Distributed file systems (DFS) are a critical component of distributed architectures. They allow multiple users and applications to access and share files over a network as if they were stored locally. This section will cover the basic concepts, key components, and popular implementations of distributed file systems.

• Definition: A distributed file system is a file system that allows access to files from multiple hosts sharing via a computer network.
• Purpose: To provide a seamless and efficient way to store, retrieve, and manage data across multiple machines.

• Transparency: Users should not be aware of the distribution of files across multiple servers.
• Scalability: The system should handle an increasing number of nodes and data without performance degradation.
• Fault Tolerance: The system should continue to function even if some of the nodes fail.
• Consistency: Ensuring that all users see the same data at the same time.

• Role: Manages metadata, such as file names, directories, permissions, and locations of file chunks.
• Example: In Hadoop HDFS, the NameNode acts as the metadata server.

• Role: Store the actual file data in chunks or blocks.
• Example: In Hadoop HDFS, DataNodes store the file blocks.

• Role: Interacts with the DFS to read and write files.
• Example: A Hadoop client interacts with HDFS to perform file operations.

• Overview: HDFS is designed to store large files across multiple machines. It is highly fault-tolerant and designed to be deployed on low-cost hardware.
• Architecture: Follows a master-slave architecture with a single NameNode and multiple DataNodes.
• Use Case: Commonly used in big data applications.

• Overview: GFS is a scalable distributed file system developed by Google for large distributed data-intensive applications.
• Architecture: Similar to HDFS, with a single master and multiple chunk servers.
• Use Case: Used internally by Google for various applications.

• Overview: Ceph is a unified, distributed storage system designed for excellent performance, reliability, and scalability.
• Architecture: Uses a distributed object store (RADOS) and provides interfaces for object, block, and file storage.
• Use Case: Suitable for cloud environments and large-scale storage solutions.

1. Install Hadoop:

   sudo apt-get update
   sudo apt-get install -y openjdk-8-jdk
   wget https://downloads.apache.org/hadoop/common/hadoop-3.3.1/hadoop-3.3.1.tar.gz
   tar -xzvf hadoop-3.3.1.tar.gz
   sudo mv hadoop-3.3.1 /usr/local/hadoop
   

2. Configure Environment Variables:

   export HADOOP_HOME=/usr/local/hadoop
   export PATH=$PATH:$HADOOP_HOME/bin
   export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64
   

3. Configure HDFS:

   • Edit core-site.xml:

     <configuration>
       <property>
         <name>fs.defaultFS</name>
         <value>hdfs://localhost:9000</value>
       </property>
     </configuration>
     

   • Edit hdfs-site.xml:

     <configuration>
       <property>
         <name>dfs.replication</name>
         <value>1</value>
       </property>
       <property>
         <name>dfs.namenode.name.dir</name>
         <value>file:///usr/local/hadoop/hdfs/namenode</value>
       </property>
       <property>
         <name>dfs.datanode.data.dir</name>
         <value>file:///usr/local/hadoop/hdfs/datanode</value>
       </property>
     </configuration>
     

4. Format the NameNode:

   hdfs namenode -format
   

5. Start HDFS:

   start-dfs.sh
   

6. Verify HDFS:

   • Create a directory in HDFS:

     hdfs dfs -mkdir /user
     hdfs dfs -mkdir /user/yourusername
     

   • List the directory:

     hdfs dfs -ls /user
     

1. Objective: Perform basic file operations in HDFS.
2. Tasks:
   • Upload a file to HDFS.
   • List files in a directory.
   • Download a file from HDFS.

1. Objective: Explain the roles of NameNode and DataNode in HDFS.
2. Tasks:
   • Describe the function of the NameNode.
   • Describe the function of DataNodes.

• NameNode: Manages the metadata and namespace of the file system. It keeps track of the file locations and directory structure.
• DataNodes: Store the actual data blocks. They handle read and write requests from clients and report back to the NameNode with the status of the blocks.

In this section, we explored the fundamental concepts of distributed file systems, their key components, and some popular implementations like HDFS, GFS, and Ceph. We also provided a practical example of setting up HDFS and included exercises to reinforce the learned concepts. Understanding distributed file systems is crucial for managing and processing large-scale data efficiently in distributed architectures.