Microsoft Technology Licensing, LLC

Tao Guan

Haibo Lin

Zhicheng Yin

Jaliya Nishantha Ekanayake

Jingren Zhou

Eric Boutin

Xiaoyu Chen

Paul Michael Brett

Nan Zhang

Anna Korsun

Pavel N Iakovenko

Marc Todd Friedman

Raghunath Ramakrishnan

Jin Sun

Yongchul Kwon

José A Blakeley

Ming Li

Processing a job request for multiple versions of a distributed computing service. The service processing node does this by at least interleavingly (e.g., via time sharing with rapid context switching, or by actually concurrently) running a first runtime library associated with a first service version of the distributed computerized service and a second runtime library associated with a different service version of the distributed computerized service. While running the first runtime library, job requests of a first service version may be at least partially processed using a first set of one or more executables that interact with the first runtime library. While running the second runtime library, job requests of a second service version may be at least partially processed using a second set of one or more executables that interact with the second runtime library.

Processing requests for multi-versioned service

Processing received job requests for a multi-versioned distributed computerized service. For each received job request, the job request is channeled to an appropriate service processing node that depends on the version of the distributed computing service that is to handle the job request. A version of the distributed computing service is assigned to the incoming job request. A service processing node that runs a runtime library for the assigned service version is then identified. The identified service processing node also has an appropriate set of one or more executables that allows the service processing node to plan an appropriate role (e.g., compiler, scheduler, worker) in the distributed computing service. The job request is then dispatched to the identified service processing node.

Processing request for multi-versioned service

Aspects extend to methods, systems, and computer program products for optimally pipelining result sets with fault tolerance in distributed query execution. Distributed computing jobs are optimized by dividing the distributed computing jobs into one or more bubbles for execution. Each bubble can be independently executed, potentially in parallel with other bubbles, when resources to handle the bubble are available. Intra-bubble communication can be streamed between vertices within a bubble. Inter-bubble communication can be stored to durable storage. Bubbles provide a failure boundary for a job graph and re-executing a bubble along with storage of intermediate results in durable storage can be used to recover from failures. When a vertex inside a bubble fails, computation can resume by rescheduling the execution of the failed bubble from the durable inputs for that bubble. Durable storage provides a light-weight failover to handle non-deterministic behavior. Jobs can also leverage streaming to increase performance.

Optimizing pipelining result sets with fault tolerance in distributed query execution

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Tao Guan