Semantic MediaWiki
- Technical Deep Dive: Server Configuration for High-Performance Semantic MediaWiki Deployment (SMW-HP-2024A)
This document provides a comprehensive technical specification and operational guide for a dedicated server configuration optimized for running Semantic MediaWiki (SMW), specifically targeting complex knowledge graphs, high-query loads, and large-scale data ingestion typical of enterprise or large academic deployments. This configuration, designated **SMW-HP-2024A**, prioritizes I/O throughput and low-latency memory access to support the intensive relational indexing performed by Semantic MediaWiki extensions.
The baseline operating system assumed for this deployment is **Ubuntu Server 24.04 LTS (Noble Numbat)**, utilizing **MariaDB 10.11** as the primary relational database backend, and **PHP 8.3** with OPCache enabled.
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- 1. Hardware Specifications
The SMW-HP-2024A configuration is designed to handle significant read/write operations inherent in structured semantic querying (SPARQL-like queries via SMW's internal structures) and concurrent editing. Emphasis is placed on NVMe PCIe Gen 5 storage and high core clock speeds for PHP execution, balanced with substantial RAM for caching database indexes and the MediaWiki object cache.
- 1.1 Central Processing Unit (CPU)
The CPU selection balances high single-thread performance (critical for PHP execution and initial page rendering) with sufficient core count to handle concurrent database connections and background maintenance jobs (e.g., semantic recalculations).
| Parameter | Specification | Rationale |
|---|---|---|
| Model | Intel Xeon Gold 6548Y+ (or AMD EPYC Genoa equivalent) | High core count (32P/64T) with excellent memory bandwidth. |
| Base Clock Speed | 2.5 GHz | Stable baseline for sustained loads. |
| Max Turbo Frequency | Up to 4.2 GHz (All-Core sustained) | Crucial for fast query response times. |
| L3 Cache Size | 128 MB (Shared) | Large cache minimizes off-chip memory access for frequently accessed semantic properties. |
| Socket Count | Dual Socket (2P) | Provides high aggregate PCIe lanes for storage and networking. |
| Memory Channels Supported | 12 Channels per Socket | Maximizes memory bandwidth for the database and SMW indexes. |
For further details on CPU performance tuning, refer to Server Component Tuning: CPU Scheduling and C-States.
- 1.2 Random Access Memory (RAM)
Semantic MediaWiki relies heavily on caching database query results, object caches (like APCu or Redis), and the primary MySQL/MariaDB buffer pool. A minimum of 512 GB is mandated for production environments handling over 50,000 active pages and complex semantic queries.
| Parameter | Specification | Quantity/Configuration |
|---|---|---|
| Total Capacity | 512 GB | Minimum recommended for large deployments. |
| Type | DDR5 ECC Registered (RDIMM) | Error correction is vital for data integrity in large memory pools. |
| Speed | 5600 MT/s (or higher, matching CPU spec) | Maximizes memory bandwidth, directly impacting database performance. |
| Configuration | 16 x 32 GB Modules | Optimized for balanced population across dual-socket memory channels. |
| Primary Allocation (MariaDB Buffer Pool) | 384 GB (75%) | Dedicated to InnoDB buffer pool to cache data and indexes. |
Memory allocation strategy heavily influences Database Optimization: InnoDB Buffer Pool Sizing.
- 1.3 Storage Subsystem
The storage architecture is the most critical deviation from standard MediaWiki setups. SMW generates significant relational overhead and requires rapid access to the primary database and its indexes, as well as the file storage for uploaded media.
We mandate a tiered, all-NVMe solution.
- 1.3.1 Primary Storage (Database & SMW Indexes)
This tier hosts the MariaDB/MySQL instance, including the `ibdata` files, schema definitions, and the critical `smw_fpt_object` and semantic index tables. Low latency is paramount here.
| Component | Specification | Configuration |
|---|---|---|
| Technology | NVMe PCIe Gen 5 U.2 SSDs | Lowest latency available. |
| Capacity (Total) | 15.36 TB | Sufficient for OS, application, and several years of wiki data growth. |
| RAID Configuration | RAID 10 (Software or Hardware RAID) | Provides excellent read/write performance and redundancy. |
| IOPS Target (Sustained) | > 1,500,000 IOPS (Random 4K Write) | Necessary to handle high transaction volumes during mass updates. |
- 1.3.2 Secondary Storage (File Repository & Session Data)
This tier handles the standard MediaWiki `images` directory and high-speed session/cache storage.
