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文件名:  Resilient Distributed Datasets.pdf
资料下载链接地址: https://bbs.pinggu.org/a-2205011.html
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  1. Abstract
  2. We present Resilient Distributed Datasets (RDDs), a distributed
  3. memory abstraction that lets programmers perform
  4. in-memory computations on large clusters in a
  5. fault-tolerant manner. RDDs are motivated by two types
  6. of applications that current computing frameworks handle
  7. inefficiently: iterative algorithms and interactive data
  8. mining tools. In both cases, keeping data in memory
  9. can improve performance by an order of magnitude.
  10. To achieve fault tolerance efficiently, RDDs provide a
  11. restricted form of shared memory, based on coarsegrained
  12. transformations rather than fine-grained updates
  13. to shared state. However, we show that RDDs are expressive
  14. enough to capture a wide class of computations, including
  15. recent specialized programming models for iterative
  16. jobs, such as Pregel, and new applications that these
  17. models do not capture. We have implemented RDDs in a
  18. system called Spark, which we evaluate through a variety
  19. of user applications and benchmarks.
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