公开(公告)号：US12118009B2

公开(公告)日：2024-10-15

申请号：US16657916

申请日：2019-10-18

申请人： Splunk Inc.

发明人： Arindam Bhattacharjee ,  Sourav Pal ,  Timothy Tully

IPC分类号： G06F16/2458 ,  G06F16/2452

CPC分类号： G06F16/2471 ,  G06F16/24526

摘要： 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.

公开(公告)号：US20200050612A1

公开(公告)日：2020-02-13

申请号：US16657916

申请日：2019-10-18

申请人： Splunk Inc.

发明人： Arindam Bhattacharjee ,  Sourav Pal ,  Timothy Tully

IPC分类号： G06F16/28 ,  G06F16/2452

摘要： 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.

公开(公告)号：US11921672B2

公开(公告)日：2024-03-05

申请号：US16657872

申请日：2019-10-18

申请人： Splunk Inc.

发明人： Sourav Pal ,  Arindam Bhattacharjee ,  Timothy Tully

IPC分类号： G06F16/14 ,  G06F16/13 ,  G06F16/17

CPC分类号： G06F16/148 ,  G06F16/13 ,  G06F16/1734

摘要： Systems and methods are described for executing a query of raw machine data that is stored at a remote data store that may store heterogeneous data. The system can determine the directories or file types that may store event data and may instruct one or more worker nodes to access files that may store events based on the determined directories of file types. Further, the system may exclude files at the remote data store that may not be identified as potentially storing events enabling a query that implicates a heterogeneous data store to be efficiently executed.

公开(公告)号：USD977476S1

公开(公告)日：2023-02-07

申请号：US29768604

申请日：2021-01-29

申请人： SPLUNK Inc.

设计人： Timothy Tully ,  Tishan Mills ,  Jesse Chor ,  Robert Fullerton

公开(公告)号：US20200050586A1

公开(公告)日：2020-02-13

申请号：US16657872

申请日：2019-10-18

申请人： Splunk Inc.

发明人： Sourav Pal ,  Arindam Bhattacharjee ,  Timothy Tully

IPC分类号： G06F16/14 ,  G06F16/13 ,  G06F16/2452 ,  G06F16/17 ,  G06F16/2458

摘要： Systems and methods are described for executing a query of raw machine data that is stored at a remote data store that may store heterogeneous data. The system can determine the directories or file types that may store event data and may instruct one or more worker nodes to access files that may store events based on the determined directories of file types. Further, the system may exclude files at the remote data store that may not be identified as potentially storing events enabling a query that implicates a heterogeneous data store to be efficiently executed.