Thod NguyenChief Technology Officer

Big Dating at eHarmony

social impact

big dating at scale

3B+ potential matches daily ~ 25+ TB of data

60M+ multi-attribute queries daily looking across 250+ attributes

212M+ photos ~ 15+ TB of data

4B+ relationship questionnaires ~ 25+ TB of data

the big win for product

Decreased the processing time to match by 95%, from 2+ weeks to 12 hours

on 3B+ potential matches/day

30% increase in 2-way communications

50% increase in paid subs

60% increase in unique visitors

today

Compatibility Matching System

The Old

The New

Why MongoDB

What’s Next

compatibility matching system®

Compatibility Matching System®

MatchDistribution

3

Compatibility Matching

1

Affinity Matching

2

Compatibility Matching System®

Affinity Matching

MatchDistribution

2 3

compatibility matching system (cont’d)

Compatibility Matching

1

traditional search

eharmony matching

compatibility models

compatibility matching process

legacy compatibility match processor (CMP)

legacy compatibility match processor V.2 (CMP)

challenges with existing v2. design

challenges with existing v2. design (contd.)

challenges with existing v2. design (contd.)

challenges with existing v2. design (contd.)

challenges with existing v2. design (contd.)

new data store requirements

why Mongodb?

tradeoffs

No schema = larger footprint

Aggregation queries are different

Initial configuration can be long, manual process

lessons learned

Turn on the Firehose

Unleash the Chaos Monkey

Engage MongoDB, Inc. early – dev to production

Try to isolate your queries to a shard

Run in shadow mode

what’s next

New matching use cases:

Globalization and Localization of eH siteCareers by eHarmonyInternet of Things “Compatible”

New use cases within eHarmony:

Real-time geo location based matching service Careers

technology stack

linkedin.com/in/thodnguyenlinkedin.com/in/thodnguyenWe’re Hiring @jobs.eharmony.comWe’re Hiring @jobs.eharmony.com