Java Pair

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Java Development 2.0: You can also hire ec2--to create efficient, scalable, leased infrastructure in a flexible and low-cost way

In this issue of Java Development 2.0, Andrew Glover describes how to develop and deploy for Amazon elastic Compute Cloud (EC2). Learn about the differences between EC2 and Google App Engine, and how to quickly build and run a simple EC2 with the Eclipse plug-in and the concise Groovy language ...

Java Development 2.0: Implementing REST through CouchDB and Groovy restclient

In the past few years, the innovative development of the open source world has elevated the productivity of Java™ developers to one level. Free tools, frameworks and solutions make up for once-scarce vacancies. The Apache CouchDB, which some people think is a WEB 2.0 database, is very promising. It's not difficult to master CouchDB, it's as simple as using a Web browser. This issue of Java open ...

tomp2p v3.2.10 release Peer-to-peer high-performance Junction pair data storage scheme

TOMP2P is a peer-to-peer based high-performance key-http://www.aliyun.com/zixun/aggregation/9541.html ">value data storage solution, Each pair of data has a table (disk-based or RAM) to store its value, a single value can be queried or updated, and the underlying communication framework uses Java NIO to support a large number of concurrent connections. TOMP2P is a extended DH ...

Atomsphere 3.0.2 release Atom specification Java feed Library

Atomsphere is a Java feed library that runs in the Atom 1.0 specification. It is designed to be an easy-to-use and intuitive API for http://www.aliyun.com/zixun/aggregation/7155.html "> Developer friendly." All objects in the library are serializable, invariant, and thread-safe. has been fully tested for accuracy and requires only one STAX-API implementation to run. Atomsphere 3 ....

Running Hadoop on Ubuntu Linux (Single-node Cluster)

What we want to does in this short tutorial, I'll describe the required tournaments for setting up a single-node Hadoop using the Hadoop distributed File System (HDFS) on Ubuntu Linux. Are lo ...

Data import HBase Three most commonly used methods and practice analysis

To use Hadoop, data consolidation is critical and hbase is widely used. In general, you need to transfer data from existing types of databases or data files to HBase for different scenario patterns. The common approach is to use the Put method in the HBase API, to use the HBase Bulk Load tool, and to use a custom mapreduce job. The book "HBase Administration Cookbook" has a detailed description of these three ways, by Imp ...

"Book pick" Big Data development deep HDFs

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 ...

Message Queuing based on HBase: HQueue

1. HQueue profile HQueue is a set of distributed, persistent message queues developed by hbase based on the search web crawl offline Systems team. It uses htable to store message data, HBase coprocessor to store the original keyvalue data in the message data format, and encapsulates the HBase client API for message access based on the HQueue client API. HQueue can be effectively used in the need to store time series data, as MAPR ...

Distributed parallel programming with Hadoop, part 1th

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 ...

"Graphics" distributed parallel programming with Hadoop (i)

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.

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