Big Data Architecture
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This document details the hardware specifications, performance characteristics, use cases, comparisons, and maintenance considerations for our "Big Data Architecture" server configuration. This configuration is designed for high-throughput, low-latency processing of massive datasets, commonly found in applications like data warehousing, machine learning, and real-time analytics.
1. Hardware Specifications
The Big Data Architecture server is built around a highly scalable and redundant design. Key components are selected for maximum performance and reliability. The exact specifications can be customized, but the following represents the standard configuration as of October 26, 2023. See Hardware Revision History for details on past configurations.
| Component | Specification | ||
|---|---|---|---|
| CPU | 2 x Intel Xeon Platinum 8480+ (56 cores / 112 threads per CPU, 3.2 GHz base clock, 3.8 GHz Turbo Boost) | ||
| CPU Socket | LGA 4677 | ||
| RAM | 2TB DDR5 ECC Registered 4800MHz (16 x 128GB DIMMs) – Expandable to 4TB | ||
| Motherboard | Supermicro X13DEI-N6 – Dual Socket, supporting 3rd Gen Intel Xeon Scalable processors. See Motherboard Specifications for detailed feature set. | ||
| Storage - OS & Metadata | 2 x 960GB NVMe PCIe Gen4 x4 SSD (Samsung PM1733) in RAID 1 (Mirroring) – For operating system, boot volume, and frequently accessed metadata. See RAID Configuration Guide for details. | ||
| Storage - Data Tier 1 (Hot) | 8 x 7.68TB NVMe PCIe Gen4 x4 SSD (Micron 7450 Enterprise) in RAID 0 (Striping) – High-performance tier for frequently accessed data. Total usable capacity: ~57.6TB. | ||
| Storage - Data Tier 2 (Warm) | 24 x 20TB SAS 12Gbps 7.2K RPM HDD (Seagate Exos X20) in RAID 6 (Double Parity) – Capacity tier for less frequently accessed data. Total usable capacity: ~360TB. See Storage Tiering Strategy for details. | ||
| Storage Controller | Broadcom MegaRAID SAS 9600-8i – For SAS HDD management. See Storage Controller Documentation. | NVMe RAID Controller | Adaptec SmartRAID 3240 – For NVMe SSD management. |
| Network Interface | 2 x 100GbE Mellanox ConnectX-7 (Dual Port) – For high-speed network connectivity. See Network Configuration for details. | ||
| Power Supply | 2 x 3000W 80+ Platinum Redundant Power Supplies – Provides high availability and efficient power delivery. See Power Supply Redundancy for details. | ||
| Chassis | Supermicro 4U Rackmount Chassis – Optimized for airflow and component density. See Chassis Specifications. | ||
| Cooling | High-Performance Air Cooling with redundant fans – Designed to maintain optimal operating temperatures. See Thermal Management Guide. | ||
| Remote Management | IPMI 2.0 Compliant with dedicated LAN port – For remote server management and monitoring. See IPMI Configuration. |
This configuration utilizes a hybrid storage approach, combining the speed of NVMe SSDs with the capacity and cost-effectiveness of SAS HDDs. The tiered storage system ensures that frequently accessed data is served from the fastest storage tier, while less critical data is stored on the more affordable HDD tier. Data movement between tiers is managed by Data Lifecycle Management Software.
2. Performance Characteristics
The Big Data Architecture server has been rigorously benchmarked to assess its performance across a variety of workloads. These benchmarks are conducted in a controlled environment and are subject to variation based on specific software configurations and data characteristics.
- **CPU Performance:** SPECint®2017: 1650 (estimated), SPECfp®2017: 1200 (estimated) – These scores indicate excellent performance in both integer and floating-point workloads. See CPU Benchmarking Methodology for details.
- **Storage Performance (Tier 1 - NVMe RAID 0):** Sequential Read: 14 GB/s, Sequential Write: 12 GB/s, Random Read (4KB): 1.5M IOPS, Random Write (4KB): 1.0M IOPS – These results demonstrate the high-speed capabilities of the NVMe storage tier. Tests were performed using FIO Benchmarking Tool.
- **Storage Performance (Tier 2 - SAS RAID 6):** Sequential Read: 800 MB/s, Sequential Write: 700 MB/s, Random Read (4KB): 80K IOPS, Random Write (4KB): 60K IOPS – These results reflect the capacity-oriented nature of the SAS storage tier.
- **Network Performance:** 100 Gbps throughput with low latency – Achieved using iperf3. See Network Performance Testing for details.
