Algolia is a distributed Search-as-a-Service API that processes more than 4 billions user-generated queries per month. Algolia’s DNA is performance: Algolia's service is optimized to reply in milliseconds from any location worldwide while maintaining high availability. Sylvain will provide you details on Algolia architecture, showing how they have designed their fault tolerant service and how they cracked the website & in-app search. http://www.meetup.com/Enterprise-Search-and-Analytics-Meetup/events/223926122/

1. Instant Search API
Build Unique Search Experiences
Sylvain Utard
VP of Engineering
sylvain@algolia.com
@sylvainutard
Enterprise Search and Analytics

2. @algolia
Who am I?
5 years @ Exalead, leading the core-engine & NLP teams
• C++
• ExaScript (RIP)
• Java
2 years @ Algolia, VP of Engineering
• C++
• Ruby
• Java
• and 10+ other languages…
@sylvainutard

3. @algolia
A hosted search API

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A hosted search API

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6. @algolia
A hosted search API
Replies in milliseconds

7. @algolia
A hosted search API
Replies in milliseconds
From anywhere

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A hosted search API
Replies in milliseconds
From anywhere With intuitive relevance

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Algolia Today

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800+customers in 80+ countries
Algolia Today

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800+customers in 80+ countries
40B+ Write operationsper month
4B+ User-generated queriesper month
Algolia Today

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Algolia Today
13locations
800+customers in 80+ countries
40B+ Write operationsper month
4B+ User-generated queriesper month

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Performance
is our DNA

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Speed matters
Half a second delay
caused 20% drop in traffic
Every 100ms of latency
costs them 1% in sales

15. @algolia
Behind the scene

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Unique set of constraints
High volume of Read & Write operations

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Unique set of constraints
High volume of Read & Write operations
High-availability

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Unique set of constraints
High volume of Read & Write operations
High-availability
Worldwide data distribution

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API Software Stack
Started as a mobile offline SDK
Written in C++
Search code embedded in Nginx as a module
Indexing is done in a separate process
Two redis instances

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API Hardware
Fast CPU (Xeon E5 >3.5GHz)
In Memory (128GB)
Backed by High-end SSD in Raid-0 (800GB)
Specific kernel settings

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Scaling horizontally
Several clusters per location
A user is assigned to one master cluster
A user can be replicated to N replicate clusters

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What is a cluster
Master-Master
Stream of writes via Consensus
At least 3 machines

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A write in practice
One of the machines accept
the write operation via the API (https)
/1/indexes/MyFirstIndex/batch

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A write in practice
The file is saved on the three machines
as a temporary file
tmp1265
tmp7864
tmp2357

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A write in practice
Launch the consensus by contacting
the RAFT master
startConsensus(tmp2357, tmp7864, tmp1265)

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A write in practice
1 -Master send the commit order to all nodes
2- Each node returns the next job ID to master
3- If there is a majority the file is committed

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A write in practice
Same job ID on all hosts
Send to slave replicate in parallel
Processed in parallel on all hosts
job42
job42
job42

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In case one host is down
Continue to accept writes
The two other hosts keep jobs
Jobs are sequential, will catch up at restart
job42job42

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Distribution
Replicate jobs, not the result
Send to all machines in parallel
Consistent with few seconds delay

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High availability
Multi-regions in one location

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High availability
13 fully independent locations

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Network Optimisations
API usage moving from servers to
browser and mobile apps
Get close to end users

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Distributed Search Network - Worldwide Synchronization

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Distributed Search Network - Worldwide Synchronization

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• 13 locations = 25 datacenters
• No ideal worldwide provider
• AWS is not in India, Eastern EU, Africa…
• Need to handle several providers
• Anticipate long deliveries / customs
• Keep as few providers as possible
Distributed Search Network - Worldwide Synchronization

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DNS is key
Used to find the closest location
Several DNS providers
Good anycast network

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API Clients
DNS health checks are not enough
Smart retry logic in all our API Clients

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Analytics
• What are my users searching for?
• Top search
• Top search without hits
• Top refinements
• From where do they search for?

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Analytics
• Billions of user-generated queries per month
• As-you-type aggregation
• ~3 months retentions
• Storing all of them in…

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Analytics
• Elasticsearch o/
• … without FTS :)
• but with aggregations

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Analytics• No FTS
• No source
• Doc values everywhere
• SSD only
• Custom aggregations
(deprecated since ES 1.1.0)

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Top-k Aggregation
• Before
• Linear memory consumption
• Exhaustivity
• After
• Constant memory consumption
• Approximative but enough

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Building your worldwide infra
- Is long and difficult quest
- Is a real asset & differentiator
The Future of APIs
is Distributed

46. @algolia
All the details of our architecture
are on HighScalability.com
Want to know more?

47. THANK YOU!
sylvain@algolia.com
@algolia
Build Unique Search Experiences
W
e are hiring in SF, NYC and Paris 😊