Features of Hadoop
Hadoop:
Hadoop is an open-source distributed computing platform that handles data processing and storage for Big Data applications operating on clustered systems. It also includes predictive analysis, data processing, and machine learning applications.
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Features of Hadoop:
Open Source:
Hadoop is an open-source framework, which indicates its source code is available free of cost for testing, correction, and reports that allow companies to change the code according to their requirements.
Cost-Effective:
As the Hadoop cluster consists of cheap commodity hardware nodes, it thus offers a cost-effective solution for saving and processing large data. Hadoop does not require any license to being an open-source product.
Faster in Data Processing:
Hadoop stores data in a distributed fashion, which allows data to be processed distributedly on a cluster of nodes. Thus it provides lightning-fast processing capability to the Hadoop framework.
Hadoop Cluster is Highly Scalable:
Hadoop cluster is scalable meaning that we can add any number of horizontally scalable nodes or increase the hardware ability of vertically scalable nodes to achieve high computing power. This ensures horizontal as well as vertical scalability of the Hadoop frame.
Feasibility:
In comparison to the traditional method, Hadoop can process unstructured data. This allows users to examine data of any format and scale.
Secures Data Reliability:
In Hadoop, data is stored efficiently on cluster machines despite system failures due to the replication of data in clusters.
The system itself offers a mechanism for ensuring data reliability using the Disk Checker, Block Scanner, Directory Scanner, and Volume Scanner. If your computer goes down or your data gets corrupted, your data is still stored securely in the cluster and can be retrieved from the other machine holding a copy of the data.
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In Conclusion, Our SkillsIon Hadoop Online Course is designed to give you an in-depth knowledge of the Big Data framework using Hadoop and Spark.
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