This article explains how Quora reduces database load by optimizing read patterns, improving high‑QPS queries with smarter caching, shrinking table size using MyRocks, and boosting write throughput through parallel replication settings, providing concrete steps, code snippets, and real‑world results.
The article details Facebook’s multi‑year effort to migrate its heavily customized MySQL 5.6 deployment—including the MyRocks storage engine—to MySQL 8.0, describing the technical challenges, patch‑porting strategy, replication changes, automated verification, and application validation performed during the upgrade.
Facebook’s engineering team detailed the multi‑year effort to upgrade a heavily customized MySQL 5.6 deployment to MySQL 8.0, describing the migration strategy, code‑patch classification, row‑based replication adoption, extensive automation testing, and the performance and compatibility issues they resolved along the way.
Facebook detailed its multi‑year journey from MySQL 5.6 to 8.0, explaining why it stayed on 5.6 for MyRocks development, the massive patch‑porting effort, replica‑set migration steps, adoption of row‑based replication, extensive automation testing, and the performance and compatibility issues uncovered along the way.
Since 2019 NetEase Media has migrated several recommendation and account services from RDS to MyRocks, cutting disk usage by up to 68 % and halving response times while handling 40‑50 k QPS write‑heavy workloads, though the engine lacks partitioning, online DDL, and certain index types, requiring careful workload assessment.
Facebook upgraded Messenger’s storage by redesigning the schema, switching from HBase to the MyRocks MySQL engine, and moving to flash storage, achieving seamless migration without downtime, cutting storage use by 90%, reducing latency fiftyfold, and simplifying operations for billions of users.
This article explains the internal workings of the SHOW ENGINE ROCKSDB STATUS command in MyRocks, detailing how STATISTICS and BG_THREADS data are collected, the underlying RocksDB APIs, code structures, and how to extend these mechanisms for performance monitoring and debugging.
