Which component of Hadoop is responsible for job scheduling andresource management?Question 2Answera. HDFSb.MapReducec.YARNd. Pig

Breakdown the Problem

To determine which component of Hadoop is responsible for job scheduling and resource management, we need to analyze the roles of each of the given components.

Relevant Concepts

1. HDFS (Hadoop Distributed File System): This is primarily used for storage and manages storing large datasets.
2. MapReduce: This is a programming model for processing large data sets with a distributed algorithm on a cluster, but it does not handle resource management.
3. YARN (Yet Another Resource Negotiator): This is a resource management layer for Hadoop that manages and schedules resources across the cluster.
4. Pig: This is a high-level platform for creating programs that run on Hadoop, but it doesn't manage resources directly.

Analysis and Detail

• HDFS focuses on data storage, not resource scheduling.
• MapReduce handles data processing, not resource management.
• YARN specifically was introduced to address the resource management and scheduling needs in Hadoop.
• Pig is an abstraction over MapReduce, useful for data processing but does not manage resources.

Verify and Summarize

Based on the functionalities of each component, YARN stands out as the responsible entity for job scheduling and resource management in the Hadoop ecosystem.

Final Answer

c. YARN