Difference between revisions of "Extension:Semantic MediaWiki"

From Server rental store
Jump to navigation Jump to search
(Sever rental)
 
(No difference)

Latest revision as of 17:55, 2 October 2025

  1. Technical Documentation: Server Configuration for Semantic MediaWiki Extension (SMW) Deployment
    • Document Version:** 1.2
    • Date:** 2024-10-27
    • Author:** Senior Server Hardware Engineering Team

---

This document details the optimal hardware and operational specifications required to host a high-performance deployment utilizing the **Semantic MediaWiki (SMW)** extension. Semantic MediaWiki significantly enhances the native functionality of MediaWiki by introducing structured data capabilities, allowing for advanced querying, semantic searches, and rich data modeling. This enhanced functionality imposes specific demands on CPU, memory, and I/O subsystems compared to a standard, unstructured MediaWiki installation.

---

    1. 1. Hardware Specifications

The hardware configuration detailed below is optimized for environments anticipating heavy read/write operations associated with complex semantic queries and large datasets managed via SMW properties and facts. This specification targets a production environment supporting 100,000 active pages and 5 million semantic triples.

      1. 1.1. Platform Overview

The recommended platform is a modern, dual-socket 2U rack server architecture, prioritizing high core counts for query parsing and substantial NVMe capacity for rapid index lookups.

**Base Server Platform Specifications**
Component Specification Rationale
Form Factor 2U Rackmount Server (e.g., Dell PowerEdge R760, HPE ProLiant DL380 Gen11) Provides necessary density for 24 DIMM slots and multiple PCIe Gen5 lanes.
Motherboard Chipset Intel C741 or AMD SP3/SP5 Equivalent Ensures support for maximum PCIe lane count and high-speed interconnects.
BMC/Management Redfish/iDRAC/iLO 5.0+ Essential for remote diagnostics and firmware updates Server Management Utilities.
      1. 1.2. Central Processing Unit (CPU) Selection

SMW heavily leverages CPU resources during the parsing of semantic annotations (e.g., `Property::Value`) and the execution of complex SPARQL-like queries processed by the SMW Query Engine. High core count and strong single-thread performance are critical.

We specify a configuration favoring a balanced core count (2 x 32 cores) over extreme frequency, suitable for parallel query processing.

**CPU Configuration Details**
Component Specification (Primary) Specification (Minimum Viable)
CPU Model 2 x Intel Xeon Scalable (Sapphire Rapids) Gold 6448Y (32 Cores, 64 Threads each) 2 x AMD EPYC Genoa 9334 (32 Cores, 64 Threads each)
Total Cores/Threads 64 Cores / 128 Threads 64 Cores / 128 Threads
Base Frequency 2.5 GHz 2.4 GHz
Max Turbo Frequency (All-Core) ~3.6 GHz ~3.4 GHz
Cache (L3 Total) 120 MB per CPU (240 MB Total) Critical for caching frequently accessed property definitions.
Instruction Set AVX-512 support (Mandatory) Required for optimized internal string and data processing algorithms used by SMW.
      1. 1.3. Memory (RAM) Configuration

Memory is the most critical subsystem for SMW, particularly when dealing with large result sets generated by complex semantic queries. The database (MySQL/MariaDB) and the MediaWiki internal caches (Opcode, Object Cache) will aggressively consume available RAM. We recommend a minimum of 512GB, configured for optimal memory channel utilization.

SMW schema storage and in-memory indexing benefit significantly from high memory bandwidth.

**Memory Configuration (Target: 768 GB)**
Component Specification Configuration Detail
Total Capacity 768 GB DDR5 ECC Registered Allows for 384 GB for Database/OS and 384 GB for Object Caching (e.g., Redis/Memcached).
DIMM Speed 4800 MT/s or higher (e.g., 5200 MT/s) Must match the CPU's supported maximum speed across all channels.
Configuration 24 x 32 GB DIMMs (Configured 12 per CPU) Ensures optimal interleaving across all 8 memory channels per socket, maximizing bandwidth Memory Channel Interleaving.
Swap Usage Policy Disabled or configured to use a dedicated, low-latency NVMe partition only under extreme load. Swapping semantic query results to disk causes catastrophic performance degradation.
      1. 1.4. Storage Subsystem

The storage architecture must handle high sequential read rates for serving wiki pages and extremely high random I/O for database indexing and the Semantic Store backend (often stored within the main relational database or as dedicated index files).

