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Sharding Data for Fun & Profit
--client
big_apple_py
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pygotham_2015
--room room701 10043 --force
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Marks
Author(s):
Wes Chow
Location
Room 701
Date
aug Sat 15
Days Raw Files
Start
14:30
First Raw Start
14:23
Duration
00:55:00
Offset
0:06:46
End
15:25
Last Raw End
15:33
Chapters
00:00
Total cuts_time
44 min.
https://pygotham.org/2015/talks/185/sharding-data-for-fun-profit
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The hash function is the veritable hammer for pounding a large array of engineering problems into submission. Want to shard your database? Draw a key from your data, hash it, and voila, instant deterministic load balancing! That’s simple enough, until you look more carefully at distributional effects, failure, and redundancy management. We’ll review well known (consistent hashing), not so well known (rendezvous hashing), and recent (shuffle sharding, copysets) work that goes a long way towards engineering more favorable failure scenarios.
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