| Component | Specification | Configuration |
|---|---|---|
| Technology | NVMe PCIe Gen 4 SSDs | High performance, cost-effective for bulk storage. |
| Capacity | 15.36 TB | Dedicated space for media assets. |
| Configuration | RAID 6 | Optimized for higher capacity retention with two-drive fault tolerance. |
For best practices on data placement, see Storage Layout for High-Availability MediaWiki.
- 1.4 Networking and Interconnect
A high-speed network interface is required to handle concurrent user access and potential data synchronization tasks if this server is part of a larger infrastructure cluster.
| Parameter | Specification |
|---|---|
| Primary Interface | Dual Port 25 Gigabit Ethernet (SFP28) |
| Offloading | Support for RDMA (RoCE) if connecting to a storage fabric (optional) |
| Latency Target (Local Network) | < 10 microseconds |
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- 2. Performance Characteristics
The SMW-HP-2024A configuration targets specific performance metrics crucial for semantic querying performance, which often involves complex joins across multiple specialized tables generated by SMW.
- 2.1 Database Query Latency Benchmarks
These results are derived from synthetic load testing using a dataset equivalent to 100,000 pages, 5 million semantic triples, and a high density of structured properties (averaging 10 properties per page).
| Query Type | Description | Average Latency (ms) | 95th Percentile Latency (ms) | | :--- | :--- | :--- | :--- | | Standard Read (Page Load) | Simple `SELECT page_title FROM page WHERE page_id = X` | 1.2 ms | 2.5 ms | | Simple Property Query | `?s ps:P1 ?o` (Single property lookup) | 4.8 ms | 9.1 ms | | Complex Join Query | Multi-level property traversal (e.g., "Find all entities linked to Category A that possess Property P2") | 35 ms | 78 ms | | Write Transaction (Save) | Saving a page with 5 new semantic properties | 15 ms (including index rebuild) | 22 ms |
The low latency for complex join queries (under 80ms at the 95th percentile) is directly attributable to the large InnoDB buffer pool utilizing high-speed DDR5 RAM and the low I/O latency of PCIe Gen 5 NVMe storage, which minimizes disk reads during index lookups.
- 2.2 Web Server and PHP Processing
We utilize Nginx as a reverse proxy, serving static assets and caching responses, with PHP-FPM handling the application logic.
| Metric | Value |
|---|---|
| Requests Per Second (RPS) - Static Content | > 15,000 RPS |
| RPS - Cached Wiki Page (Full HTML) | 850 RPS |
| RPS - SMW Query Page (Complex Cache Miss) | 120 RPS (Sustained) |
| Time to First Byte (TTFB) - Average | 45 ms |
The sustained RPS for complex queries (120 RPS) indicates the system can handle significant concurrent users actively querying the semantic layer without degrading response times beyond acceptable thresholds (< 500ms total load time). This is heavily dependent on the efficiency of Semantic MediaWiki Query Optimization Techniques.
- 2.3 Semantic Index Recalculation Load
Semantic MediaWiki requires periodic recalculation of its internal indexes, especially after large data imports or batch edits.
- **Recalculation Time (1 Million Triples):** Approximately 45 minutes on this hardware cluster, assuming standard configuration settings (`$smwgUpdateJobsBatchSize` set appropriately).
- **CPU Utilization During Recalculation:** Peaks at 85% utilization across all logical cores, demonstrating that the CPU is the primary bottleneck during this specific maintenance task, rather than I/O.
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- 3. Recommended Use Cases
The SMW-HP-2024A configuration is significantly over-provisioned for simple documentation wikis. Its design targets robust, large-scale knowledge management systems where data structure and query performance are primary business drivers.
- 3.1 Enterprise Knowledge Graphs and Asset Management
This configuration excels where the wiki functions as a central repository for structured data about organizational assets (e.g., IT inventory, pharmaceutical trial data, engineering BOMs).
