Data Analytics In Edge Devices
    11.
    发明申请

    公开(公告)号:US20200012966A1

    公开(公告)日:2020-01-09

    申请号:US16573745

    申请日:2019-09-17

    Applicant: Splunk Inc.

    Abstract: Disclosed is a technique that can be performed by an electronic device. The electronic device can generate time-stamped events, extract training data from the time-stamped events, and sending the training data over a network to a remote computer. The electronic device can receive model data generated by the remote computer from the training data by use of a machine learning process, update a local model of the electronic device based on the received model data, and generate an output by processing locally sourced data of the electronic device with the updated local model.

    Machine learning in edge analytics
    12.
    发明授权

    公开(公告)号:US10460255B2

    公开(公告)日:2019-10-29

    申请号:US15224439

    申请日:2016-07-29

    Applicant: Splunk Inc.

    Abstract: Disclosed is a technique that can be performed by an electronic device. The technique can include generating raw data based on inputs to the electronic device, and sending the raw data or data items over a network to a server computer system. The sent raw data or the data items can include training data. The technique can further include receiving global model data from the server computer system over the network. The global model data may have been derived from the training data in accordance with a machine learning process. The technique can further include generating an updated local model by updating a local model associated with the electronic device based on the received global model data, and processing local data based on the updated local model to generate output data. The local data can include raw data or data items generated based on inputs to the electronic device.

    Filesystem destinations
    13.
    发明授权

    公开(公告)号:US12174797B1

    公开(公告)日:2024-12-24

    申请号:US18103323

    申请日:2023-01-30

    Applicant: Splunk Inc.

    Abstract: A method for file system destinations includes obtaining events for storage on one or more of the storage systems. For each event, the method includes extracting at least one field value from the event, comparing the at least one field value to configurations of the storage systems to identify at least one storage system of the plurality of storage systems having a matching configuration, transmitting the event to an ingest module queue for the at least one storage system, selecting a partition for the event based on the at least one field value to obtain a selected partition, mapping the selected partition to a file using a partition mapping, and appending the event to the file on the at least one storage system.

    Bucket merging for a data intake and query system using size thresholds

    公开(公告)号:US11720537B2

    公开(公告)日:2023-08-08

    申请号:US17661510

    申请日:2022-04-29

    Applicant: Splunk Inc.

    CPC classification number: G06F16/2228 G06F16/14 G06F16/16

    Abstract: Systems and methods are disclosed for scalable bucket merging in a data intake and query system. Various components of a bucket manager can be used to monitor recently-created buckets of data in common storage that are associated with a particular tenant and a particular index, apply a comprehensive bucket merge policy to determine groups of buckets that qualify for merging, merge those group of buckets into merged buckets to be stored in the common storage, and update any information associated with the merged buckets and pre-merged buckets. These components may be shared across multiple tenants, and some of these components may be dynamically scalable based on need. This approach may also provide many additional benefits, including improved search performance from merged buckets, efficient resource utilization associated with discriminate merging, and redundancy in case of component failure.

    Scalable bucket merging for a data intake and query system

    公开(公告)号:US11334543B1

    公开(公告)日:2022-05-17

    申请号:US16657924

    申请日:2019-10-18

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for scalable bucket merging in a data intake and query system. Various components of a bucket manager can be used to monitor recently-created buckets of data in common storage that are associated with a particular tenant and a particular index, apply a comprehensive bucket merge policy to determine groups of buckets that qualify for merging, merge those group of buckets into merged buckets to be stored in the common storage, and update any information associated with the merged buckets and pre-merged buckets. These components may be shared across multiple tenants, and some of these components may be dynamically scalable based on need. This approach may also provide many additional benefits, including improved search performance from merged buckets, efficient resource utilization associated with discriminate merging, and redundancy in case of component failure.

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