changes applied to a source database in a transaction. The change records does not include a commit record that indicates that the transaction is committed on the source database. Before receiving the commit record, the replication client computes transaction dependency data based on the change records and detects, based on the transaction dependency data, that the transaction can be at least partially applied to a target database. Also before receiving the commit record, the replication client applies, to a target database and based on the detecting, at least some of the change records. Upon receiving the commit record of the transaction, the replication client completes applying the change records and commits the transaction on the target database.

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