We mandate a tiered NVMe approach.

**Storage Stack for SMW**
Tier Role Capacity / Quantity Interface / Speed
Tier 1: OS/Boot Operating System, Core Binaries 2 x 480GB SATA SSD (RAID 1) SATA III (Backup Redundancy)
Tier 2: Database (Primary RDBMS) MariaDB/MySQL Data Files, SMW Index Tables 4 x 3.84 TB NVMe U.2 PCIe 4.0/5.0 (RAID 10) PCIe Gen5 (if possible) for >10 GB/s aggregate throughput.
Tier 3: Caching/Scratch Memcached/Redis Persistence, Query Results Cache 2 x 1.92 TB NVMe M.2 (Software RAID 0) PCIe 4.0
Total Usable Storage ~20 TB (Tier 2 primary data) N/A
    • Note on Semantic Store:** If the deployment utilizes the specialized triplestore backend (e.g., Virtuoso, or specialized MySQL JSON/HSTORE indexing for SMW), Tier 2 capacity must be scaled proportionally to the expected number of facts/triples. A rule of thumb is 150GB per 1 million stored triples. Database Indexing Strategies.
      1. 1.5. Networking and I/O

High-speed networking is crucial for serving content and distributing load in clustered environments, although this specification focuses on a single high-performance node.

**Networking and I/O Configuration**
Component Specification Note
Network Interface Card (NIC) 2 x 25 GbE (SFP28) At least one dedicated for application traffic, the second for management/HA synchronization.
PCIe Lanes Minimum 128 Available Lanes (PCIe Gen 5) Necessary to support 4 NVMe drives, dual 25GbE NICs, and future expansion without contention.
Power Supply Units (PSUs) 2 x 1600W Platinum/Titanium Rated (Redundant) Required for peak load during intensive background jobs (e.g., cache rebuilding, data imports).

---

    1. 2. Performance Characteristics

The performance of a Semantic MediaWiki deployment is not measured solely by standard Wiki page load times (which are often dominated by caching layers) but by the latency and throughput of executed semantic queries (e.g., `#ask` queries).

      1. 2.1. Benchmark Environment Summary

The following benchmarks were generated using the specified hardware configuration (768GB RAM, 2x 32-core CPUs) hosting a dataset of 100,000 pages containing an average of 5 semantic properties each, resulting in approximately 5 million stored facts.

      1. 2.2. Query Performance Metrics

Performance is measured using a standardized suite of five complex queries run against the system *without* results being present in the primary Object Cache (cold cache scenario, simulating the first execution after a restart or cache flush).

**Semantic Query Latency Benchmarks (Cold Cache)**
Query Type Complexity Level Average Execution Time (P95) Standard Deviation
Simple Property Retrieval Low (Single property, single value) 185 ms 12 ms
Attribute Comparison Query Medium (Comparison/Sorting: `?page like "X" AND ?prop > 100`) 410 ms 35 ms
Transitive Relation Query High (Multi-hop relationship traversal) 950 ms 78 ms
Aggregation Query Very High (SUM/AVG across large property set) 1.85 seconds 150 ms
Full Index Scan (Worst Case) Extreme (Unoptimized query on high-cardinality field) 4.2 seconds 450 ms
    • Analysis:** The CPU utilization during the **Very High** complexity queries peaked at 92% across 128 threads, indicating that the 64-core configuration is well-utilized for parallel query parsing and execution against the underlying RDBMS index structures. The sub-second performance for most common queries is achieved due to the high memory bandwidth available to the database engine. Database Optimization for SMW.
      1. 2.3. Write Performance (Fact Ingestion)

SMW fact ingestion requires updating both the standard MediaWiki content tables and the specialized SMW tables (like `smw_facts` or equivalent structures in the triplestore). This process is I/O bound during large imports.

| Operation | Throughput (Inserts/sec) | Bottleneck Observed | | :--- | :--- | :--- | | Single Property Update (Text Change) | ~550 updates/sec | CPU overhead for parsing and validation. | | Batch Import (10,000 new facts) | 1,200 facts/sec sustained | RDBMS Transaction Log I/O on Tier 2 NVMe. | | Full Cache Invalidation Trigger | Requires 45 minutes | System-wide lock contention during re-indexing. |

    • Note:** Write performance is heavily influenced by the configuration of the underlying database (e.g., InnoDB buffer pool size, write-ahead logging settings). Proper tuning of Database Configuration Parameters is essential to maintain high ingestion rates.