- **Hadoop Distributed File System (HDFS) Benchmark:** Write throughput: 80 GB/s, Read throughput: 100 GB/s (with 10 data nodes).
- **Spark Benchmark:** Processing time for a 1TB dataset: 60 seconds. See Spark Cluster Configuration for details.
- Real-World Performance:**
In a customer deployment running a large-scale fraud detection system, this configuration processed over 500 million transactions per day with an average latency of 50 milliseconds. This demonstrates the server’s ability to handle demanding real-time analytics workloads. See Case Study: Fraud Detection System for more details.
3. Recommended Use Cases
The Big Data Architecture server is ideally suited for the following applications:
- **Data Warehousing:** Storing and analyzing large volumes of historical data for business intelligence and reporting. Integration with Data Warehouse Solutions is seamless.
- **Machine Learning:** Training and deploying complex machine learning models, requiring significant computational resources and storage capacity. Compatible with popular frameworks like TensorFlow and PyTorch. See Machine Learning Infrastructure.
- **Real-Time Analytics:** Processing and analyzing streaming data in real-time, enabling immediate insights and decision-making. Suitable for applications like fraud detection, anomaly detection, and personalized recommendations. See Stream Processing Architecture.
- **Hadoop Cluster Node:** Serving as a high-performance node in a Hadoop cluster for distributed data processing.
- **NoSQL Database:** Hosting large-scale NoSQL databases like Cassandra, MongoDB, and HBase.
- **Genomic Sequencing:** Analyzing large genomic datasets, requiring high throughput and storage capacity.
- **Financial Modeling:** Running complex financial models and simulations.
4. Comparison with Similar Configurations
The Big Data Architecture server competes with other high-performance server configurations designed for big data workloads. The following table compares this configuration with two common alternatives:
| Feature | Big Data Architecture | High-Memory Configuration | All-Flash Configuration |
|---|---|---|---|
| CPU | 2 x Intel Xeon Platinum 8480+ | 2 x Intel Xeon Gold 6348 | 2 x Intel Xeon Platinum 8380 |
| RAM | 2TB DDR5 | 4TB DDR4 | 1TB DDR4 |
| Storage - Tier 1 | 57.6TB NVMe RAID 0 | 19.2TB NVMe RAID 0 | 38.4TB NVMe RAID 0 |
| Storage - Tier 2 | 360TB SAS RAID 6 | 720TB SAS RAID 6 | None |
| Network | 100GbE | 25GbE | 100GbE |
| Cost (Estimated) | $65,000 | $40,000 | $80,000 |
| Best For | Balanced performance and capacity | Memory-intensive applications | Highest performance, limited capacity |
- **High-Memory Configuration:** Prioritizes RAM capacity over storage performance. Suitable for applications that require large in-memory datasets, such as in-memory databases and complex simulations. Lower cost but slower storage access.
- **All-Flash Configuration:** Utilizes exclusively NVMe SSDs for both storage tiers. Offers the highest performance but at a significantly higher cost and lower overall capacity. Ideal for applications requiring extremely low latency and high IOPS. See Storage Technology Comparison for a detailed analysis.
5. Maintenance Considerations
Maintaining the Big Data Architecture server requires careful attention to cooling, power, and component monitoring.
- **Cooling:** The server generates a significant amount of heat. Ensure adequate airflow in the data center and regularly inspect the cooling fans for proper operation. Consider implementing Data Center Cooling Best Practices. Ambient operating temperature should be maintained between 18°C and 27°C.
- **Power Requirements:** The server requires significant power (approximately 6000W). Ensure that the data center power infrastructure can support this load. Redundant power supplies provide failover protection, but proper power distribution is crucial. See Data Center Power Management.
- **Storage Monitoring:** Regularly monitor the health of the storage devices using SMART attributes and RAID controller logs. Proactive monitoring can help identify and prevent data loss. Utilize Storage Monitoring Tools.
- **Software Updates:** Keep the operating system, firmware, and drivers up to date to ensure optimal performance and security. Follow Software Update Procedures.
- **Component Replacement:** Establish a hot-spare program for critical components like power supplies, fans, and storage devices. This minimizes downtime in the event of a failure. See Hot-Spare Configuration.
- **Regular Diagnostics:** Run periodic diagnostic tests to verify the health of the server’s hardware. Utilize Server Diagnostic Tools.
- **Data Backup and Recovery:** Implement a robust data backup and recovery plan to protect against data loss. See Data Backup Strategy.
This configuration is designed for high availability, but regular maintenance is essential to ensure continued reliable operation. Consult our Support Documentation for further assistance. ```
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.* ⚠️