PPT-Caching and caching dependencies explained

in Kentico CMS Boris Pocatko Solution Architect Kentico Software borispkenticocom 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. 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. Stuart Kent. DEV-B346. Introduction. Objectives. Understand key developer scenarios where code maps are effective. Learn how to create useful code . m. aps in context of scenarios. Learn about the specific capabilities supported by code maps. Compose at A higher level of abstraction. As applications grow in size and complexity they require some kind of high-level organization. Grouping code into packages provides two benefits. It allows us to reason about the design at a higher level of abstraction. 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. . Virtual teams . 2. Mixed Control Team Structure. Incorporates both hierarchical reporting and democratic set up. . 3. Extreme programming. XP can be seen as an attempt to improve team heedfulness and reduce the length of communication paths (the time between something being recorded and it being used). Chandra S. Amaravadi. 1. DESIGN CONCEPTS. NORMAL FORMS. REPEATING GROUPS. PARTIAL DEPENDENCIES. TRANSITIVE DEPENDENCIES. MULTI-VALUED DEPENDENCIES. 2. NORMALIZATION. unnormalized. 1st NF. 2nd NF. 3rd NF. 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. Distributed Systems. Lecture 14. Michael Freedman. 2. Linearizability. Eventual. Consistency models. Sequential. Causal. Lamport. clocks: C(a) < C(z) Conclusion: . None. Vector clocks: V(a) < V(z) Conclusion: . 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 Module: . Design: E/R Models and Normalization. Instructor: Amol Deshpande. . amol@umd.edu. Design Process; . Basics of E/R Modeling. Book Chapters (6. th. Edition). Sections 7.1, 7.2.1, 7.2.2. for . Real Estate Appraisal. Yanjie. Fu. Joint work with . Hui. . Xiong. , Yu . Zheng, . Yong . Ge. , . Zhihua. Zhou, . Zijun. Yao. Rutgers, the State University of New Jersey. Microsoft . Research, . Keith J. Bloomfield, Benjamin D. Stocker, Trevor F. Keenan, I. Colin Prentice. EGU21-BG3.7. We hope to provide an empirical demonstration that gross primary production (GPP) is predictable using a single model structure.. 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.