“大数据系统”版本间的差异
来自iCenter Wiki
(→分布式系统) |
(→MapReduce) |
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=== MapReduce=== | === MapReduce=== | ||
+ | Map/Reduce编程模型 (Abstraction)和实现框架。 | ||
+ | |||
+ | 用户只要编写 map()和 reduce()函数。 | ||
+ | |||
+ | Map/Reduce 框架能够自动将程序分配到集群上运行,并汇总运行结果 | ||
=== Hadoop === | === Hadoop === |
2017年4月12日 (三) 02:17的版本
分布式系统
- M Steen, AS Tanenbaum, Distributed systems: principles and paradigms, Prentice Hall, 2007.
MapReduce
Map/Reduce编程模型 (Abstraction)和实现框架。
用户只要编写 map()和 reduce()函数。
Map/Reduce 框架能够自动将程序分配到集群上运行,并汇总运行结果
Hadoop
- 大数据存储
- Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung. "The Google file system." ACM SIGOPS operating systems review. Vol. 37. No. 5. ACM, 2003.
- Jeffrey Dean and Sanjay Ghemawat. "MapReduce: simplified data processing on large clusters." Communications of the ACM 51.1 (2008): 107-113.
Spark
- Zaharia, Matei, et al. "Spark: cluster computing with working sets.“ Proceedings of the 2nd USENIX conference on Hot topics in cloud computing. Vol. 10. 2010.
Druid
大数据解析