The roles and functions of the three core components of hadoop

The three core components of the Hadoop ecosystem are: HDFS (a reliable and scalable file system for storing and managing massive data); MapReduce (a distributed computing framework for processing massive data sets) ; YARN (resource management framework, responsible for managing and scheduling resources in Hadoop clusters).

The role and function of the three core components of Hadoop

Hadoop Distributed File System (HDFS), MapReduce and YARN is the three core components in the Hadoop ecosystem, and they play a vital role in data processing and management.

1. HDFS (Hadoop Distributed File System)

• Function: Reliable, scalable file system for storage and manage massive amounts of data.

• Function:

  • Split data into chunks and distribute them across multiple nodes in the cluster.
  • Provides high fault tolerance and protects data from failures through redundant storage.
  • Supports concurrent read and write access to meet high throughput requirements.

2. MapReduce

• Function: Used to process and process massive data sets Distributed computing framework.

• Function:

  • Decompose the job into two stages: Map (mapping) and Reduce (reduce).
  • Execute jobs in parallel on multiple nodes in the cluster.
  • Provides final results by sorting and aggregating intermediate results.

3. YARN (Yet Another Resource Negotiator)

• Role: Resource management framework , responsible for managing and scheduling resources in the Hadoop cluster.

• Function:

  • Allocate and manage computing, memory and storage resources for applications.
  • Provides a unified scheduling mechanism and supports various computing frameworks.
  • Allows the cluster to be dynamically scaled up and down to meet demand.

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