Уровень 0 · материалов: 4
В кластер входят документы, посвященные техническим методам разделения данных в СУБД (партиционированию и шардингу), и не входят документы об общей архитектуре серверов или управлении состоянием в многопользовательских играх.
Общие признаки: партиционирование таблиц, шардинг данных, оптимизация производительности БД, PostgreSQL, MySQL, обработка больших объемов данных
Группа выше: Масштабирование и высокая доступность баз данных
Смысл: The main idea is to provide a practical guide on how to scale PostgreSQL databases using partitioning (on one server) and sharding (across multiple servers) to maintain performance as data grows, utilizing specific tools and extensions to minimize application-side changes.
A technical guide on scaling databases using PostgreSQL partitioning and horizontal sharding to improve performance and handle massive data growth.
Смысл: The main idea is to educate developers and DBAs on how to implement and manage table partitioning in PostgreSQL to improve performance and maintainability for very large datasets, while providing a practical strategy for migrating existing data without service interruption.
A comprehensive technical tutorial on implementing table partitioning in PostgreSQL using inheritance, triggers, and batch migration strategies to optimize large-scale database performance.
Смысл: The main idea is to demonstrate how to scale a database for a high-load MMORPG by transitioning from simple sharding and MySQL to a sophisticated PostgreSQL-based architecture featuring virtual sharding, hybrid JSON storage, and hardware optimization with SSDs.
A lead developer explains the transition from MySQL to a high-performance, hybrid PostgreSQL architecture to support the massive scaling requirements of the MMORPG Skyforge.
Смысл: The main idea is to explain the concept, implementation, and benefits of horizontal partitioning in MySQL to optimize database performance for both reading and writing large volumes of data.
An educational guide on using MySQL horizontal partitioning (RANGE, LIST, HASH, KEY) to improve query performance and data management for large tables.