公开(公告)号：US20170339202A1

公开(公告)日：2017-11-23

申请号：US15481958

申请日：2017-04-07

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jingren Zhou ,  Zhengping Qian ,  Peter Zabback ,  Wei Lin

IPC: H04L29/06 ,  G06F17/30 ,  G06F11/14

CPC classification number: H04L65/60 ,  G06F11/1438 ,  G06F17/30463

Abstract: A low-latency cloud-scale computation environment includes a query language, optimization, scheduling, fault tolerance and fault recovery. An event model can be used to extend a declarative query language so that temporal analysis of event of an event stream can be performed. Extractors and outputters can be used to define and implement functions that extend the capabilities of the event-based query language. A script written in the extended query language can be translated into an optimal parallel continuous execution plan. Execution of the plan can be orchestrated by a streaming job manager which schedules vertices on available computing machines. The streaming job manager can monitor overall job execution. Fault tolerance can be provided by tracking execution progress and data dependencies in each vertex. In the event of a failure, another instance of the failed vertex can be scheduled. An optimal recovery point can be determined based on checkpoints and data dependencies.

公开(公告)号：US20190166173A1

公开(公告)日：2019-05-30

申请号：US16249357

申请日：2019-01-16

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jingren Zhou ,  Zhengping Qian ,  Peter Zabback ,  Wei Lin

IPC: H04L29/06 ,  G06F16/2453 ,  G06F11/14

Abstract: A low-latency cloud-scale computation environment includes a query language, optimization, scheduling, fault tolerance and fault recovery. An event model can be used to extend a declarative query language so that temporal analysis of event of an event stream can be performed. Extractors and outputters can be used to define and implement functions that extend the capabilities of the event-based query language. A script written in the extended query language can be translated into an optimal parallel continuous execution plan. Execution of the plan can be orchestrated by a streaming job manager which schedules vertices on available computing machines. The streaming job manager can monitor overall job execution. Fault tolerance can be provided by tracking execution progress and data dependencies in each vertex. In the event of a failure, another instance of the failed vertex can be scheduled. An optimal recovery point can be determined based on checkpoints and data dependencies.

公开(公告)号：US10225302B2

公开(公告)日：2019-03-05

申请号：US15481958

申请日：2017-04-07

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jingren Zhou ,  Zhengping Qian ,  Peter Zabback ,  Wei Lin

IPC: G06F17/30 ,  H04L29/06 ,  G06F11/14

Abstract: A low-latency cloud-scale computation environment includes a query language, optimization, scheduling, fault tolerance and fault recovery. An event model can be used to extend a declarative query language so that temporal analysis of event of an event stream can be performed. Extractors and outputters can be used to define and implement functions that extend the capabilities of the event-based query language. A script written in the extended query language can be translated into an optimal parallel continuous execution plan. Execution of the plan can be orchestrated by a streaming job manager which schedules vertices on available computing machines. The streaming job manager can monitor overall job execution. Fault tolerance can be provided by tracking execution progress and data dependencies in each vertex. In the event of a failure, another instance of the failed vertex can be scheduled. An optimal recovery point can be determined based on checkpoints and data dependencies.

公开(公告)号：US11271981B2

公开(公告)日：2022-03-08

申请号：US16249357

申请日：2019-01-16

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jingren Zhou ,  Zhengping Qian ,  Peter Zabback ,  Wei Lin

IPC: G06F16/00 ,  H04L65/60 ,  G06F16/2453 ,  G06F11/14

Abstract: A low-latency cloud-scale computation environment includes a query language, optimization, scheduling, fault tolerance and fault recovery. An event model can be used to extend a declarative query language so that temporal analysis of event of an event stream can be performed. Extractors and outputters can be used to define and implement functions that extend the capabilities of the event-based query language. A script written in the extended query language can be translated into an optimal parallel continuous execution plan. Execution of the plan can be orchestrated by a streaming job manager which schedules vertices on available computing machines. The streaming job manager can monitor overall job execution. Fault tolerance can be provided by tracking execution progress and data dependencies in each vertex. In the event of a failure, another instance of the failed vertex can be scheduled. An optimal recovery point can be determined based on checkpoints and data dependencies.