[Guest Post] The Use Of Hadoop Technology In Handling Huge Databases

Heard a lot about the Hadoop technology, and wonder where you may use this in your business or organization? First get to know what is Hadoop. This is a technology, which deals with the handling of massive amounts of data. Massive amounts of data are stored in clusters of hardware which are used as a commodity. The technology allows storage of data in massive amounts which is beyond your imagination, and has the vast efficiency to process the data at unbelievable speed, and thus can parallelly handle many data, process them, and execute many tasks.

How the need for significant data processing brought Hadoop?

With the evolvement in search engine search procedure and with the big boom the World Wide Web saw from the 1900s to the present time, many things had to be changed with the demand of the era. The human returned searches in 1900 soon got replaced by web crawlers in the 2000s. And gradually by 2008 Hadoop got configured by Yahoo, and in the current day, nonprofit open source software development platform Apache Software Foundation brought Hadoop.

What is special about Hadoop

Hadoop is a system and technology, designed to deal with the enormous volume of data within a brief time, and process the data in such organized ways to bring on multiple parallel executions and processing on the data, and convert any cluster of unstructured data into the most sophisticated and usable form of structured data.

The specialty of the system lies in its open source platform, its ability for handling really huge volume of varied, complex, different types of data in any form, and process things in such efficient way, that no global commodity and hardware system is bare without this technology in the day to day execution and processing of data.

Storage and processing of varied, mixed data at the superfast speed

Hadoop is made special by its abilities. This technology can practically accept data in any form, any complexity, any type, and can process those by putting them in a systematic order. And it does this all with the fastest execution time.

Higher computing speed

Hadoop has a computing model which is distributed for processing big chunks of data at the fastest rate. With the use of more nodes for computing the data processing speed increases, which is another excellent specialty of the system.

Tolerance to failures and faults

Another specialty of Hadoop is that the data stays stored in copies across all nodes of the system, thereby making the system protected against errors and failures. If one or more nodes of the system see downtime, the others function unaffected to keep on processing data.

No need to sort unstructured data compulsorily

Hadoop systems come with the advantage of storing unstructured data in any form for later use. In traditional RDBMS the data needs to be stored in a sorted, organized form for using later. But this is not a mandate in Hadoop. Here data in any type and format can be stored as raw data, and can later be sorted and processed.

Free and expandable

Being open source, the system is free to use through the use of commodity hardware, which is one significant advantage, thereby making the use of the technology super economical. Also, the system can be grown to handle more data. This can be done merely through the addition of more nodes.

Hadoop comes with a few challenges

Simple requests for problem solving and information which can be distributed amongst different nodes can be made great with Hadoop MapReduce programming. However, if you are after analytical data processing with interactivity and iterative skills, then it may lag behind. During the execution of MapReduce programming, multiple files do get produced which reduces efficiency for analytical problem-solving.

Also, Java programmers who can use their pro skills to use MapReduce productively are not those much available. And this is one big reason that people dependent on Hadoop are keener on hiring remote database administrative teams for this job. Services like RemoteDBA.com are especially suitable for handling MapReduce in an advanced way and find solutions to all customer problems with their experienced Java programmers.

The requirement for remote DBA services

Hadoop is the growing technology which still needs good programmers to use the system with full potent. And not an average programmer may have all the abilities to make use of the technology at its best. But when you hire Hadoop based database management services on the remote, by contacting a database admin team, which works from a distance, and yet provides full management solutions, then you get sorted completely.

Remote DBA teams work day and night through shuffling duties to give you a complete database management solution using the technology youprefer. And since it’s not that easy to get advanced experts of Hadoop at full-time employment in a budget, you may use the remote DBA services at ease. You can get their service from your place without having to move an inch. And you also get the services at competitive rates.

How to overcome Hadoop challenges

The challenges in Hadoop programming like data standardization and quality control tools and the lack of fragmented data security can be best overcome by expert programmers. Looking at the positive sides of Hadoop as a potent RDBMS with exceptional qualities, these small challenges can be overcome easily with the use of an expert admin team taking care of the nodes and systems.

Finally

Hadoop has opened the gateway for handling vast chunks of data, previously deemed unmanageable. Data increasing in volume each day in all sizes and types, in all complex structured and unstructured formats can be given shape, stored, structured, and processed efficiently. And all these take minimal time using this open source technology which has proven economical for the organizations and all private and government concerns. Therefore, if you are concerned about using Hadoop, you can be sure that this is the best choice for handling complex to simple, all formats of various data, in any volume, at the fastest rate in an inexpensive way.