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公开(公告)号:US10581964B2
公开(公告)日:2020-03-03
申请号:US15845855
申请日:2017-12-18
Applicant: Amazon Technologies, Inc.
Inventor: Jonathan Daly Einkauf , Luca Natali , Bhargava Ram Kalathuru , Saurabh Dileep Baji , Abhishek Rajnikant Sinha
Abstract: A service provider may apply customer-selected or customer-defined auto-scaling policies to a cluster of resources (e.g., virtualized computing resource instances or storage resource instances in a MapReduce cluster). Different policies may be applied to different subsets of cluster resources (e.g., different instance groups containing nodes of different types or having different roles). Each policy may define an expression to be evaluated during execution of a distributed application, a scaling action to take if the expression evaluates true, and an amount by which capacity should be increased or decreased. The expression may be dependent on metrics emitted by the application, cluster, or resource instances by default, metrics defined by the client and emitted by the application, or metrics created through aggregation. Metric collection, aggregation and rules evaluation may be performed by a separate service or by cluster components. An API may support auto-scaling policy definition.
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公开(公告)号:US11461329B2
公开(公告)日:2022-10-04
申请号:US17006522
申请日:2020-08-28
Applicant: Amazon Technologies, Inc.
Inventor: Xing Wu , Bhargava Ram Kalathuru , Jian Fang , Yuanyuan Yue , Pratik Bhagwat Gawande , Turkay Mert Hocanin , Jason Douglas Denton , Luca Natali , Rahul Sharma Pathak , Abhishek Rajnikant Sinha , Sumeetkumar Veniklal Maru , Armen Tangamyan , Yufeng Jiang
IPC: G06F7/00 , G06F16/2453 , G06F16/21 , G06F16/248 , G06F16/28 , G06F16/2455 , G06F16/2458 , G06F16/903 , G06F9/50 , G06F16/27 , G06F16/20 , G06F16/25 , H04L67/1008 , H04L67/1029 , H04L67/10 , H04L67/1031 , G06F16/245
Abstract: Query execution status may be tracked to selectively route queries to resources for execution. The completion of queries executing at computing resources obtained from a pool of computing resources configured to execute queries may be detected. Instead of returning the computing resources to the pool, the computing resources may be identified as available in resource management data. When another query is received, the resource management data may be evaluated to select an available computing resource. The query may then be routed to the selected computing resource for execution.
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公开(公告)号:US20210392185A1
公开(公告)日:2021-12-16
申请号:US17352065
申请日:2021-06-18
Applicant: Amazon Technologies, Inc.
Inventor: Jonathan Daly Einkauf , Luca Natali , Bhargava Ram Kalathuru , Saurabh Dileep Baji , Abhishek Rajnikant Sinha
Abstract: A service provider may apply customer-selected or customer-defined auto-scaling policies to a cluster of resources (e.g., virtualized computing resource instances or storage resource instances in a MapReduce cluster). Different policies may be applied to different subsets of cluster resources (e.g., different instance groups containing nodes of different types or having different roles). Each policy may define an expression to be evaluated during execution of a distributed application, a scaling action to take if the expression evaluates true, and an amount by which capacity should be increased or decreased. The expression may be dependent on metrics emitted by the application, cluster, or resource instances by default, metrics defined by the client and emitted by the application, or metrics created through aggregation. Metric collection, aggregation and rules evaluation may be performed by a separate service or by cluster components. An API may support auto-scaling policy definition.
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公开(公告)号:US20210097080A1
公开(公告)日:2021-04-01
申请号:US17067495
申请日:2020-10-09
Applicant: Amazon Technologies, Inc.
