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timelines at scale
@raffi
qcon sf 2012
Timelines at scale
Timelines at scale
Pull Push
Targeted twitter.com
home_timeline API
User / Site Streams
Mobile Push (SMS, etc.)
Queried Search API Track / Follow Streams
the challenge
⇢> 150M world wide active users
⇢> 300K QPS for timelines
⇢naïve timeline “materialization” can be
slow
Timeline
Service
Ingester
SearchCache
Redis
Redis
Earlybird
Blender
PushCompute
HTTP Push
Mobile
Push
BatchCompute
Hadoop
Write API
Fanout
Redis
Redis
TimelineCache
Redis
Timeline
Service
Ingester
SearchCache
Redis
Redis
Earlybird
Blender
PushCompute
HTTP Push
Mobile
Push
BatchCompute
Hadoop
Write API
Fanout
Redis
Redis
TimelineCache
Redis
Social
Graph
Service
Timeline
Service
Ingester
SearchCache
Redis
Redis
Earlybird
Blender
PushCompute
HTTP Push
Mobile
Push
BatchCompute
Hadoop
Write API
Fanout
Redis
Redis
TimelineCache
Redis
Social
Graph
Service
insert
⇢keyed off
“recipient”
⇢pipelined 4k
“destinations”
at a time
⇢replicated
Timeline
Service
Ingester
SearchCache
Redis
Redis
Earlybird
Blender
PushCompute
HTTP Push
Mobile
Push
BatchCompute
Hadoop
Write API
Fanout
Redis
Redis
TimelineCache
Redis
using redis
⇢native list
structure
Tweet ID BitsUser ID
8 bytes 4 bytes8 bytes
Timeline
Service
Ingester
SearchCache
Redis
Redis
Earlybird
Blender
PushCompute
HTTP Push
Mobile
Push
BatchCompute
Hadoop
Write API
Fanout
Redis
Redis
TimelineCache
Redis
using redis
⇢native list
structure
⇢RPUSHX to
only add to
cached
timelines
Tweet ID BitsUser ID
Tweet ID BitsUser ID
Tweet ID BitsUser ID
Tweet ID BitsUser ID
Tweet ID BitsUser ID
Tweet ID BitsUser ID
Tweet ID BitsUser ID
Tweet ID BitsUser ID
Tweet ID BitsUser ID
Tweet ID BitsUser ID Tweet ID
Tweet ID
Tweet ID
Ingester
SearchCache
Redis
Redis
Earlybird
Blender
PushCompute
HTTP Push
Mobile
Push
BatchCompute
Hadoop
Write API
Fanout
Redis
Redis
TimelineCache
Timeline
Service
Redis
Timeline
Service
Write API
Fanout
Redis
Redis
TimelineCache
Redis
TweetyPieGizmoduck
Pull Push
Targeted twitter.com
home_timeline API
User / Site Streams
Mobile Push (SMS, etc.)
Queried Search API Track / Follow Streams
Ingester
SearchCache
Redis
Redis
Earlybird
Blender
PushCompute
HTTP Push
Mobile
Push
BatchCompute
Hadoop
Write API
Fanout
Redis
Redis
TimelineCache
Timeline
Service
Redis
PushCompute
HTTP Push
Mobile
Push
BatchCompute
HadoopSearchIndex
Blender
Redis
Timeline
Service
Ingester
Earlybird
Write API
Fanout
Redis
Redis
TimelineCache
RedisEarlybird
blender
⇢queries one
replica of all
indexes
⇢merges &
ranks results
PushCompute
HTTP Push
Mobile
Push
BatchCompute
HadoopSearchIndex
Blender
Redis
Timeline
Service
Ingester
Earlybird
Write API
Fanout
Redis
Redis
TimelineCache
RedisEarlybird
Write
API
Redis
Redis
Redis
Write
API
Earlybird
Earlybird
Earlybird
API
Cache
Read
API
Redis
Redis
Redis
Read
API
Earlybird
Earlybird
Earlybird
API
Cache
⇢O(n) write
⇢O(1) write
⇢O(1) read
⇢O(n) read
the challenge (part #2)
⇢fanout can be really slow!
⇢...especially for high follower counts
Timelines at scale
@barackobama
23 million followers
31 million followers
@katyperry
28 million followers
@justinbieber
28 million followers
@raffi
0.019 million followers
@ladygaga
there are over
400 million tweets
a day
a second
4600 tweets
0.2 m
a twe
≈
Timelines at scale
Write API
Ingester Fanout
SearchIndexRedis
Earlybird
Earlybird
Redis
Redis
Redis
TimelineCache
search index
⇢[‘hello’,‘world’]
fanout index
⇢[@danadanger, ...]
User Intent Query Expansion
“Hello, world” “Hello” AND “world”
@raffi’s home timeline home_timeline:raffi
User Intent Query Expansion
“Hello, world” “Hello” AND “world”
@raffi’s home timeline
user_timeline:nelson
OR
user_timeline:danadanger
User Intent Query Expansion
“Hello, world” “Hello” AND “world”
@raffi’s home timeline home_timeline:raffi
User Intent Query Expansion
“Hello, world” “Hello” AND “world”
@raffi’s home timeline
home_timeline:raffi
OR
user_timeline:taylorswift13
BatchCompute
Hadoop
PushCompute
HTTP Push
SearchIndex
Blender
Redis
Timeline
Service
Ingester
Earlybird
Write API
Fanout
Redis
Redis
TimelineCache
RedisEarlybird
Mobile
Push
Asynchronous Path
Query Path
BatchCompute
Hadoop
Synchronous Path
PushCompute
HTTP Push
SearchIndex
Blender
Redis
Timeline
Service
Ingester
Earlybird
Write API
Fanout
Redis
Redis
TimelineCache
RedisEarlybird
Mobile
Push
Synchronous Path
Query Path
BatchCompute
Hadoop
Asynchronous Path
PushCompute
HTTP Push
SearchIndex
Blender
Redis
Timeline
Service
Ingester
Earlybird
Write API
Fanout
Redis
Redis
TimelineCache
RedisEarlybird
Mobile
Push
Asynchronous Path
Synchronous Path
BatchCompute
Hadoop
Query Path
PushCompute
HTTP Push
SearchIndex
Blender
Redis
Timeline
Service
Ingester
Earlybird
Write API
Fanout
Redis
Redis
TimelineCache
RedisEarlybird
Mobile
Push
timeline query statistics
⇢>150m active users worldwide
⇢>300k qps poll-based timelines
@ 1ms p50 / 4ms p99
⇢>30k qps search-based timelines
tweet input
⇢~400m tweets per day
⇢~5K/sec daily average
⇢~7K/sec daily peak
⇢>12K/sec during large events
timeline delivery statistics
⇢30b deliveries / day (~21m / min)
⇢3.5 seconds @ p50 to deliver to 1m
⇢~300k deliveries / sec
Timelines at scale
Timelines at scale
Timelines at scale
Timelines at scale
Timelines at scale
Timelines at scale
thanks!

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Timelines at scale