Hadoop is an open-source software framework for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware. It is developed by the Apache Software Foundation. This framework allows for the distributed processing of large data sets across clusters of computers using simple programming models. Below, we'll dive into the basics of Hadoop and its components.

Key Components of Hadoop

  • Hadoop Distributed File System (HDFS): A distributed file system that provides high-throughput access to application data.
  • YARN: Yet Another Resource Negotiator, a cluster management technology that manages resources in the cluster.
  • MapReduce: A programming model for processing large data sets with a parallel, distributed algorithm on large clusters of computers.

Learning Resources

  • To learn more about Hadoop, we recommend checking out our Hadoop Tutorial.

Hadoop Architecture

Conclusion

Hadoop has revolutionized the way big data is stored and processed. By understanding its core components and the principles behind them, you can leverage this powerful framework to handle large-scale data processing tasks.

Big Data Processing