Inventor: Bhargava Ram Kalathuru , Jian Fang , Xing Wu , Yuanyuan Yue , Pratik Bhagwat Gawande , Turkay Mert Hocanin , Jason Douglas Denton , Luca Natali , Rahul Sharma Pathak , Abhishek Rajnikant Sinha , Sumeetkumar Veniklal Maru , Armen Tangamyan , Yufeng Jiang
IPC: G06F16/2453 , G06F16/21 , G06F16/248 , G06F16/28 , G06F16/2455 , G06F16/2458 , G06F16/903 , G06F9/50 , G06F16/27 , G06F16/20 , G06F16/25 , H04L29/08
Abstract: Queries may be received and executed by a managed query service. A query directed to data sets that are separately stored in a remote data store may be received. Computing resources to execute the query may be provisioned from a pool of computing resources that are configured to execute queries. The query may be routed to the provisioned computing resources to execute the query. Results may be obtained from the computing resource and provided to a submitter of the query.
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公开(公告)号:US20180060400A1
公开(公告)日:2018-03-01
申请号:US15470841
申请日:2017-03-27
Applicant: Amazon Technologies, Inc.
Inventor: Xing Wu , Bhargava Ram Kalathuru , Jian Fang , Yuanyuan Yue , Pratik Bhagwat Gawande , Turkay Mert Hocanin , Jason Douglas Denton , Luca Natali , Rahul Sharma Pathak , Abhishek Rajnikant Sinha , Sumeetkumar Veniklal Maru , Armen Tangamyan , Yufeng Jiang
Abstract: Query execution status may be tracked to selectively route queries to resources for execution. The completion of queries executing at computing resources obtained from a pool of computing resources configured to execute queries may be detected. Instead of returning the computing resources to the pool, the computing resources may be identified as available in resource management data. When another query is received, the resource management data may be evaluated to select an available computing resource. The query may then be routed to the selected computing resource for execution.
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公开(公告)号:US20180060393A1
公开(公告)日:2018-03-01
申请号:US15470829
申请日:2017-03-27
Applicant: Amazon Technologies, Inc.
Inventor: Bhargava Ram Kalathuru , Jian Fang , Xing Wu , Yuanyuan Yue , Pratik Bhagwat Gawande , Turkay Mert Hocanin , Jason Douglas Denton , Luca Natali , Rahul Sharma Pathak , Abhishek Rajnikant Sinha , Sumeetkumar Veniklal Maru , Armen Tangamyan , Yufeng Jiang
IPC: G06F17/30
Abstract: Queries may be received and executed by a managed query service. A query directed to data sets that are separately stored in a remote data store may be received. Computing resources to execute the query may be provisioned from a pool of computing resources that are configured to execute queries. The query may be routed to the provisioned computing resources to execute the query. Results may be obtained from the computing resource and provided to a submitter of the query.
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公开(公告)号:US09848041B2
公开(公告)日:2017-12-19
申请号:US14702080
申请日:2015-05-01
Applicant: Amazon Technologies, Inc.
Inventor: Jonathan Daly Einkauf , Luca Natali , Bhargava Ram Kalathuru , Saurabh Dileep Baji , Abhishek Rajnikant Sinha
IPC: G06F15/173 , H04L29/08 , H04L12/26 , H04L12/24 , G06F9/50
CPC classification number: H04L67/1076 , G06F9/5077 , G06F9/5083 , H04L41/0893 , H04L43/0876 , H04L67/10 , H04L67/1031
Abstract: A service provider may apply customer-selected or customer-defined auto-scaling policies to a cluster of resources (e.g., virtualized computing resource instances or storage resource instances in a MapReduce cluster). Different policies may be applied to different subsets of cluster resources (e.g., different instance groups containing nodes of different types or having different roles). Each policy may define an expression to be evaluated during execution of a distributed application, a scaling action to take if the expression evaluates true, and an amount by which capacity should be increased or decreased. The expression may be dependent on metrics emitted by the application, cluster, or resource instances by default, metrics defined by the client and emitted by the application, or metrics created through aggregation. Metric collection, aggregation and rules evaluation may be performed by a separate service or by cluster components. An API may support auto-scaling policy definition.
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