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How Neo4j Sparked a New Wave of Innovation at Adobe
BehanceDavid Fox | Senior Software Engineer
© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Behance
 Leading online platform to showcase and discover creative work
 More than 10 million members
 Allows creatives to share their work with millions of daily visitors
 Highlights Adobe software used in the creation process
 Drives people to the Adobe Creative Cloud
 Social platform for discovery, learning, and more
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Behance
3
Behance Logged-in Home Page/Activity Feed (2018)
© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Introduced Neo4j to our Tech Stack
 Replaced bloated/difficult to manage Cassandra architecture
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Activity Feed Cassandra Instances (48)
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Activity Feed Neo4j Instances (3)
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Introduced Neo4j to our Tech Stack cont.
 Eliminated fanouts from Cassandra model
 50tb of data to 50gb
 Cost savings
 Better performance for user-facing feature
 More content for users to consume
 Cassandra model was very rigid, Neo4j graph model is flexible
 Big success, but more use-cases weren’t clear for us
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Shortly after we moved to Neo4j…
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Basic following model
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Very easy to filter by followee type
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Basic unfiltered activity fetch
MATCH (me:User{id:123})-[:FOLLOWS]->(something)-[r:DID_ACTION]-
>(project:Project)
RETURN project, r.type ORDER BY r.created_on DESC LIMIT 50
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Only show newly published projects from people I follow
MATCH (me:User{id:123})-[:FOLLOWS]->(someone:User)-[r:DID_ACTION]-
>(project:Project)
WHERE r.type = “published”
RETURN project ORDER BY r.created_on DESC LIMIT 50
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
OK… Cypher/graph model is flexible, so what?
 Not just flexible; flexible at scale and in production
 Encourages innovation and experimentation
 Do more with the data you already have in DB
 Cassandra – no new activity-feed-based features/improvements for 1 year+
 Shows product team we can develop + iterate quickly
 Slow-to-iterate/rigid db structures can become a mindset + culture?
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Introduced WIPs (work in progress) (2018)
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Users can react to WIPs
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
WIP Recommendations - Challenges
 Ephemeral content (WIPs only last for 24 hours) means pipeline has to be very
short
 Couldn’t use usual tools like Spark, periodic model re-calculation, etc.
 Needed ability to calculate recommended WIPs in near-realtime
 Building Spark or other pipeline would take months with uncertain results
 Working with remote Adobe research team
 Developed Spark recommendation pipeline for previous project
 No prior experience with graph databases or Neo4j
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
WIP Recommendations – Neo4j
 Flexible graph db model already had data we needed
 Cypher is pretty intuitive – research team could quickly learn
 Very quick prototyping, just change the Cypher query
 check if what you’re spending time on is working!
 Powerful: 61 line Cypher query algorithm for prod algorithm
 Still fast enough to run on-demand
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Just about a month for full product dev/rollout… (early 2019)
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Success Metric - Reactions
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+20%!
© 2019 Adobe. All Rights Reserved. Adobe Confidential.
WIP Recommendations - Summary
 Collaboration with algorithm-heavy with no Neo4j experience
 Rapid prototyping allowed product team review of progress/quality
 No pipeline = quick to production, easy rollout
 Neo4j allowed us to get the feature in front of users quickly
 20% increase in WIP reactions (engagement metric)
 Most complex algo/pipeline might not be best solution
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Returning to feed, our main experience
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
More features, but became a bit fragmented (For You feed,
2018-2019)
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© 2019 Adobe. All Rights Reserved. Adobe Confidential. 27
© 2019 Adobe. All Rights Reserved. Adobe Confidential.
What if we… put it all together into one feed??
 Status quo was any large-scale data view change was hard
 required large migrations
 extensive load-testing
 new database tables, etc.