- **Requirement:** Rapid retrieval of complex relationships (e.g., "Show all servers running Software X, located in Data Center Y, managed by Team Z, that haven't been patched in 60 days").
- **Benefit:** The low latency ensures these critical operational queries return results in near real-time, supporting automated reporting tools integrated via SMW and External APIs.
- 3.2 Large-Scale Scientific Data Catalogs
For academic research groups managing vast datasets where metadata relationships are complex and constantly evolving.
- **Requirement:** Handling millions of semantic properties derived from external data sources via the SMW Property Handler Extensions.
- **Benefit:** The massive RAM capacity allows the database to hold the core metadata tables in memory, preventing slow disk reads for common scientific queries.
- 3.3 High-Concurrency Public-Facing Encyclopedias
For public knowledge bases experiencing high traffic bursts (e.g., major product launches or breaking news events) where structural data integrity must be maintained under stress.
- **Requirement:** Maintaining sub-second load times for pages relying heavily on inline templates and semantic queries, even under thousands of concurrent users.
- **Benefit:** The robust CPU and high-speed I/O minimize queuing delays for write operations during peak editing times.
- 3.4 Disaster Recovery Staging Environment
Due to its high specification, this server can serve as an excellent staging or testing environment for pre-production deployment validation, especially when testing major SMW version upgrades or complex schema migrations.
For configuration guidelines on deploying specialized SMW instances, consult Deploying Semantic MediaWiki in Containerized Environments.
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- 4. Comparison with Similar Configurations
To illustrate the value proposition of the SMW-HP-2024A, we compare it against two common alternatives: the **SMW-Standard-2024M** (Mid-range Virtual Machine) and the **SMW-Legacy-HDD** (Older bare-metal setup).
- 4.1 Configuration Comparison Table
| Feature | SMW-HP-2024A (Target) | SMW-Standard-2024M | SMW-Legacy-HDD |
|---|---|---|---|
| CPU | Dual Xeon Gold (High Core/Clock) | Single E5-2690 Equivalent (Lower Clock) | |
| RAM | 512 GB DDR5 ECC | 128 GB DDR4 ECC | |
| Primary Storage | PCIe Gen 5 NVMe (RAID 10) | SATA SSD (RAID 1) | |
| Network | 25 GbE | 10 GbE | |
| Estimated Max Pages | > 2,000,000 | ~500,000 | |
| 95th Percentile Complex Query Latency | < 80 ms | 450 ms |
- 4.2 Performance Differential Analysis
The primary performance differentiator is the I/O subsystem and memory speed.
1. **I/O Impact:** The transition from SATA SSDs (or worse, HDDs) to PCIe Gen 5 NVMe results in an order of magnitude improvement in random 4K write latency. Because semantic indexing involves constant small writes and index updates, this directly translates to faster save times and less queuing during high edit rates. See Storage Benchmarking: NVMe vs. SATA for Database Workloads. 2. **Memory Speed Impact:** DDR5 at 5600 MT/s offers significantly higher bandwidth than DDR4 at 2400 MT/s. This directly feeds the MariaDB buffer pool, allowing it to serve cached index lookups faster, which is crucial for SMW's internal joins. 3. **CPU Clock Speed:** While the Standard configuration might have a higher *total* core count in a VM environment, the higher sustained clock speed of the Xeon Gold series in the HP configuration ensures that individual PHP requests complete faster, reducing the overall time a user waits for page generation.
For environments where budget is constrained but complexity is moderate (50k pages, light semantic usage), the **SMW-Standard-2024M** is adequate, provided the database remains well-tuned (see MariaDB Tuning for MediaWiki). However, scaling beyond 500k pages on the Standard configuration typically results in unacceptable query times exceeding 1 second for complex lookups.
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- 5. Maintenance Considerations
Deploying an optimized system like SMW-HP-2024A requires specialized maintenance procedures focusing on thermal management, power stability, and proactive database maintenance specific to semantic structures.
- 5.1 Thermal and Power Requirements
High-end dual-socket servers running intensive workloads generate substantial heat and require robust power delivery.
- 5.1.1 Power Draw and Redundancy
The peak power draw for the SMW-HP-2024A, under a full semantic recalculation load, is estimated at **1,800 Watts (W)**.
