Java Serialization Library

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Hadoop Serialization System

This article is my second time reading Hadoop 0.20.2 notes, encountered many problems in the reading process, and ultimately through a variety of ways to solve most of the.   Hadoop the whole system is well designed, the source code is worth learning distributed students read, will be all notes one by one post, hope to facilitate reading Hadoop source code, less detours. 1 serialization core Technology The objectwritable in 0.20.2 version Hadoop supports the following types of data format serialization: Data type examples say ...

Processing XML files using notepad++ plug-in functionality and Java JNI Technology

Fastinfoset as a standard XML serialization means, the XML on the basis of the compression to achieve excellent support, but the lack of direct reading tools, the user caused a certain difficulty, the use of notepad++ plug-in function and Java JNI technology, combining the characteristics of both Directly to the Fastinfoset file in the notepad++ open, to solve the user two times the trouble of editing, but also fully use notepad++ to edit the XML file ...

Notes:hadoop based Open source projects

Hadoop Here's my notes about introduction and some hints for Hadoop based open source projects. Hopenhagen it ' s useful to you. Management Tool ambari:a web-based Tool for provisioning, managing, and Mon ...

"Book pick" large data development of the first knowledge of Hadoop

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 ...

Twitter Open source Summingbird: Consolidated batch processing and flow processing under near-native coding

Depending on the use scenario, large data processing is gradually evolving to two extremes-batch processing and streaming. The streaming processing pays more attention to the real-time analysis of the data, and represents the storm and S4 of the tools.   and batch processing is more focused on the long-term data mining, the typical tool is derived from the three major Google paper Hadoop. With the "bursting" of data, companies are racking their brains over large data processing, with the aim of being faster and more accurate. However, the recent new Open-source tool Summingbird has broken the rhythm of ...

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MapReduce Tutorial (1) Based on MapReduce Framework Development

MapReduce is a programming model for parallel computing of large-scale data sets (greater than 1TB) to solve the computational problems of massive data.

A word about the Hadoop family product

The use of Hadoop has been going on for some time, from the beginning of confusion, to various attempts, to the current combination of .... Slowly involved in data processing things, has been inseparable from Hadoop. The success of Hadoop in large data fields has led to its own accelerated development.   Now the Hadoop family product, has already reached 20 many. It is necessary to do a collation of their knowledge, the product and technology are strung together.   Not only can deepen the impression, but also to the future technology direction, technical selection to do the groundwork. A word product introduction: ...

Chen: Spark this year, from open source to hot

The Big data field of the 2014, Apache Spark (hereinafter referred to as Spark) is undoubtedly the most attention. Spark, from the hand of the family of Berkeley Amplab, at present by the commercial company Databricks escort. Spark has become one of ASF's most active projects since March 2014, and has received extensive support in the industry-the spark 1.2 release in December 2014 contains more than 1000 contributor contributions from 172-bit TLP ...

RPC Framework for cloud computing

In the past Client-server, RPC framework hierarchies such as CORBA and RMI did not seek because such technologies could extend a stand-alone IPC (inter-process communication, interprocess communication) to communication between multiple computers, This is very helpful for extensibility, but for a variety of reasons these RPC frameworks have not been adopted by the industry on a large scale. In the era of cloud computing, more and more machines are needed for distributed communications, although they can be easily communicated by using the HTTP protocol.

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