Distributed File Systems and Hadoop

HDFS (Hadoop Distributed File System) is a distributed file system used in Hadoop for storing large amounts of data.

MapReduce is the primary programming model used in Hadoop for processing large amounts of data.

YARN (Yet Another Resource Negotiator) is the component of Hadoop responsible for resource management.

The NameNode in HDFS is responsible for managing file system metadata, including file and directory information.

The JobTracker in Hadoop is responsible for scheduling and monitoring MapReduce jobs.

DataNodes in HDFS are responsible for storing data blocks.

TaskTrackers in Hadoop are responsible for executing MapReduce tasks.

The ResourceManager in YARN is responsible for allocating resources to applications.

NodeManagers in Hadoop are responsible for monitoring and managing the health of the cluster.

NameNode checkpoints in HDFS are used to periodically save the file system metadata to a persistent storage.

DataNodes in Hadoop are responsible for handling client requests and providing access to HDFS.

TaskTrackers in Hadoop are responsible for performing data processing tasks.

The ResourceManager in YARN is responsible for scheduling and monitoring YARN applications.

Secondary NameNodes in HDFS are used to periodically merge the file system metadata edits from the NameNode into the fsimage file.

The JobTracker in Hadoop is responsible for managing the execution of MapReduce jobs.