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    TOP BIG DATA PAPERS

    |  Oct 16,2018
    Following are list of papers responsible to change BIG DATA trends:
    • MapReduce: Simplified Data Processing on Large Clusters
    • The Google File System
    • Bigtable: A Distributed Storage System for Structured Data
    • Dynamo: Amazon’s Highly Available Key-value Store
    • The Chubby lock service for loosely-coupled distributed systems
    • Chukwa: A large-scale monitoring system
    • Cassandra – A Decentralized Structured Storage System
    • HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads
    • S4: Distributed Stream Computing Platform.
    • Dremel: Interactive Analysis of Web-Scale Datasets
    • Large-scale Incremental Processing Using Distributed Transactions and Notifications
    • Pregel: A System for Large-Scale Graph Processing
    • Spanner: Google’s Globally-Distributed Database
    • Shark: Fast Data Analysis Using Coarse-grained Distributed Memory
    • A Few Useful Things to Know about Machine Learning
    • Random Forests
    • A Relational Model of Data for Large Shared Data Banks
    • Map-Reduce for Machine Learning on Multicore
    • Megastore: Providing Scalable, Highly Available Storage for Interactive Services
    • Finding a needle in Haystack: Facebook’s photo storage
    • Spark: Cluster Computing with Working Sets
    • The Unified Logging Infrastructure for Data Analytics at Twitter
    • F1: A Distributed SQL Database That Scales
    • MLbase: A Distributed Machine-learning System
    • The Promise and Peril of Big Data
    • TDWI Checklist Report: Big Data Analytics

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