Hadoop is an open source, Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment. It consists of computer clusters built from commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.
Hadoop makes it conceivable to run applications on frameworks with a large number of hardware nodes, and to deal with a huge number of terabytes of data. Its appropriated files system encourages fast information transfer rates among nods and permits the system to keep working if there should be an occurrence of a nodes failure.This approach brings down the risk of catastrophic system failure and un predictable data loss.
It supports a range of related projects that can complement and extend Hadoop’s basic capabilities.
Hadoop runs in clusters of commodity servers and typically is used to support data analysis .Several increasingly common analytics use cases map nicely to its distributed data processing and parallel computation model. Like….
Operational intelligence applications for capturing streaming data from transaction processing systems and organizational assets, monitoring performance levels, and applying predictive analytics for preemptive maintenance or process changes.
Web analytics, which are intended to help organizations understand the economics and online exercises of site visitors,reviews of Web server logs to find out the system performance issues, and recognize approaches to improve advanced marketing efforts.
Security and risk management,like running analytical models that compare transactional data to a knowledge base of fraudulent activity patterns, and also consistent cybersecurity investigation for recognizing remerging patterns of suspicious behavior.
Internet of Things applications, such as analyzing data from things like manufacturing devices, pipelines.
Sentiment analysis and brand protection.
Massive data ingestion for data collection, processing and integration scenarios such as capturing satellite images and geospatial data.
Advantages of Using Hadoop: High-performance computing framework wit low cost like Hadoop can used for different IT and business motivations for scaling up processing power or expanding data management capabilities in an organization. Let’s examine some characteristics of application..
- Ingestion and processing of large data sets, massive data volumes and streaming data.
- Ingestion and handling of large data sets , monstrous information volumes and streaming data.
- To eliminate performance impediments.
- The achieve for linear scalability on performance.
- A mixture of structured and unstructured data.
- IT cost efficiency