Java Explained

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 ...

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Cloud computing has different meanings for different people. Business people see it as a way to save costs and achieve strategic goals; Technology experts see it as another "toy" for the cool, which developers see as an opportunity. As cloud computing continues to evolve, more companies are starting to dabble in cloud-based development environments, and cloud strategies are increasingly popular with early adopters. According to the Java Trends Survey, 34% of the respondents have already joined the cloud, 17% are planning to invest within 15 months, 19% are considering cloud-based technology, but there is no immediate implementation ...

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 ...

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1. The introduction of the Hadoop Distributed File System (HDFS) is a distributed file system designed to be used on common hardware devices. It has many similarities to existing distributed file systems, but it is quite different from these file systems. HDFS is highly fault-tolerant and is designed to be deployed on inexpensive hardware. HDFS provides high throughput for application data and applies to large dataset applications. HDFs opens up some POSIX-required interfaces that allow streaming access to file system data. HDFS was originally for AP ...

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The Microlark developed by John Cowan is an open source Microxml parser in the Java™ environment. In this article, we'll use sample code to learn Microlark. Microxml is a backward-compatible, XML-simplified version and a new specification. In part 1th of this series, part 1th: Explore the microxml of http://www.aliyun.com/zixun/aggregation/176 ...

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The most interesting place for Hadoop is the job scheduling of Hadoop, and it is necessary to have a thorough understanding of Hadoop's job scheduling before formally introducing how to build Hadoop. We may not be able to use Hadoop, but if the principle of the distributed scheduling is fluent Hadoop, you may not be able to write a mini hadoop~ when you need it: Start Map/reduce is a part for large-scale data processing ...