新浪微博开放平台中的 Redis 实践
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This document discusses using Redis for social networking applications. Some key points: - Redis is an in-memory database that can dump data to disk and supports many useful data structures like hashes. It provides fast read and write performance. - Redis is used to store relationship data like follower/following lists in hashes with user IDs as keys and fields. MySQL is also used to complement Redis for persistence. - Challenges include high memory usage, slow disk writes, lack of high availability, and performance issues with large hashes. - Potential solutions explored are using MySQL with queues and processors to keep Redis in sync, splitting data between Redis and MySQL more intelligently, and implementing Redis data sharding and replication
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新浪微博开放平台中的 Redis 实践
- 1. Redis @ http://weibo.com/tangfl http://fulin.org
- 2. • Redis • Redis • • •
- 3. Redis • in memory (database?) • data can dump to disk • many useful data structure • FAST both read and write • we start use from 2.0, now 2.4
- 4. =feed+ +
- 5. =feed+ + • feed • •
- 6. =feed+ +
- 7. =feed+ + • • •
- 8. =feed+ +
- 9. =feed+ + • • • @ • @ •
- 10. =feed+ +
- 11. =feed+ + • • • @ • @ •
- 12. =feed+ +
- 13. =feed+ + • • • @ • @ •
- 14. =feed+ +
- 15. =feed+ + • • • @ • @ •
- 16. =feed+ +
- 17. =feed+ + •feed • mysql • mc
- 18. =feed+ + •
- 19. =feed+ + • mysql: relation.following • fromuid, touid, addtime • addtime desc select * from following where fromuid=? order by • addtime desc select * from following where touid=? order by • fromuid, touid
- 20. =feed+ + • mysql: relation.following relation.follower • fromuid, touid, addtime • addtime desc select * from following where fromuid=? order by • desc select * from follower where touid=? order by addtime •
- 21. =feed+ + • • • • •
- 22. =feed+ + • ta • ta • ta •
- 23. =feed+ + • • c/java • • •
- 24. =feed+ + • redis • hash : • key : user id • fields : friends ids • value : add time
- 25. =feed+ + • redis • hash : • hset fromuid.following touid addtime • hset touid.follower fromuid addtime • hgetAll fromuid. following • hgetAll touid.follower ? • 11,704,598 @Wed Sep 7 21:46:33 CST 2011
- 26. =feed+ + • hash-max-zip-size • 64 -> 256 1/3 • cpu • hgetAll cost too much cpu • add mc • high delay
- 27. =feed+ +
- 28. =feed+ + • redis • cache ? waste too much mem • storage ? • rdb may lost data • aof r/w too slow, recover too slow • all data in mem, waste money • HA : master slave ? NO WAY • memory fragment
- 29. =feed+ +
- 30. =feed+ + • • mysql binlog >> queue >> Java Processor >> redis • mysql binlog >> trigger >> redis
- 31. =feed+ + • • redis@weibo for now: • TB • growing fast
- 32. =feed+ + • •@ mysql modified + innodb • following list of a user in one column • still under dev
- 33. =feed+ + •
- 34. =feed+ + • • • •@ • •
- 35. =feed+ +
- 36. =feed+ + • • • @ • • • js
- 37. =feed+ + • mc + queue + mysql • mysql • mc mysql • mc
- 38. =feed+ + • • • • •
- 39. =feed+ + • redis • k-v , 100 byte per k-v • mc • • hash , hget pipeline slow
- 40. =feed+ + • redis • rdb ? may lost data • aof ? grow too fast (4G/day) • bgsave/bgrewriteaof influence parent
- 41. =feed+ +
- 42. =feed+ + • redis rolling • • • • key
- 43. =feed+ + • • rediscounter @ • array , not linked list • malloc all mem when start • hash key to position • write disk: asyn & slow down • add position to aof file
- 44. =feed+ + • • rediscounter + innodb • auto roll cold data to disk
- 45. =feed+ + • • @TimYang • @XiaoJunHong • • redis (delay) - mc (throughput) - java hash map
- 46. • • cache • storage
- 47. • • • • + •
- 48. • • • / • •
- 49. • • • rdb or aof
- 50. • • • rehash
- 51. • HA / Cluster • Redis • Jedis
- 52. • CPU • Redis • hset with big hash-max-zip-size • hgetAll • mc
- 53. • • • • •
- 54. Thanks @ http://weibo.com/tangfl http://fulin.org
- 55. Q &A PS. We are hiring ! contact me via @