Category : Hadoop | Sub Category : Hadoop Concepts | By Prasad Bonam Last updated: 2023-07-12 05:13:46 Viewed : 356
What is Hadoop:
Hadoop is an open-source framework that provides a distributed computing system for processing and storing large datasets across clusters of commodity hardware. It was developed by the Apache Software Foundation and is widely used in big data analytics and processing.
The key components of the Hadoop ecosystem include:
Hadoop Distributed File System (HDFS): HDFS is a distributed file system designed to store and manage large amounts of data across multiple machines. It breaks data into blocks and replicates them across the cluster for fault tolerance.
MapReduce: MapReduce is a programming model and processing engine in Hadoop for distributed data processing. It allows developers to write parallelizable computations that can be executed across the nodes in a Hadoop cluster. MapReduce processes data in two stages - Map and Reduce - to perform distributed data processing and aggregation.
YARN (Yet Another Resource Negotiator): YARN is a cluster resource management system in Hadoop. It manages resources and schedules tasks across the nodes in a Hadoop cluster, enabling concurrent processing of multiple applications.
Hadoop Common: Hadoop Common provides the necessary libraries and utilities that are required by other Hadoop components. It includes common utilities, configuration files, and libraries used by Hadoop modules.
Hadoop Query Engines: Hadoop ecosystem offers various query engines to enable data processing and analytics on the stored data. Apache Hive, Apache Pig, and Apache Spark are popular tools used for querying and analyzing data in Hadoop.
Hadoop is designed to handle large-scale data processing and storage by leveraging the distributed computing capabilities of a cluster of machines. It provides fault tolerance, scalability, and the ability to process data in parallel, making it suitable for big data applications.
Hadoop is widely used in various industries for tasks such as data processing, data warehousing, log analysis, machine learning, and data analytics. It has become an essential tool in the big data ecosystem, enabling organizations to extract valuable insights from massive amounts of data.
Note that Hadoop has evolved over time, and there are different distributions and variations available, such as Apache Hadoop, Cloudera CDH, Hortonworks Data Platform (HDP), and MapR. Each distribution may have additional components or proprietary enhancements, but the core concepts of Hadoop remain the same.