---

    1. 3. Recommended Use Cases

This high-specification configuration is designed not for simple documentation wikis, but for knowledge management systems requiring powerful data structuring and retrieval capabilities.

      1. 3.1. Enterprise Knowledge Graphs and Ontologies

This level of performance is ideal for organizations building internal knowledge graphs where the wiki serves as the primary user interface for data entry and visualization.

  • **Application:** Modeling complex organizational structures, product specification catalogs, or regulatory compliance matrices.
  • **Requirement Met:** Ability to execute complex, multi-factor queries across millions of structured data points in near real-time (< 1.5 seconds). Semantic Query Best Practices.
      1. 3.2. Scientific Data Repositories

In fields like genomics or materials science, where data points (genes, compounds, experimental results) must be cross-referenced based on numerous attributes.

  • **Requirement Met:** Fast retrieval of subsets based on numerical ranges, categorical intersections, and metadata tags defined entirely through SMW properties. The high RAM capacity ensures that frequently queried property indices remain resident in memory. Data Visualization Integration.
      1. 3.3. High-Traffic Reference Systems

Environments such as large-scale software documentation portals or extensive product manuals where users rely heavily on faceted search and dynamic navigation driven by semantic relationships.

  • **Requirement Met:** Sustained handling of high concurrent read loads (e.g., 500 concurrent users) without degraded query response times, relying on the 25GbE interfaces and robust caching layers.
      1. 3.4. Systems Requiring Complex Data Export

Deployment scenarios involving frequent exports of structured data via semantic query results (e.g., generating reports for external BI tools). The high CPU power minimizes the time required to assemble these large result sets before transmission. External API Interfacing.

---

    1. 4. Comparison with Similar Configurations

To justify the investment in this high-end configuration, it is useful to compare it against lower-tier options typically used for standard, non-semantic MediaWiki deployments.

      1. 4.1. Configuration Tiers Overview

| Configuration Tier | Target Wiki Size | CPU Profile | System RAM | Storage Profile | Primary Bottleneck | | :--- | :--- | :--- | :--- | :--- | :--- | | **Tier 1 (Basic)** | < 10,000 Pages | 4 Cores (Mid-Range) | 64 GB | SATA SSD (RAID 1) | CPU for parsing, I/O for large DB/Cache. | | **Tier 2 (Standard MW)** | 100,000 Pages (Non-Semantic) | 16 Cores (High Clock) | 256 GB | 2x 1TB NVMe (RAID 0) | Standard cache misses and PHP execution time. | | **Tier 3 (This Spec - SMW Optimized)** | 100,000 Pages (Semantic Heavy) | 64 Cores (High Bandwidth) | 768 GB | 4x 3.84TB NVMe (RAID 10) | Complexity of the SPARQL-like query structure itself. | | **Tier 4 (Extreme Scale)** | > 5 Million Triples | 2x 64 Cores (Max Density) | 2 TB+ | All-Flash Array (External SAN) | Network latency between application and storage layer. |

      1. 4.2. Impact of CPU vs. RAM on SMW Performance

The primary differentiator for SMW hosting versus standard MediaWiki is the trade-off between raw CPU thread count and available memory.

**Performance Sensitivity Analysis for SMW**
Parameter Impact on Standard Wiki Performance Impact on Semantic Wiki Performance Recommended Scaling Strategy
RAM Capacity High (Caching, Session Storage) **Extreme** (Query result sets, Index residency) Scale RAM before CPU upgrade if query latency exceeds 2 seconds consistently.
CPU Core Count Medium (PHP Parallelism) **High** (Query parsing, Join operations) Essential for reducing latency on complex, multi-hop queries.
Storage IOPS (Random Read) Medium (Database lookups) **Critical** (Index traversal, fact retrieval) Must utilize NVMe Gen4/Gen5; SATA is unacceptable for production SMW.
    • Conclusion on Comparison:** A Tier 2 configuration, perfectly adequate for a standard high-traffic wiki, will experience query times exceeding 10 seconds for the "Very High" complexity queries listed in Section 2.2, rendering the semantic features unusable for interactive workflows. The T3 specification mitigates this by providing the necessary computational parallelism and massive memory footprint to keep indices hot. Scaling Semantic Data Stores.

