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. Shouling. . Ji. and . Raheem. . Beyah. CAP group, School of Electrical and Computer Engineering. Georgia Institute of Technology. Zhipeng. . Cai. . Department of Computer Science. Georgia State . Distributed. , Low Latency Scheduling. 72130310 . 임규찬. Abstract. Introduction. Design Goals. Sample-Based Scheduling for Parallel . Jobs. Implements. 목차. Large-scale data analytics frameworks are shifting. SQL:. Relational . Data Processing in Spark. Michael Armbrust. , . Reynold. . Xin. , Cheng . Lian. , . Yin . Huai. , . Davies . Liu, Joseph K. Bradley, . Xiangrui. . Meng. , . Tomer. Kaftan, Michael J. Franklin, Ali . 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. SQL:. Relational . Data Processing in Spark. Michael Armbrust. , . Reynold. . Xin. , Cheng . Lian. , . Yin . Huai. , . Davies . Liu, Joseph K. Bradley, . Xiangrui. . Meng. , . Tomer. Kaftan, Michael J. Franklin, Ali . Andy Dang. About Me. Andy Dang. Software Development Engineer. Amazon Development Centre Scotland. At Amazon . since graduating in . 2014. Understanding Relationships in the Catalogue. AWARENESS. CONSIDERATION. (with thanks to . Paco. Nathan and . Databricks. ). Quick Demo. Quick Demo. API Hooks. Scala. / Java. All Java libraries. *.jar. http://www.scala-lang.org. Python. Anaconda: . https://store.continuum.io/cshop/anaconda. 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 . 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. 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 The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand and Use Cases for Data Analysis. Afzal Godil. Information Access Division, ITL, NIST. Outline. Growth of big datasets. I. ntroduction to Apache . Hadoop. and Spark for developing applications . Components of Hadoop, HDFS, MapReduce and .

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