External dataset capability compensation

    公开(公告)号:US11163758B2

    公开(公告)日:2021-11-02

    申请号:US15665248

    申请日:2017-07-31

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for processing queries against an external data source utilizing dynamically allocated partitions operating on one or more worker nodes. The external data source can include data that has not been processed by the system. To query the external data source, a query coordinator can generate a subquery for the external data source based on determined functionality of the data source. The subquery can identify data in the external data source for processing and a manner for processing the data. In addition, the query coordinator can dynamically allocate partitions operating on worker nodes to retrieve and intake results of the subquery. In some cases, number of partitions allocated can be based on a number of partitions supported by the external data source.

    Converting and modifying a subquery for an external data system

    公开(公告)号:US11023463B2

    公开(公告)日:2021-06-01

    申请号:US16146990

    申请日:2018-09-28

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for receiving, at a data intake and query system, a query that includes a subquery that is to be executed at an external data system that supports a different query language than the data intake and query system. The data intake and query system converts the subquery from the query language supported by the external data system to the query language supported by the data intake and query system. The data intake and query system then processes the query including the translated subquery. The translated subquery is then translated back to the language supported by the external data system including any processing or optimizations performed with respect to the subquery.

    MANAGEMENT OF DISTRIBUTED COMPUTING FRAMEWORK COMPONENTS IN A DATA FABRIC SERVICE SYSTEM

    公开(公告)号:US20210117425A1

    公开(公告)日:2021-04-22

    申请号:US16657899

    申请日:2019-10-18

    Applicant: Splunk Inc.

    Abstract: Systems and methods are described for establishing and managing components of a distributed computing framework implemented in a data intake and query system. The distributed computing framework may include a master and a plurality of worker nodes. The master may selectively operate on a search head captain that is chosen from the search heads of the data intake and query system. The search head captain may distribute configuration information for the master and the distributed computing framework to the other search heads, which in turn, may distribute that configuration information to indexers of the data intake and query system. Worker nodes may be selectively activated for operation on the indexers based on the configuration information, and the worker nodes may additionally use the configuration information to contact the master and join the distributed computing framework. This approach may provide numerous benefits, including improved security, flexibility in the selection of worker nodes, and redundancy for failures of physical components of the data intake and query system.

    Batch searches in data fabric service system

    公开(公告)号:US10592563B2

    公开(公告)日:2020-03-17

    申请号:US15339853

    申请日:2016-10-31

    Applicant: Splunk Inc.

    Abstract: The disclosed embodiments include a technique to obtain search results from the application of transformation operations on partial search results obtained from across internal and/or external data sources. Examples of transformation operations include arithmetic operations such as an average, mean, count, or the like. Examples of reporting transformations include join operations, statistics, sort, top head. Hence, the search results of a search query can be derived from partial search result rather than include the actual partial search results. In this case, the ordering of the search results may be nonessential. An example of a search query that requires a transformation operation is a “batch” or “reporting” search query. The related disclosed techniques involve obtaining data stored in the bid data ecosystem, and returning that data or data derived from that data.

    ADDRESSING MEMORY LIMITS FOR PARTITION TRACKING AMONG WORKER NODES

    公开(公告)号:US20200065303A1

    公开(公告)日:2020-02-27

    申请号:US16657867

    申请日:2019-10-18

    Applicant: Splunk Inc.

    Abstract: Systems and methods are described for distributed processing a query in a first query language utilizing a query execution engine intended for single-device execution. While distributed processing provides numerous benefits over single-device processing, distributed query execution engines can be significantly more difficult to develop that single-device engines. Embodiments of this disclosure enable the use of a single-device engine to support distributed processing, by dividing a query into multiple stages, each of which can be executed by multiple, concurrent executions of a single-device engine. Between stages, data can be shuffled between executions of the engine, such that individual executions of the engine are provided with a complete set of records needed to implement an individual stage. Because single-device engines can be significantly less difficult to develop, use of the techniques described herein can enable a distributed system to rapidly support multiple query languages.

    REASSIGNING PROCESSING TASKS TO AN EXTERNAL STORAGE SYSTEM

    公开(公告)号:US20200050607A1

    公开(公告)日:2020-02-13

    申请号:US16657894

    申请日:2019-10-18

    Applicant: Splunk Inc.

    Abstract: Systems and methods are described for reducing execution time of a query that references external data systems. The system can determine an external data system is capable of processing one or more map or reduce phases of a map-reduce operation. When it is determined that the external data system can process a map or reduce phase, associated operations may be reassigned from the system to the external data system reducing the processing resources used by the system to response to the query and, in some cases, speeding up performance of the query.

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