Introduction
With the advancement in the complexity of the data, all the organizations needed bigger and better open-source networks to critically analyze all the systems and networks. One of those profound networks is the Apache Hadoop which has come at the top due to its massive benefits.
Apache Hadoop is open-source software that can be used to solve the problems and store massive amounts of data in the cluster of computers. This software is highly used to extract something useful by harnessing a large amount of Big Data for the betterment of the entire organization.
Design Problems in the Organizations before Hadoop
Before Hadoop came into existence, there was a wide array of designing problems that come in the way of IT professionals which include:
- Fair usage of resources
- Even Job Scheduling
- Coordinating the resources
- Interrupting errors in the systems
- Transfer of the bulk of data across the network and the backplane
- Faster processing of the data
The organizations used unique hardware to perform all these functions but that hardware was hard on their pockets. Therefore, the creation of efficient software that can take care of all the designing problems was a necessity at that time.
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Design Principles of Hadoop
Later in the 20s, a software came into being which is referred to as Hadoop. It came with various features and design principles which resulted in the efficient allocation of the resources and time. It is these design principles that make Hadoop different than the rest of the software and these principles are mentioned below.
- Hadoop is Fault Tolerant
Hadoop is the kind of software that not only embraces the faults in the system but it also tolerates all the faults without damaging any system in the software. All the systems and networks manage themselves and heal on their own without any external aid. Whenever there is a fault in the system Hadoop automatically encircles around and it becomes transparent. Moreover, it speculatively takes care of all those nodes which are slower than the other and looks out for the problems that can cause this discrepancy.
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- Enhanced Scalability
Hadoop is composed of six processors and about 96 gigabytes of memory along with the other local hard drives for the storage of the data. However, whenever the amount of stored data gets increased, the storage capacity of Hadoop also increases. This is one of the most profound design principles because of why Hadoop is highly implemented in organizations. Billions of data are being produced and collected by various industries, thus; in this case, Hadoop comes out at the top.
- Move the Processing
The next unique design principle of Hadoop is that it makes the processing of the data faster than any other software or hardware. This is because Apache Hadoop doesn't separate the processing of the data from where it is stored instead this software takes this to the area where all the data is securely stored.
This can ensure a fast processing of the data due to lower bandwidth and latency. Moreover, all the queries of the applications don't have to access the remote disk to perform various functions. In this way, the complexity of the systems and networks is decreased and the performance of the systems is enhanced.
Read more: Hadoop Interview Question and Answers
- Usage of Local Hard Drives
Hadoop consists of a large number of local hard drives of about one-terabyte to four-terabyte. With the help of these drives, Apache Hadoop can carry out multiple functions such as the replication of the data. After replicating into three or more copies, this data is saved in these local drives along with various servers. By utilizing the larger hard drives, Hadoop can take care of all the problems in the system and it can resubmit all the necessary queries without any break or interruption.
Apache Hadoop also uses Just a Bunch of Disk instead of using Redundant Array of Independent Disks. That is why Hadoop can scale and perform better than any other software or hardware present in the organizations. All of these principles are the reasons behind the smooth working of Hadoop and all of your machinery.
Conclusion
Many companies have spent millions on the incorporation of efficient hardware in the system over the past few years. But with the emergence of Apache Hadoop all over the world, efficiency and enhanced performance can come at the most reasonable price. Because of the above-mentioned design principles, Hadoop has been increasingly used in several industries and organizations.
Therefore, any person who knows everything about Hadoop is in high demand in the market. That person can be you if you acquire Hadoop Certification to train yourself and enhance your abilities. In today's competitive market, these certifications are a necessity if you want to come to the top of the list.
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