What is Hadoop | In 1 minute!
Hadoop is an open-source framework for distributed storage and processing of large datasets across clusters of computers using simple programming models. It's designed to scale from single servers to thousands of machines, each offering local computation and storage.
Here's a breakdown of its key components:
Hadoop Distributed File System (HDFS): HDFS is the primary storage system used by Hadoop. It breaks down large files into smaller blocks (typically 128MB or 256MB) and distributes them across nodes in a cluster. This replication ensures fault tolerance and high availability.
MapReduce: MapReduce is a programming model for processing and generating large datasets in parallel across a distributed cluster. It comprises two main functions: Map, which processes a key/value pair to generate intermediate key/value pairs, and Reduce, which merges all intermediate values associated with the same intermediate key.
YARN (Yet Another Resource Negotiator): YARN is a resource management layer that sits atop HDFS and enables different data processing engines like MapReduce, Apache Spark, Apache Flink, etc., to run and process data stored in HDFS.
Common Utilities: Hadoop also includes various utilities, libraries, and frameworks for common tasks such as data integrity, job scheduling, and cluster management.
Hadoop is widely used for processing and analyzing big data in various industries, including finance, healthcare, retail, and more. It's known for its scalability, fault tolerance, and ability to handle large volumes of data efficiently.
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►Website Link👇
Hadoop: https://hadoop.apache.org/
What is Hadoop: https://en.wikipedia.org/wiki/Apache_...
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