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所在主题： [Lecture Notes]Intro to Apache Spark Stanford University
文件名: Intro to Apache Spark Stanford University.pdf
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[hide] stanford.edu/~rezab/sparkclass [/hide] Spark ClassHosted by Stanford ICME August 13-15, 2014 Clark Center Auditorium, Stanford University Organizers: Reza Zadeh \| Matei Zaharia \| Ion Stoica A three-day class on distributed computing, using the high-speed cluster programming framework, Spark. Throughout the class, there will be hands-on exercises with computing resources provided by the organizers. The class will include introductions to the many Spark features, case studies from current users, best practices for deployment and tuning, future development plans, and hands-on exercises. Clark Center Auditorium James H. Clark Center Stanford, CA 94305 Wednesday August 13th to 15th, 2014 Please register here: Spark class registration Hands-on Exercises Please download the course materials here and slides Course Prerequisites: Laptop with WiFi capabilities Java 6 or 7 Schedule Day 1 (10am-4pm, lunch break 12:30-1:30pm) An introduction to Distributed Computing and Spark (Reza Zadeh) [slides] Hands-on exercises (Paco Nathan): [slides] Installing Spark, then running a first app Theory of operation, major abstractions Historical background Writing/running several example apps Review of the API in Scala, Python, Java Language Clustering Demo Databricks Cloud Demo Day 2 (10am-4pm, lunch break 12:30-1:30pm) Hands-on exercises (Paco Nathan): [slides] Review: coding assignment Extended Spark examples Unified engine across batch, iterative, SQL, ML, etc. Software development lifecycle: build, deploy, monitor Tooling: Maven, SBT, IPython notebook, etc. Production case studies Other resources for learning Installing the Cassandra / Spark OSS Stack Additional materials and exercises Day 3 (10am-2:30pm, lunch break 11:30-1pm) MLlib and Distributing the Singular Value Decomposition (Reza Zadeh) [slides] Towards an Optimizer for MLbase (Ameet Talwalkar) [slides] Graph Processing with the GraphX library (Ankur Dave) [slides] Spark Streaming (Tathagata Das) [slides]
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