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Tuesday, 24 June 2014

Basic Introduction of Hadoop Map Reduce

An open source java implementation of MapReduce framework, Hadoop is introduced by Google. However, the main developer and contributor of Hadoop is said to be Yahoo, which amazed a lot of people because Yahoo, being one of the major competitors of Google released an open source version of a framework that was introduced by it competitor, Google. Nevertheless, Google has granted patent for it.
One of the major reasons why Yahoo could easily use the technology is because the Map and Reduce functions and features have been known and used in the field of functional programming for a lot of years. This is another major reason why Hadoop Map Reduce has gained a higher popularity as part of the Apache project. Today, numerous companies are using this technology as a significant component in their web architecture.
Hadoop Mapreduce
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The technology is used to simplify the process of data management within organizations. Every organization depends upon its data to function and perform better. However, it is seen that large and complicated data present within the organization increases complications and reduce work productivity. In such situations, the used of Hadoop Ecosystem helps organization manage data better by distributing large data clusters into various small parts.
It is the major and most significant framework for data analysis and processing that sometimes can be presented as an alternative to conventional relational databases. However, it is not a real database even if it does offer no SQL one called H Base as one of its major tools because it is a framework for distributing major data processes.
On the other hand, Map Reduce is a basic programming model that is introduced by Google, which is a significant part of Hadoop. It is based on the use of two major functions taken from basic fundamental programming: Map and Reduce, where Map processes a key pair into a list of intermediate key pairs and Reduce takes an intermediate key and the set of values for that particular key. In this process, the user writes both the mapper and the reducer processes. Hadoop Map framework groups together intermediary values linked with the same key to process them to the equivalent Reduce.
If you feel that by including Hadoop framework you save increase your organizational proficiency and manage data within the organization better, you can find this framework for free anywhere on the net. However, in order to excel in the field and make the best use of this framework, Hadoop training is extremely important.

Tuesday, 6 May 2014

Is Hadoop The Future Of Enterprise Data Warehousing?

While the answer to this question may not have been verified yet, what is clear is that Hadoop is proving itself in the world of enterprise data warehousing. Its presence is felt especially in handling execution of embedded advanced analytics and where unstructured content is concerned. This is actually the most dominating role of Hadoop in the production environments. It is true that the traditional Hadoop-less enterprise data warehousing is working effectively from the standpoint of architecture. However, considering the fact that the majority of cutting edge cloud analytics is taking place in Hadoop clusters, in less than one or two years, vendors will be bringing Hadoop distributed file system close to their architectural hearts. For the numerous enterprise data warehouse vendors who are yet to be fully committed to Hadoop, circumstances surrounding the increasing adoption of this open source strategy will actually force them to embrace it.

If studied objectively, it is not impossible to realize that petabyte staging cloud is just an initial footprint of Hadoop. Organizations are quickly moving towards the enterprise data warehousing as the hub for all their advanced analytics. Typically, vendors are expected to incorporate Hadoop technologies such as Hadoop distributed file system, pig, hive and the popular MapReduce in their architectures. Surprisingly, MapReduce is experiencing an impressive growth in the world of enterprise data warehousing.

This impressive growth is expected to compel enterprise data warehousing vendors to maximize their platforms of MapReduce in line with high performance support such as SAS, R, SPSS and other statistical formats and languages. There are a number of factors that are truly a clear indication that this is already happening. For instance, the recent announcement about one of the Hadoop products by EMC Green plum and the emergence of competitors with similar road maps is a clear indication that Hadoop will shape the future of enterprise data warehousing.

Hadoop for the structured data may actually be more relevant for firms that are planning to  push or are already pushing structured data to the cloud; either private or public. It is undeniable that it is actually the core platform as far as big data is concerned. Additionally, it is a core convergence focus for the purpose of enterprise application, in analytics as well as middleware vendors essentially everywhere. This may actually mean that Hadoop could be the bright future that the world of enterprise data warehousing has been waiting for the longest time.

Wednesday, 9 April 2014

Embracing SQL-MR to Handle Advanced (Analytical) Queries

The story behind the development of the SQL-mr function, as far as the world of enterprise data warehouse is concerned, is quite a funny one. Simply told, this resourceful function actually started out just as a simple expression evaluator, which is add, multiply, subtract and divide. It is from this humble beginning that this function grew into a full fledged programming language. With so much programming in the world, it is not impossible to wonder whether there aren’t enough of them yet. What is more, one cannot help but wonder what makes a new programming language more special than the earlier ones. Well, there are obviously convincing responses to your questions. 