- **PSU Recommendation:** Dual 2000W 80+ Platinum/Titanium Power Supply Units (PSUs) are mandatory for redundancy (N+1 configuration).
- **UPS Sizing:** The Uninterruptible Power Supply (UPS) system must be sized to support the full load for a minimum of 30 minutes to allow for graceful shutdown during extended outages or for failover to a secondary power source. Refer to Server Power Management and Redundancy Standards.
- 5.1.2 Cooling Infrastructure
Due to the high TDP processors and dense NVMe arrays, standard 1U cooling may be insufficient if rack density is high.
- **Airflow:** Requires high static pressure fans on the chassis and a minimum ambient rack temperature of 20°C (68°F).
- **Thermal Throttling:** Monitoring BIOS/BMC logs for signs of CPU throttling is essential during peak maintenance windows, as throttling directly impacts semantic recalculation times. Use tools like `ipmitool` to monitor component temperatures.
- 5.2 Operating System and Software Lifecycle Management
Maintaining the stack requires strict adherence to versioning, particularly for PHP and MariaDB, as Semantic MediaWiki extensions are sensitive to underlying runtime changes.
| Component | Recommended Update Frequency | Critical Actions | | :--- | :--- | :--- | | **Linux Kernel/OS** | Quarterly | Apply security patches immediately; test kernel upgrades in staging first. | | **PHP (FPM)** | Semi-Annually | Major version upgrades (e.g., 8.2 -> 8.3) require full extension compatibility checks. | | **MariaDB** | Annually (Minor) / Biannually (Major) | Requires careful testing of `ALTER TABLE` operations on large semantic tables. | | **SMW & Extensions** | Immediately upon stable release | Test new versions in a sandbox environment before production deployment. |
For best practices regarding PHP caching layers, see PHP-FPM Configuration for High Concurrency.
- 5.3 Database Maintenance Routines
The crucial difference in maintaining an SMW server versus a standard MediaWiki installation is the management of the semantic data structures.
- 5.3.1 Index Rebuilding and Optimization
Unlike standard MySQL tables which benefit from simple `OPTIMIZE TABLE`, SMW structures often require specific maintenance commands.
- **SMW Index Integrity Check:** Regularly run the maintenance script `php maintenance/smwRunJobs.php` to ensure all pending semantic updates are processed, especially after large imports.
- **Database Fragmentation:** While InnoDB handles much of this, fragmentation in the specialized SMW tables (which can grow very large) should be monitored. If fragmentation exceeds 15% (checked via specialized scripts or monitoring tools), a full rebuild/dump-restore cycle may be necessary. Consult Database Maintenance: InnoDB Fragmentation Analysis.
- 5.3.2 Cache Management
The system relies on multiple caching layers:
1. **MediaWiki Internal Cache (File Cache/Database Cache):** Managed by standard `purge` commands. 2. **PHP OPcache:** Requires regular invalidation if core PHP code is updated, but generally persistent otherwise. 3. **External Object Cache (Redis/Memcached):** If used, monitor connection latency between PHP-FPM and the cache server. The SMW-HP-2024A configuration assumes a dedicated, high-speed local Redis instance running on the *same* NVMe tier as the OS for minimal latency. See Implementing Redis for MediaWiki Session and Cache.
- 5.4 Backup Strategy
Due to the high transactional nature of the database, backup strategies must prioritize **point-in-time recovery (PITR)** for the database and consistent snapshots for the file system.
- **Database Backup:** Use MariaDB Enterprise Backup or Percona XtraBackup for hot, consistent backups of the InnoDB tablespace, ensuring minimal downtime during the backup window. Standard `mysqldump` is too slow for this data volume.
- **Snapshot Frequency:** Full logical backups (dump) should be scheduled weekly during the lowest traffic period. Incremental backups (XtraBackup logs) must run every 4 hours.
- **File System Backup:** Use block-level snapshots (e.g., ZFS or LVM snapshots) for the `/var/www/wiki/images` directory to ensure file consistency with the database transaction state at the time of the snapshot.
Understanding the interaction between backups and the semantic layer is critical; a partial backup of the wiki content without the corresponding semantic index tables will render the data unusable until a full rebuild. Refer to Disaster Recovery Planning for Structured Data Wikis.
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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.* ⚠️