Posted by mod198 June - 25 - 2016 ADD COMMENTS

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Posted by jaymepobre748 May - 10 - 2016 ADD COMMENTS

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Data-Intensive Text Processing with MapReduce

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Posted by mod198 April - 2 - 2016 ADD COMMENTS

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Posted by admin March - 26 - 2016 ADD COMMENTS

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Posted by gildenshelton565 February - 27 - 2016 ADD COMMENTS

Mapreduce Design Patterns

Mapreduce Design Patterns

Brings together a collection of valuable MapReduce patterns explained in context with pitfalls and caveats clearly identified to help avoid common design mistakes when modeling big data architecture.
Title MapReduce Design Patterns
Author Miner Donald/ Shook Adam
Publisher Oreilly & Associates Inc
Publication Date 2012/12/22
Number of Pages 232
Binding Type PAPERBACK
Library of Congress bl2013000675

List Price: $ 259.00

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Posted by mod198 February - 2 - 2016 ADD COMMENTS

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Posted by gildenshelton565 January - 16 - 2016 ADD COMMENTS

What's in Store for Big Data in 2016?
Spark will kill Map Reduce, but save Hadoop. Map Reduce is quite esoteric. Its slow, batch nature and high level of complexity can make it unattractive for many enterprises. Spark, because of its speed, is much more natural, mathematical, and …
Read more on ADT Magazine

Kudu and the Ongoing Evolution of Hadoop
In other words, Cloudera has a full-fledged alternative to the Hive/MapReduce/HDFS stack with Impala/Kudu, offering new capabilities, improved storage, improved performance, and a simplified architecture. This is huge, and just another indication how …
Read more on Data Informed

Data isn't going big, but AI is
According to Foote's survey of more than 200,000 IT workers in the U.S. and Canada, pay premiums for 31 noncertified big data skills (such as Hadoop, MapReduce, Hbase, Hive, NoSQL, data mining, and base SAS) fell an average of 3 percent in over the …
Read more on Tech Page One

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Posted by jaymepobre748 December - 5 - 2015 ADD COMMENTS

MapReduce information is generally associated with Google. But does this technology have just one implementation. Of course not! Map reduce can be used in various other ways. People have this believe that Map reduce is licensed by Google so its authority is entirely in its hand, which is actually not the case. The fact is that there are many independent Map reduce projects going on all over the world, some of them are working under commercial vendors, some of them from open source activities. This arrangement is same as that of relational database where SQL or MySQL are used together, even though from two different mediums.

Since this Map reduce function is developed for handling large data sets, this idea has great significance. This idea is well understood and accepted in the industry and developers are using it quite openly for their benefit. As a programmer now you don’t need to understand the internals of parallel processing. The MapReduce information floating over the web has proved that there are large numbers of projects which are running with the creation of libraries, protocols, codes etc. Due to all these facilities large chunk of data can be easily submitted and can be easily analyzed by the computers in order to find a better solution for future. Moreover, using the MapReduce technologies you cane easily get the most effective and accurate results fairly fast. This is indeed the need of the hour. Every business needs accurate figures, proper analysis and fast results for their business development and growth.  

If you want an efficient system for managing your large data sets, read a lot on Hadoop tutorials online and learn how they can be used in your running system to bring the best results. One thing to be aware while choosing a solution for your business – Not all large volumes of data or analysis are eminently suitable on MapReduce platform. It is very important to know here that these large data sets if can be broken into smaller parallel chunks can only be analyzed. As the smaller chunks can best fit in the MapReduce system, thus you should choose a function after proper analysis. Why to do wasteful investment?

If you need any further information on MapReduce and its benefits you should read online. Here you will find the best reasons and the most appropriate solutions for all your data management and other related issues. You will come to know the situations where relational database system succeeds and where MapReduce fails. 

The auther is having 5 yars of experience in internet marketing. Know about Hadoop tutorials and MapReduce information.

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Posted by BlairMABEL25 November - 24 - 2015 ADD COMMENTS

Have you ever faced issues within your enterprise because the data is not updated or you are unable to manage it well? No matter whether you are a small business or an already established one, data management is the most important factor in increasing your enterprise’s work efficiency. There are numerous ways of managing data within any enterprise; however, some do not provide the expected results and others are extremely expensive. This is where open source technology of Hadoop comes in to the limelight.

Hadoop MapReduce is an open source software framework that is known to divide various types of large data clusters in to numerous small parts so that the management of data becomes easy. If used efficiently, this framework can help you manage the data well and can work as a boon for your enterprise. In a particular set-up where there is large amount of data along with huge network, it becomes important for an enterprise to distribute it in the best possible manner so that it can be used properly.

In such situation, Hadoop Distributed File System (HDFS) is definitely needed in order to manage the data within any enterprise well. The process usually termed as a huge-scale bath processing infrastructure that is considered to be extremely helpful for the overall set-up that has numerous computers connected to each other. While the process can easily be used on a particular machine, it definitely requires the experience of the power of a particular system. During this time, it is important for the user to use the system on any network where thousands of computers are easily available.

In any such huge network, where the distribution of overall data is required but it is a difficult task, Hadoop MapReduce technology can help because it is so well designed that it efficiently distributes the complete data across various networks. A lot of efforts are usually involved in making of this type of efficient software systems and also takes years in developing all these magical instruments that ease out the work process and efficiently bring better efficiency in various business outcomes.

Hadoop Distributed File System has the capability to store various types of vast quantities of information that can easily be processed regardless of the operating system that you are using. It also has a unique feature of Hadoop ecosystem that provides various addictive abilities to all your distributed systems completely. Get Hadoop tutorials to make the most out of Hadoop technology.

This article has been written by Alfrid Desouza. He wants to aware people about Haddop technology, it is highly advisable to go for Hadoop tutorials online in order to make the most of this technology. For more information, Read this article.

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Posted by mod198 November - 17 - 2015 ADD COMMENTS

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