This programming language usually runs in and as a SQL-mr function. The user passes on the program he or she wishes to run at the command line and done, it executes the code. Specifically, reading in normally record from the functions ON clause and passing then records back to your database. If you were already wondering if it can handle multi functions, then the answer is yes. What is more, it usually supports JDBC. This means that you can read from through a cursor variable, you can update, delete, insert records and even execute arbitrary SQL using a JDBC connection.

Another great thing about this function is that it bears the capacity to execute programs that were previously stored as enterprise data warehouse via the install command. This explains why it is considered an effectively kept procedure language.

There is actually a lot more of good things as far as this function is considered. Typically, SQL map reduce is a solution specifically designed for handling advanced analytical queries. Generally, the presence of more complex queries and increased data demands a more powerful enterprise data warehouse platform. A good number of database vendors have actually implemented SQL MapReduce. Better explained, it is a combination of the popular database language, SQL and a programming model developed by Google known as MapReduce.

Advantages of SQL MapReduce

  • Map reduce is usually implemented as a set of SQL table of functions. Despite being extremely sophisticated on the inside, these tables resemble the ones supported by SQL.
  • Individuals developing a report have to learn neither a new language nor a new set of statements. In any case, they just have to study the specific parameters of the MR functions.
  • Any existing reporting as well as an analytical tool that usually supports SQL can work effectively with SQL MapReduce.
  • SQL MapReduce is as storage independent and declarative as the SQL
  • With SQL MapReduce, developers have the liberty of writing their personal analytical functions and can use the language they consider comfortable to them.


Tuesday, 4 February 2014

Importance of Hadoop Training and Certification for Students


Introduction:

Before considering the importance and relevance of Hadoop Training and Certification for students, it is important and necessary to consider what constitutes Hadoop, its architecture, benefits and mode of operational usage for the benefit of users.

Hadood- an open sourced library with many benefits:

Essentially, as the scope of this paper would permit, Hadoop is an open sourced library which is readily available and downloadable from Apache Software Foundation. http://hadoop.apache.org/#Who+Uses+Hadoop%3F

One of the principal business advantages of Hadoop is that it provides for very convenient and easy distribution of data sets, possibly in petabytes, not over a single computer but over large clusters, or bunches of computers. Not only does it offer operational effectiveness but also increases performance of individual computers, while also shortening vital processing time. Besides, should any issues arise in individual computers, the other members of the cluster would be assigned to take over the tasks and duties of that affected computer, thereby reducing processing losses and time. This beneficially moves the company as a whole and helps increase performance, productivity and profitability in the medium and long term. However, the only concern that this author points out is in terms of large scale investments and operational costs that are necessary to enforce and sustain large clusters of computers, but this does even out in the long run through reduction of losses and increased productivity and optimally gains the benefits of economies of large scale in software libraries. 

Essentially this works on the architectural principle of one Master Computer, one second- in- command Back up Computer and a number of Slave computers, depending upon needs and operational viability.

Hadood architecture:

The Master computer issues orders that are processed by Slave computers and in the absence of Master Computer the Backup Computer takes over the tasks, responsibilities and practices of the Master Computer with equal apparent ease, efficacy and benefit to both user and enforcer.

Hadoop Training and certification is very important, since this one library which holds tremendous scope for a very good future, considering that businesses are now leap frogging from MB and GB to possible PB (petabytes) in future. With great increases in business development and increased activities, current and contemporary computer systems are unable to cope with increased inputs and thus there is greater need and demand for software that could perform massive computing tasks at high speed and low processing times. Besides, many major blue chip companies have not taken this library into their fold and are reaping rich dividends over time. In addition, this library is most innovative and is amenable for reform measures in future too, to keep pace and speed with changing, dynamic and perhaps overwhelming technology too.

Future of Hadood in evolving and ever changing software world:

In short, keeping in view the future needs, aspirations and demands of future technology and their impact on education and enlightenment, the Hadoop Training and Certification would be the best thing that has ever happened to many aspirant software professionals, developers and consultants over time. Since this is an open source and innovative library, it does not depend upon often-failing-servers, but itself takes up the responsibility of detecting and remedying failures at application stages, thus ensuring optimum and maximum protection, sustenance, propagation and perpetration of knowledge , exposure and skill development in the domains of software development, consultancy services and training that could go on a long, long way into the future, undeterred and unfazed by newer technological upgradations and introduction of newer software into this domains.

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