Hadoop Administration Guide
Hadoop Administration Guide
This guide provides a comprehensive overview of Hadoop administration, geared towards newcomers. It covers essential configuration aspects, common tasks, and troubleshooting tips. Hadoop is a powerful, open-source framework for distributed storage and processing of large datasets. Understanding its administration is crucial for maintaining a stable and performant cluster. This guide focuses on a typical on-premise deployment, though many concepts apply to cloud-based Hadoop distributions as well. See also Hadoop Distributed File System and Yet Another Resource Negotiator.
1. Core Components & Configuration Files
Hadoop consists of several key components. The most important are:
- HDFS (Hadoop Distributed File System): The storage layer.
- YARN (Yet Another Resource Negotiator): The resource management layer.
- MapReduce: The processing framework (though often replaced by other frameworks like Spark).
Configuration is primarily managed through XML files located in the `/etc/hadoop/conf` directory. Key files include:
- `core-site.xml`: Contains core Hadoop properties, such as the HDFS URI. See HDFS URI Configuration.
- `hdfs-site.xml`: Configures HDFS-specific parameters, like replication factor and block size. Consult HDFS Configuration Options.
- `yarn-site.xml`: Configures YARN, including node manager and resource manager settings. Refer to YARN Configuration Details.
- `mapred-site.xml`: Configures MapReduce, though often minimal in modern deployments. Check MapReduce Configuration.
2. Hardware Requirements
A well-configured hardware infrastructure is fundamental to Hadoop's performance. The following table outlines recommended specifications for a small to medium-sized cluster.
| Component | CPU | Memory | Storage | Network |
|---|---|---|---|---|
| NameNode | 8 Cores | 32 GB | 500 GB SSD | 10 Gbps |
| DataNode | 16 Cores | 64 GB | 4-12 TB HDD (RAID) | 10 Gbps |
| ResourceManager | 8 Cores | 32 GB | 500 GB SSD | 10 Gbps |
| NodeManager | 16 Cores | 64 GB | 1-4 TB HDD (RAID) | 10 Gbps |
These are general guidelines. Actual requirements depend heavily on data volume, processing complexity, and desired performance. Consider using Solid State Drives for frequently accessed metadata.
3. Networking Configuration
Proper network configuration is critical for inter-node communication. Ensure that all nodes can resolve each other by hostname. This is typically achieved through DNS or the `/etc/hosts` file. Firewall configurations must allow communication on the following ports:
| Port | Service | Description |
|---|---|---|
| 8088 | NameNode Web UI | Access the NameNode's web interface for monitoring. |
| 50070 | DataNode Web UI | Access DataNode web interfaces. |
| 8089 | ResourceManager Web UI | Access the ResourceManager's web interface. |
| 8042 | NodeManager Web UI | Access NodeManager web interfaces. |
| 9000 | HDFS Data Transfer | Used for data transfer between DataNodes and clients. |
| 8020 | YARN RPC | Used for communication between YARN components. |
Consider a dedicated network for Hadoop traffic to avoid congestion with other network activities. See Network Security Considerations.
4. Security Considerations
Hadoop security is a complex topic. Key considerations include:
- Kerberos Authentication: Securing access to Hadoop services using Kerberos. Refer to Kerberos Integration.
- Authorization: Controlling access to HDFS data using ACLs. See HDFS Access Control Lists.
- Encryption: Encrypting data at rest and in transit. Investigate Hadoop Encryption Methods.
- Auditing: Tracking user activity for security monitoring. Configure Hadoop Auditing.
The following table summarizes common security settings:
| Setting | Description | Default Value |
|---|---|---|
| `hadoop.security.authentication` | Specifies the authentication mechanism. | `SIMPLE` |
| `dfs.permissions.enabled` | Enables HDFS permissions. | `false` |
| `yarn.resourcemanager.kerberos.principal` | Kerberos principal for the ResourceManager. | N/A |
5. Monitoring and Troubleshooting
Regular monitoring is essential for identifying and resolving issues. Tools include:
- Hadoop Web UIs: Provide basic monitoring information for each component.
- Ambari: A comprehensive cluster management and monitoring tool. See Apache Ambari Documentation.
- Ganglia: A scalable distributed monitoring system. Learn about Ganglia Integration.
- Logs: Hadoop logs are located in the `/var/log/hadoop` directory. Analyze logs for error messages and warnings.
Common troubleshooting steps include:
- Checking disk space on DataNodes.
- Verifying network connectivity.
- Examining Hadoop logs.
- Restarting affected components.
- Consulting the Hadoop Troubleshooting Guide.
6. Further Resources
- Apache Hadoop Official Documentation
- Hadoop Best Practices
- Data Locality in Hadoop
- Hadoop Cluster Scaling
- Hadoop File Permissions
Intel-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Core i7-6700K/7700 Server | 64 GB DDR4, NVMe SSD 2 x 512 GB | CPU Benchmark: 8046 |
| Core i7-8700 Server | 64 GB DDR4, NVMe SSD 2x1 TB | CPU Benchmark: 13124 |
| Core i9-9900K Server | 128 GB DDR4, NVMe SSD 2 x 1 TB | CPU Benchmark: 49969 |
| Core i9-13900 Server (64GB) | 64 GB RAM, 2x2 TB NVMe SSD | |
| Core i9-13900 Server (128GB) | 128 GB RAM, 2x2 TB NVMe SSD | |
| Core i5-13500 Server (64GB) | 64 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Server (128GB) | 128 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Workstation | 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000 |
AMD-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Ryzen 5 3600 Server | 64 GB RAM, 2x480 GB NVMe | CPU Benchmark: 17849 |
| Ryzen 7 7700 Server | 64 GB DDR5 RAM, 2x1 TB NVMe | CPU Benchmark: 35224 |
| Ryzen 9 5950X Server | 128 GB RAM, 2x4 TB NVMe | CPU Benchmark: 46045 |
| Ryzen 9 7950X Server | 128 GB DDR5 ECC, 2x2 TB NVMe | CPU Benchmark: 63561 |
| EPYC 7502P Server (128GB/1TB) | 128 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/2TB) | 128 GB RAM, 2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/4TB) | 128 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/1TB) | 256 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/4TB) | 256 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 9454P Server | 256 GB RAM, 2x2 TB NVMe |
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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️