介绍了MapReduce的诞生的背景,基本原理,算法思想,以及如何用于文本挖掘,管理关系型数据,如何进行图计算及常用图计算的实现伪代码(Dijkstra’s / BFS / PageRank),最后谈到了大数据之上的存储HDFS/HBASE以及Hive和Pig。虽然不是最新的流行趋势,但是已经把大数据领域最基本的问题讲清楚了。
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
Large-Scale Data Processing with MapReduce
原文&下载https://www.slidestalk.com/s/large_scale_data_processing_with_mapreduce

相关文章:

  • 2021-06-06
  • 2022-12-23
  • 2021-06-10
  • 2022-12-23
  • 2021-09-01
  • 2021-09-27
  • 2022-12-23
  • 2021-09-05
猜你喜欢
  • 2021-05-01
  • 2022-02-15
  • 2022-12-23
  • 2021-08-31
  • 2022-12-23
  • 2021-10-07
  • 2022-12-23
相关资源
相似解决方案