CentOS HDFS resource management policy

Hadoop Distributed File System (HDFS) Configuration and Management Guide for CentOS

This article explains the key strategies and steps for configuring and managing HDFS in a CentOS environment to help you build and maintain HDFS clusters efficiently.

HDFS resource management strategy

The core of HDFS lies in its resource management mechanism, which includes:

• Block Management: HDFS splits files into fixed-sized data blocks (default 128MB) and copies them to multiple nodes in the cluster, thereby improving data reliability and fault tolerance.
• Namespace: A namespace is a logical view of files and directories in the file system, and its metadata information is managed by NameNode.
• DataNode: DataNode is a node that actually stores data blocks and regularly reports its storage status to NameNode.
• Replica management: For data redundancy and high availability, each data block is copied by default and distributed on different DataNodes.
• Load balancing: NameNode continuously monitors the storage space and load of DataNode, dynamically adjusts the data block distribution, and ensures cluster load balancing.
• Data consistency: HDFS adopts the "write once, read multiple times" model to ensure data consistency.
• Data redundancy and fault tolerance: Through data block replication, HDFS achieves high fault tolerance, and data is still accessible even if node failures.

HDFS configuration steps

The following steps guide you to configure HDFS on CentOS:

1. Java environment configuration: Make sure the system has been correctly installed and configured with the Java running environment.
2. Hadoop environment variable settings: Edit /etc/profile file and add Hadoop-related environment variable paths.
3. HDFS configuration file configuration: The following core configuration files are correctly configured:
   • core-site.xml : Configure HDFS default file system and temporary directory path.
   • hdfs-site.xml : Configure key parameters such as data block size, number of replicas, NameNode and DataNode storage directory.
   • mapred-site.xml and yarn-site.xml : (Optional) Configure the relevant parameters of MapReduce and YARN.
4. NameNode Format: NameNode must be formatted before starting the HDFS cluster.
5. HDFS cluster startup: Use the start-dfs.sh script to start the HDFS service.

Notes:

The above steps and strategies provide a common HDFS configuration framework. In actual configuration, you may need to adjust according to cluster size, specific requirements, and security policies. In addition, important factors such as security, performance optimization, monitoring and logging need to be considered.

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