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A. storage layer
storage layer
HDFS, or Hadoop Distributed File System, is a distributed file system designed to run on commodity hardware. It is part of the Apache Hadoop framework and is used for storing and managing large datasets across multiple machines. Key features of HDFS include:
1. Fault Tolerance: HDFS replicates data across multiple nodes to ensure data availability in case of hardware failure.
2. Scalability: It can easily scale up by adding more hardware to accommodate growing data.
3. High Throughput: HDFS is optimized for large data sets, providing high throughput access to applications that process big data.
4. Data Locality: It attempts to store data on the same node where the computation is happening, which reduces network congestion and increases the speed of data processing.
5. Write-Once, Read-Many Model: HDFS is designed for applications that write data once and read it many times, making it suitable for big data processing tasks.
Overall, HDFS is crucial for the storage component in big data processing frameworks.