PPT-Caching for Data Analysis

Author : marina-yarberry | Published Date : 2019-12-11

Caching for Data Analysis Ken Birman Theo Gkountouvas Data Analysis Data processing is growing very fast compared to the hardware acceleration Volume Complexity

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Caching for Data Analysis: Transcript

Caching for Data Analysis Ken Birman Theo Gkountouvas Data Analysis Data processing is growing very fast compared to the hardware acceleration Volume Complexity Spark RDDs Spark uses Resilient Distributed Datasets RDDs as a core structure. in Kentico CMS. Boris . Pocatko. Solution Architect. Kentico Software. borisp@kentico.com. Agenda. Problem. Describing different caching mechanisms. Demo for cache dependencies. API caching and additional info. How It Works and When You Should Use It . Shy Cohen. Principal, . Shy Cohen Consulting. AAP314. What Gurus Need to Know. What’s a cache and what it does. Core and advanced concepts. Caching on premises and in Windows Azure. Utilizing AppFabric Caching Services On-. Premise. and Beyond to Optimize Performance. About Me. Overview. of . Caching. Server . AppFabric. . Caching. Architecture. Demo. : Server . AppFabric. . Ilija Vukotic. ADC TIM - Chicago. October 28, 2014. Caching – why and where?. Straight Tier3 . Most of the disk space is devoted to input data. The input data is almost always from downloaded from the grid. Telerik Software Academy. http://academy.telerik.com. . ASP.NET MVC. Table of Contents. Why do we need caching?. ASP.NET Output Caching. OutputCache. page directive. Cache profiles. Post-cache substitution. James Kovacs. JamesKovacs.com. jkovacs@post.harvard.edu. Performance. Application A. 40 Requests per second. Application B. 20 Requests per second. Scalability. Is 20 Requests per Second Enough?. 20 requests per second. Victor Zakhary, . Divyakant. Agrawal, Amr El . Abbadi. 1. The old problem of Caching. Disk. RAM. L. 2. L. 1. Larger. Slower. Cheaper. Smaller. Faster. Expensive. 2. The old problem of Caching. Smaller. and When You Should Use It . Jon Flanders. Senior Consultant. MCW Technologies. MID302. Agenda. Why Caching?. What is AppFabric Cache?. On-Premise and in Azure. Demo, demo, demo. Typical Web Architecture. www.chriswoodruff.com. www.twitter.com/cwoodruff. Chris Woodruff. Developer Advocate at JetBrains. www.linkedin.com/in/chriswoodruff. What do you and . I. do wrong?. Calling Data Access functionality (EF Core) from Controllers. Name. Title. Microsoft Corporation. Presentation Summary. Version: Jul 2010. Feedback: . ryandunn@microsoft.com. . Technical Level: 300/400. Intended Audience: Developers, Architects. Intended Time: 60 minutes. Caching at the Web Scale Victor Zakhary, Divyakant Agrawal, Amr El Abbadi Full slide deck: https://goo.gl/1VYGW3 1 The old problem of Caching Disk RAM L 2 L 1 Larger Slower Cheaper Smaller Faster . 01. BACKGROUND. PROBLEM & TERMINOLOGY & Motives & OBJECTIVES. Linux Virtual File System (VFS). Linux Virtual File System (VFS) – . cont. ’. The Linux Virtual File System (VFS) . (also known as the Virtual Filesystem Switch) is the software layer in the kernel that provides the filesystem interface to user space programs. . &. Caching. Noah Mendelsohn. Tufts University. Email: . noah@cs.tufts.edu. Web: http://www.cs.tufts.edu/~noah. COMP 150-IDS: Internet Scale Distributed Systems . (Spring 2015). 2. Goals. Explore some general principles of performance,... S. Narravula, P. Balaji, K. Vaidyanathan, . H.-W. Jin and D. K. Panda. The Ohio State University. Presentation Outline. Introduction/Motivation. Design and Implementation. Experimental Results. Conclusions.

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