Hadoop is JAVA based framework useful for storing and efficiently processing large datasets. In other words, this tool is a collection of open-source utilities that facilitates the storage and processing of massive data with its enormous processing power. This technology allows multiple devices to analyze the datasets instead of using a single computer to process data.
Sub-Projects
Apache Hadoop comes with two sub-components that are as follows-
- Hadoop MapReduce- Hadoop MapReduce can be termed as a software framework useful in writing applications executed. In addition, these frameworks are capable enough to process large data in clusters of computation nodes.
- HDFS – This subproject is responsible for handling and managing the storage of Hadoop. In addition, HDFS creates many copies of data blocks and sends them to the compute nodes in a cluster.
- YARN (Yet Another Resource Negotiator)- This component is responsible for managing and monitoring the cluster nodes. Moreover, it also schedules jobs and tasks and maintains resource usage.
- Hadoop Common- This module ensures the availability of common Java libraries that are useful across all modules.
Features
Hadoop ensures flexibility and can deal with multiple types of data sets such as My SQL. XLM, JSON, etc. In addition, being open-source software, it is easy to use and provides faster data processing capability. Moreover, it uses data locality and with a minimum cost, it can move data on HDFS. One can learn this technology from Big Data Hadoop Online Training. Due to its extensive features, its useful for a vast number of organizations to analyze valuable insights. Given below are some of the features of this tool.
- Open Source- Hadoop is open-source software that makes it easy to access. In addition, one can easily get its source code online and it can be used to make necessary modifications sin Hadoop as per the company’s requirement.
- Scalable- Hadoop is a scalable cluster as it allows a vast amount of data to divide into inexpensive machines and be processed parallelly. This feature makes Hadoop better than RDBMS as they cannot scale a large amount of data.
- Ensures Fault Tolerance- As it uses inexpensive hardware that can crash, it makes sure that the data is replicated on multiple Data Nodes in a Hadoop cluster. It allows a user access to all the data from a single machine in case of any technical issues.
- Provides High Availability- Hadoop ensures the availability of data in the clusters. In addition, a user can retrieve the data from another node in case of technical faults. Moreover, it has two name nodes that are active node and passive node. The passive node is responsible for handling the work of the active node and providing the same data in case of its failure.
Cost-Effective- As this technology makes use of inexpensive hardware, it provides a cost-effective model. Moreover, it’s free to use and stores large sets of data in a cost-efficient manner.
Career Opportunities
In the past few years, Hadoop has registered itself as one of the leading names in storing and managing large datasets. It has helped in the process of real-time data analytics and fraud detection. In addition, several organizations use Hadoop for analyzing massive datasets and site visits. Above all, Big Data Analysis is useful for a large number of organizations as it helps in taking better decisions and provides valuable insights.
This is the correct time for an individual who wishes to pursue a career in this field. Moreover, various institutions provide Big Data Hadoop Training in Delhi. According to the reports by Forbes, the Hadoop market is expected to grow up to $99.31B by 2022. In addition, there are certain skill sets required for making a career in it. Linux knowledge and a programming background will ensure that you have a great start in learning. Given below are some of the domains in which a skilled professional in Hadoop can make a career.
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- Developers and Architects
- BI /ETL/DW professionals
- Senior IT Professionals
- Testing professionals
- Mainframe professionals
Conclusion
Hadoop is useful in storing and processing large datasets. It has the enormous processing power and ensures flexibility and scalability. It is a demanding technology and one can make a good career in it.