干货 | 实践Hadoop MapReduce 任务的性能翻倍之路
source link: https://mp.weixin.qq.com/s/pzN5YRg5CMy3E_lFRZPGwQ
Go to the source link to view the article. You can view the picture content, updated content and better typesetting reading experience. If the link is broken, please click the button below to view the snapshot at that time.
Recommend
-
16
该文章正在审核中 如有...
-
16
本文源码: GitHub·点这里 || GitEE·点这里 一、MapReduce概述 1、基本概念...
-
10
MapReduce Tutorial: IntroductionIn this MapReduce Tutorial blog, I am going to introduce you to MapReduce, which is one of the core building blocks of processing in Hadoop framework. Before moving ahead, I would sugg...
-
9
Spark vs. Hadoop MapReduce: Which Big Data Framework Is Better? Knoldus Blog Audio Reading Time: 2 minutes Are you looking for an extensive data framework to help you manage data and exp...
-
0
摘要:在排序和reducer 阶段,reduce 侧连接过程会产生巨大的网络I/O 流量,在这个阶段,相同键的值被聚集在一起。 本文分享自华为云社区《
-
7
Hadoop面试题之MapReduce 什么是MapReduce?它是一种框架或编程模型,用于使用分布式编程在计算机集群上处理大型数据集。什么是“Map”和“Reduce”?“Maps”和“Reduces”是在 HDFS 中解决查询的两个阶段。'Map'负责从输...
-
1
正文 MapReduce Hadoop中将数据切分成块存在HDFS不同的DataNode中,如果想汇总,按照常规想法就是,移动数据到统计程序:先把数据读取到一个程序中,再进行汇总。 但是HDFS存的数据量非常大时,对汇总程序所在的服务器将产生巨大压力...
-
5
This article was published as a part of the Data Science Blogathon. Introduction Apache Spark was released in 2014....
-
4
This article was published as a part of the Data Science Blogathon. Introduction Every Data Science enthusiast’s journey goes through one of the most classical dat...
-
1
在MapReduce中,为了优化性能,我们可以使用Combine方法将具有相同键值的键值对进行合并。使用Combine能够减少Map阶段和Reduce阶段需要处理的数据量,并且也能够减少shuffle阶段传输的数据量,从而减少程序执行时间,提升系统性能。 MapReduce的流程如下:
About Joyk
Aggregate valuable and interesting links.
Joyk means Joy of geeK