{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

starfish-cps216-sep

starfish-cps216-sep - Starfish A Self-tuning System for Big...

Info icon This preview shows pages 1–12. Sign up to view the full content.

View Full Document Right Arrow Icon
Starfish: A Self-tuning System for Big Data Analytics Herodotos Herodotou, Harold Lim, Fei Dong, Shivnath Babu Duke University
Image of page 1

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Analysis in the Big Data Era 9/26/2011 2 Massive Data Data Analysis Insight Key to Success = Timely and Cost-Effective Analysis Starfish
Image of page 2
Hadoop MapReduce Ecosystem Popular solution to Big Data Analytics 9/26/2011 3 MapReduce Execution Engine Distributed File System Hadoop Java / C++ / R / Python Oozie Hive Pig Elastic MapReduce Jaql HBase Starfish
Image of page 3

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Practitioners of Big Data Analytics Who are the users? Data analysts, statisticians, computational scientists… Researchers, developers, testers… You! Who performs setup and tuning? The users! Usually lack expertise to tune the system 9/26/2011 4 Starfish
Image of page 4
Tuning Challenges Heavy use of programming languages for MapReduce programs (e.g., Java/python) Data loaded/accessed as opaque files Large space of tuning choices Elasticity is wonderful, but hard to achieve (Hadoop has many useful mechanisms, but policies are lacking) Terabyte-scale data cycles 9/26/2011 5 Starfish
Image of page 5

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Our goal: Provide good performance automatically Starfish: Self-tuning System 9/26/2011 6 MapReduce Execution Engine Distributed File System Hadoop Java / C++ / R / Python Oozie Hive Pig Elastic MapReduce Jaql HBase Starfish Analytics System Starfish
Image of page 6
What are the Tuning Problems? 9/26/2011 7 Job-level MapReduce configuration Workload management Data layout tuning Cluster sizing Workflow optimization J1 J2 J3 J4 Starfish
Image of page 7

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Starfish’s Core Approach to Tuning 9/26/2011 8 1) if Δ(conf. parameters) then what …? 2) if Δ(data properties) then what …? 3) if Δ(cluster properties) then what Profiler Collects concise summaries of execution What-if Engine Estimates impact of hypothetical changes on execution Optimizers Search through space of tuning choices Job Workflow Workload Data layout Cluster Starfish
Image of page 8
Starfish Architecture 9/26/2011 9 Profiler What-if Engine Workflow Optimizer Workload Optimizer Elastisizer Job Optimizer Data Manager Metadata Mgr. Intermediate Data Mgr. Data Layout & Storage Mgr. Starfish
Image of page 9

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
MapReduce Job Execution 9/26/2011 10 split 0 map out 0 reduce Two Map Waves One Reduce Wave split 2 map split 1 map split 3 map Out 1 reduce job j = < program p , data d , resources r , configuration c > Starfish
Image of page 10
What Controls MR Job Execution?
Image of page 11

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 12
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern