what is hadoop 

Apache Hadoop is an open-source software framework for storing and processing large volumes of data on distributed clusters of servers. It is designed to scale up from a single server to thousands of machines, and to handle a wide variety of data types and workloads.

Hadoop is composed of four core components:

Hadoop Distributed File System (HDFS): A distributed file system that enables storing very large files across a large number of servers.

MapReduce: A programming model and execution environment for processing large datasets in parallel on a cluster of servers.

YARN (Yet Another Resource Negotiator): A resource management platform that enables scheduling of applications running on a Hadoop cluster.

Common Utilities: A set of utilities for working with HDFS, MapReduce, and YARN, including a command-line interface and a programming API.

hadoop cluster types

There are two main types of Hadoop clusters:

Standalone (Single-Node) Cluster: This is the most basic type of Hadoop cluster, consisting of a single node (server) running both the Hadoop Distributed File System (HDFS) and MapReduce. Standalone clusters are typically used for testing and development purposes, as they are not suitable for production environments due to their limited scalability and reliability.

Multi-Node Cluster: This type of Hadoop cluster consists of multiple nodes (servers) running HDFS and MapReduce. Multi-node clusters are more scalable and reliable than standalone clusters, and are suitable for production environments. There are two main types of multi-node clusters:

Pseudo-distributed cluster: This type of cluster is used for testing and development, and consists of multiple nodes running on a single physical machine.

Fully-distributed cluster: This type of cluster consists of multiple nodes running on multiple physical machines, and is used for production environments. Fully-distributed clusters can be further divided into two types:

Small-scale cluster: This type of cluster consists of a few dozen nodes, and is suitable for small- to medium-sized organizations.

Large-scale cluster: This type of cluster consists of hundreds or thousands of nodes, and is suitable for large organizations with very large datasets.

Hadoop is often used for big data applications such as data processing, data warehousing, and log processing. It is also used for machine learning, scientific simulation, and other data-intensive applications.