Merge Algorithm Java

As we all know, Java in the processing of data is relatively large, loading into memory will inevitably lead to memory overflow, while in some http://www.aliyun.com/zixun/aggregation/14345.html "> 　　Data processing we have to deal with massive data, in doing data processing, our common means is decomposition, compression, parallel, temporary files and other methods; For example, we want to export data from a database, no matter what the database, to a file, usually Excel or ...

Multithreading is the problem that programmers often face in the interview, the level of mastery and understanding of multithreading concept is often used to measure a person's programming strength. Yes, ordinary multithreading is not easy, then when multithreading encounter "elephants" will produce what kind of sparks? 　　Here we share the Java thread Pool management and distributed Hadoop scheduling framework with 严澜, the Shanghai Creative Technology director. Usually the development of the thread is a thing, such as Tomcat in the servlet is the threads, no thread how we provide more ...

Usually the development of the thread is a thing, such as Tomcat is a servlet in the threads, there is no thread how do we provide multi-user access? But many developers who have just started to touch threads have suffered a lot. 　　How to do a set of simple threading Development Mode framework for everyone from the single thread development into multithreaded development, this is really a relatively difficult project. What is the specific thread? First look at what the process is, the process is a system executed a program, this program can use memory, processor, file system and other related resources ...

This is the second of the Hadoop Best Practice series, and the last one is "10 best practices for Hadoop administrators." Mapruduce development is slightly more complicated for most programmers, and running a wordcount (the Hello Word program in Hadoop) is not only familiar with the Mapruduce model, but also the Linux commands (though there are Cygwin, But it's still a hassle to run mapruduce under windows ...

Hadoop is an open source distributed parallel programming framework that realizes the MapReduce computing model, with the help of Hadoop, programmers can easily write distributed parallel program, run it on computer cluster, and complete the computation of massive data. This paper will introduce the basic concepts of MapReduce computing model, distributed parallel computing, and the installation and deployment of Hadoop and its basic operation methods. Introduction to Hadoop Hadoop is an open-source, distributed, parallel programming framework that can run on large clusters.

Hadoop is an open source distributed parallel programming framework that realizes the MapReduce computing model, with the help of Hadoop, programmers can easily write distributed parallel program, run it on computer cluster, and complete the computation of massive data. This paper will introduce the basic concepts of MapReduce computing model, distributed parallel computing, and the installation and deployment of Hadoop and its basic operation methods. Introduction to Hadoop Hadoop is an open-source, distributed, parallel programming framework that can be run on a large scale cluster by ...

Translation: Esri Lucas The first paper on the Spark framework published by Matei, from the University of California, AMP Lab, is limited to my English proficiency, so there must be a lot of mistakes in translation, please find the wrong direct contact with me, thanks. (in parentheses, the italic part is my own interpretation) Summary: MapReduce and its various variants, conducted on a commercial cluster on a large scale ...

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...

Aiming at the problem of low storage efficiency of small and medium files in cloud storage system based on HDFS, the paper designs a scheme of small and medium file in cloud storage System with sequential file technology. Using multidimensional attribute decision theory, the scheme by combining the indexes of reading file time, merging file time and saving memory space, we get the best way of merging small files, and can achieve the balance between the time consumed and the memory space saved; The system load forecasting algorithm based on AHP is designed to predict the system load. To achieve the goal of load balancing, the use of sequential file technology to merge small files. Experimental results show that ...

The 2013 will soon be over, summarizing the major changes that have taken place in the year hbase. The most influential event is the release of HBase 0.96, which has been released in a modular format and provides many of the most compelling features. 　　These characteristics are mostly in yahoo!/facebook/Taobao/millet and other companies within the cluster run a long time, can be considered more stable available. 1. Compaction Optimization HBase compaction is a long-standing inquiry ...