PPT-Sparrow Distributed Low-Latency Spark Scheduling

Author : sherrill-nordquist | Published Date : 2018-03-17

Kay Ousterhout Patrick Wendell Matei Zaharia Ion Stoica Outline The Spark scheduling bottleneck Sparrows fully distributed faulttolerant technique Sparrows

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Sparrow Distributed Low-Latency Spark Scheduling: Transcript

Kay Ousterhout Patrick Wendell Matei Zaharia Ion Stoica Outline The Spark scheduling bottleneck Sparrows fully distributed faulttolerant technique Sparrows nearoptimal performance. Large-scale near-real-time stream processing. Tathagata . Das (TD). along with. Matei. . Zaharia. , . Haoyuan. Li, Timothy Hunter, Scott . Shenker. , Ion . Stoica. , and many others. UC BERKELEY. What is . Kulkarni. . Ameya.s. . JongHwa. Song. Ashvin. Goal (University of Toronto). Charles . Krasic. (University of British Columbia). Jonathan Walpole (Portland State University) . A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei Zaharia, Mosharaf Chowdhury. , Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica. … from POC to production. What does VideoAnalytics do? (1). What does VideoAnalytics do? (2). What does VideoAnalytics do? (3). Why Spark Streaming?. It's a text-book example for the type of app. SS was designed for.. Shreya. The Problem. Machine learning requires real time, accurate, and robust predictions under heavy query load.. Most machine learning frameworks care about optimizing model training not deployment. Selah – Greatest Hymns, ©2005. Lyrics by . Civilla. D. Martin. Why do I feel . Discouraged. Why do the . shadows . come. And why does . my . heart . feel . lonely. And long . for . heaven . and . Kay Ousterhout, Patrick Wendell, . Matei. . Zaharia. , . Ion . Stoica. Sparrow schedules tasks in clusters. using a . decentralized, randomized approach. Sparrow schedules tasks in clusters. using a . Niladrish Chatterjee. Mike O’Connor. Gabriel H. . Loh. Nuwan. . Jayasena. Rajeev . Balasubramonian. Irregular GPGPU Applications. Conventional GPGPU workloads access vector or matrix-based data structures. Reetuparna. Das. €. §. . Onur. Mutlu. †. . Thomas Moscibroda. ‡. . Chita Das. §. € . Intel Labs . §. PennState. . †. CMU . ‡. Microsoft Research. Network-on-Chip. Network-on-Chip. Reetuparna. Das. €. §. . Onur. Mutlu. †. . Thomas Moscibroda. ‡. . Chita Das. §. € . Intel Labs . §. PennState. . †. CMU . ‡. Microsoft Research. Network-on-Chip. Network-on-Chip. Openstack. *. Yunhong Jiang . Yunhong.Jiang@intel.com. *Other names and brands may be claimed as the property of others.. Agenda. NFV and network . l. atency. Why network latency on NFV. How to achieve . Explained (T he more things change the more they stay the same) Arnon Rotem - Gal - Oz [This whitepaper is based on a series of blog posts that first appeared in Dr. Dobb's Portal www.ddj.com/dept/a APPRAISAL . REPORT RECORDING ONLINE WINDOW. SPARROW . – . Agenda. SPARROW – Snapshot of Features. Workflow . Setting. Authorisation. & Access Roles . Document . Upload . option. Digital . Signing & e-Signing. Date:. 2024-. 10. -. 10. October 2024. Akira Kishida, NTT. Slide . 1. Authors:. Name. Affiliations. Address. Phone. e-mail. Akira Kishida. NTT. 1-1, Hikarinooka Yokosuka-Shi, Kanagawa 239-0847, Japan.

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