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大数据和分布式计算

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  • Drizzle- Fast and Adaptable Stream Processing at Scale
  • [TODO] Pathways: Asynchronous Distributed Dataflow for ML
  • Scaling Distributed Machine Learning with the Parameter Server
  • Exoshuffle: Large-Scale Shuffle at the Application Level
  • Dataframe Systems - Theory, Architecture, and Implementation
  • [Doing] OneFlow: Redesign the Distributed Deep Learning Framework from Scratch
  • [Book] Streaming Systems
  • State Management in Apache Flink
  • Apache Flink Stream and Batch Processing in a Single Engine
  • 0. 重要会议
  • The Dataflow Model
  • Lightweight Asynchronous Snapshots for Distributed Dataflows
  • Distributed snapshots: determining global states of distributed systems
  • Bigtable: A Distributed Storage System for Structured Data
  • GFS: The Google File System
  • MapReduce: Simplified Data Processing on Large Clusters
  • A Distributed Systems Reading List
  • 1. 大数据技术栈

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  • 计算机基础
    • Great Papers In Computer Science
    • GREAT PAPERS IN COMPUTER SCIENCE: A RETROSPECTIVE
    • List of important publications in computer science
    • What Every Programmer Should Know About Memory
    • List of important publications in concurrent, parallel, and distributed computing
  • 大数据和分布式计算
    • 0. 重要会议
    • 1. 大数据技术栈
    • A Distributed Systems Reading List
    • MapReduce: Simplified Data Processing on Large Clusters
    • GFS: The Google File System
    • Bigtable: A Distributed Storage System for Structured Data
    • Distributed snapshots: determining global states of distributed systems
    • Lightweight Asynchronous Snapshots for Distributed Dataflows
    • The Dataflow Model
    • Drizzle- Fast and Adaptable Stream Processing at Scale
    • Apache Flink Stream and Batch Processing in a Single Engine
    • State Management in Apache Flink
    • [Book] Streaming Systems
    • [Doing] OneFlow: Redesign the Distributed Deep Learning Framework from Scratch
    • Dataframe Systems - Theory, Architecture, and Implementation
    • Exoshuffle: Large-Scale Shuffle at the Application Level
    • Scaling Distributed Machine Learning with the Parameter Server
    • [TODO] Pathways: Asynchronous Distributed Dataflow for ML
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