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This document details how Facebook engineers scaled Memcached, a popular open-source in-memory caching solution, to accommodate the demands of the world's largest social network. The paper outlines the development of Facebook's Memcached architecture, starting with a single cluster of servers and progressing through geographically distributed clusters. It highlights key optimizations and mechanisms implemented at various scales, including reducing latency, handling failures, and maintaining data consistency across multiple regions. The document also provides insights into the characteristics of Facebook's Memcached workload, including fan-out, response size, and latency.
https://research.facebook.com/publications/scaling-memcache-at-facebook/
43 פרקים
This document details how Facebook engineers scaled Memcached, a popular open-source in-memory caching solution, to accommodate the demands of the world's largest social network. The paper outlines the development of Facebook's Memcached architecture, starting with a single cluster of servers and progressing through geographically distributed clusters. It highlights key optimizations and mechanisms implemented at various scales, including reducing latency, handling failures, and maintaining data consistency across multiple regions. The document also provides insights into the characteristics of Facebook's Memcached workload, including fan-out, response size, and latency.
https://research.facebook.com/publications/scaling-memcache-at-facebook/
43 פרקים
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