'Eventual consistency' diaporamas de présentation

NoSQL and Big Data Processing Hbase , Hive and Pig, etc.

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Lecture 10: NoSQL

Lecture 10: NoSQL. Wednesday, December 1 st , 2011. Stonebraker et al., CACM 2010. RDBMS v.s . Map/Reduce. Common Wisdom: RDBMS load slowly, process fast MR load fast, process slower. Stonebraker et al., CACM 2010. Hadoop MR v.s . Parallel DBMS.

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NoSQL Data Stores Data Stores for the Cloud

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EPIDEMIC TECHNIQUES

EPIDEMIC TECHNIQUES. Ki Suh Lee. OUTLINE. Epidemic Protocol Epidemic Algorithms for Replicated Database Maintenance Astrolabe: A Robust and scalable technology for distributed system monitoring, management, and data mining . EPIDEMIC PROTOCOL.

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Database Scalabilty , Elasticity, and Autonomic Control in the Cloud

Database Scalabilty , Elasticity, and Autonomic Control in the Cloud. Divy Agrawal Department of Computer Science University of California at Santa Barbara Collaborators: Amr El Abbadi, Sudipto Das, Aaron Elmore. Outline. Infrastructure Disruption

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CS 194: Lecture 8

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Versioning, Consistency, and Agreement

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Nosql in Facebook

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Sadna Project Distributed databases: Access Control Security vs. Performance

Sadna Project Distributed databases: Access Control Security vs. Performance. Dr. Alexandra Shulman-Peleg Storage Research, Cloud Platforms Dept., IBM Haifa Research Lab. Project Overview.

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CS 194: Lecture 15

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High Throughput Computing on P2P Networks

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Coming to a world near you: massive computing power in the palm of your hands

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Ordering of events in Distributed Systems & Eventual Consistency

Ordering of events in Distributed Systems & Eventual Consistency. Jinyang Li. What is consistency?. Consistency model: A constraint on the system state observable by application operations Examples: X86 memory: Database:. write x=5. read x (should be 5). time. x:=x+1; y:=y-1.

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Dynamo

Dynamo. Highly Available Key-Value Store. Context. Core e-commerce services need scalable and reliable storage for massive amounts of data n x 100 of services n x 100,000 concurrent sessions on key services Size and scalability require a storage architecture that is highly decentralized

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Distributed Data Stores and No SQL Databases

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QoSDN QoS -assured Networks vs. SDN

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The Cloud Trade Off

The Cloud Trade Off. IBM Haifa Research Storage Systems. Fundamental Requirements form Cloud Storage Systems. The Google File System first design consideration:

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CIS 720

CIS 720. Lecture 16. Client-Centric Consistency. Intended to address the issues in eventual consistency for mobile clients. Consistent for a single client. Notation x i [ t ] is the version of x at local copy L i at time t .

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NoSQL

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