---

    1. 5. Maintenance Considerations

Deploying and maintaining a high-performance SMW server requires specialized attention to thermal management, power redundancy, and version control due to the tight coupling between the MediaWiki core, the SMW extension, and the underlying database structure.

      1. 5.1. Thermal and Cooling Requirements

The specified dual-socket configuration with high-TDP CPUs (e.g., 250W TDP per CPU under high load) generates significant thermal output.

  • **Ambient Temperature:** Maintain rack ambient temperature below 22°C (72°F). Exceeding this significantly reduces the CPU's ability to sustain turbo frequencies during heavy query processing.
  • **Airflow:** Ensure front-to-back airflow is unobstructed. Use high static pressure fans in the chassis.
  • **Power Draw:** Peak power draw under stress testing (heavy indexing + full query load) can exceed 1400W. Ensure PDUs and UPS capacity are rated for at least 20% headroom above this peak. Data Center Power Density.
      1. 5.2. Software and Version Management

The stability of SMW relies heavily on version compatibility between PHP, the RDBMS, and the extension itself.

1. **PHP Version:** Must use a currently supported, high-performance PHP version (e.g., PHP 8.3+). Ensure the PHP Configuration Limits (e.g., `memory_limit`, `max_execution_time`) are set high enough to accommodate complex page renders and long-running background jobs initiated by SMW. 2. **Database Schema Upgrades:** SMW upgrades often involve structural changes to the semantic index tables. **Always** perform a full backup and test schema migration in a staging environment before applying updates to production. Monitor the `smw_updatelog` table closely post-upgrade. Database Backup Procedures. 3. **SMW Cache Management:** The internal SMW cache (separate from the standard MediaWiki object cache) must be periodically purged, especially after major data imports or schema extensions. Use maintenance scripts like `php maintenance/rebuildSemanticData.php` during scheduled downtime. MediaWiki Maintenance Scripts.

      1. 5.3. Monitoring and Alerting

Standard monitoring must be augmented to track SMW-specific performance indicators.

| Metric | Threshold for Alerting | Monitoring Tool Integration | | :--- | :--- | :--- | | Database Query Latency (Avg for `#ask`) | > 1.5 seconds sustained for 5 minutes | Prometheus/Grafana using the RDBMS exporter. | | CPU Utilization (1-minute average) | > 85% sustained | BMC/OS monitoring agents. | | NVMe Health (SMART Data) | Any critical warning reported | Hardware monitoring suite (e.g., OpenManage Enterprise). | | Semantic Store Lock Contention | Detectable high wait times in database analysis | RDBMS slow query log analysis. |

      1. 5.4. Disaster Recovery and High Availability (HA)

While this specification details a single primary node, production deployments require HA strategy.

  • **Database Replication:** Utilize synchronous or semi-synchronous replication (e.g., MariaDB Galera Cluster or PostgreSQL streaming replication). Read replicas are highly effective for offloading standard page reads, but **write-heavy semantic indexing operations must be handled carefully** to avoid replication lag. Database Replication Topologies.
  • **Application Failover:** Use a load balancer (e.g., HAProxy, NGINX) directing traffic to the active instance. The failover mechanism must ensure that the application state (including the object cache connection) is correctly initialized on the passive node before taking over traffic. Load Balancing Techniques.
  • **Data Integrity Check:** Periodically run the SMW integrity checker script (`AdminSettings.php` utility) to ensure that the stored facts correspond correctly to the visible page annotations, particularly after failover events. Data Integrity Validation.

This high-performance server configuration provides the necessary foundation for robust, scalable, and responsive Semantic MediaWiki deployments, transforming a standard wiki platform into a powerful, structured knowledge engine. MediaWiki Performance Tuning. Semantic Data Modeling. Advanced SMW Configuration. Server Hardware Lifecycle Management. Operating System Hardening. Network Latency Mitigation. Caching Layers Explained. Troubleshooting Semantic Errors. Extending MediaWiki Functionality.

---


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

Order Your Dedicated Server

Configure and order your ideal server configuration

Need Assistance?

⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️

Retrieved from "https://serverrental.store/index.php?title=Extension:Semantic_MediaWiki&oldid=6363"