 Product team confident we could deliver without lots of work/time based on ease
of past Neo4j features/iterations
 Consistent, infinitely-scrollable API with user activity, curated gallery activity, and
recommendations
 Consumable by our web and mobile apps
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Building the smart For You Feed experience with Neo4j
(summer 2019)
 Main goals:
 Bring more exposure to newly published projects from people you follow
 Ability to quickly iterate on the feed across all our apps
 Ability to strategically prioritize different types of feed content
 Future flexibility
 Relatively simple to build because data already in Neo4j
 Robustness of Cypher/graph model allow for querying data in this very
detailed/custom ways
 Performance very important – one of most frequently accessed pages on
Behance
 Hard to cache
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
New projects from people you follow + followed gallery projects
on web
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Projects from moodboards you follow on web
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Appreciations from people you follow on web
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Recommendations on web
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
New projects from people you follow + followed gallery projects
on iOS
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Appreciated by people you follow on iOS
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Smart For You Feed – success metric review
 10% increase in projects viewed overall
 240% increase in views of new projects from people you
follow
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© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Smart For You Feed - Summary
 Success through experimentation and flexibility
 Core to our business, hard metrics to move easily
 Would’ve been difficult, time-consuming, and extremely hard to iterate with old
system
 Future flexibility
 Deprioritize already-seen items?
 Dynamically shift content prioritization based on user tastes/behavior?
 Product team already thinking about these, knowing we can execute quickly
37
© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Applying this innovation structure elsewhere
 Try to be open to using graph in prod for use-cases that make sense
 Take a lot of care when you develop your data model
 Take advantage of ease of creating proof-of-concepts in Neo4j to sell it at
company
 Think how you can turn complex pipelines into smaller, simpler Cypher queries
that reduce app complexity
 You may be surprised how much is runnable on-demand (per request) even at scale
38
© 2019 Adobe. All Rights Reserved. Adobe Confidential.
The real value
 Product team can focus on innovating instead of thinking about what can’t easily
be done
 More complex/slightly more effective algos/pipelines aren’t always better
 Value in being able to quickly iterate and change entire user-experiences by just changing
Cypher queries
 Easier to make measurable changes
 Granular A/B tests
 Use-cases and innovation can spread beyond initial feature
 Other team members pitching ideas, ex. user-facing stats overhaul with Neo4j
39
© 2019 Adobe. All Rights Reserved. Adobe Confidential.
Thanks for coming!
Please let me know if you have any questions!
Contact:
David Fox
dafox@adobe.com
40

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Neo4j GraphTour New York_ Adobe Presentation_David Fox

  • 1. How Neo4j Sparked a New Wave of Innovation at Adobe BehanceDavid Fox | Senior Software Engineer
  • 2. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Behance  Leading online platform to showcase and discover creative work  More than 10 million members  Allows creatives to share their work with millions of daily visitors  Highlights Adobe software used in the creation process  Drives people to the Adobe Creative Cloud  Social platform for discovery, learning, and more 2
  • 3. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Behance 3 Behance Logged-in Home Page/Activity Feed (2018)
  • 4. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Introduced Neo4j to our Tech Stack  Replaced bloated/difficult to manage Cassandra architecture 4
  • 5. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Activity Feed Cassandra Instances (48) 5
  • 6. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Activity Feed Neo4j Instances (3) 6
  • 7. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Introduced Neo4j to our Tech Stack cont.  Eliminated fanouts from Cassandra model  50tb of data to 50gb  Cost savings  Better performance for user-facing feature  More content for users to consume  Cassandra model was very rigid, Neo4j graph model is flexible  Big success, but more use-cases weren’t clear for us 7
  • 8. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Shortly after we moved to Neo4j… 8
  • 9. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Basic following model 9
  • 10. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Very easy to filter by followee type 10
  • 11. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Basic unfiltered activity fetch MATCH (me:User{id:123})-[:FOLLOWS]->(something)-[r:DID_ACTION]- >(project:Project) RETURN project, r.type ORDER BY r.created_on DESC LIMIT 50 11
  • 12. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Only show newly published projects from people I follow MATCH (me:User{id:123})-[:FOLLOWS]->(someone:User)-[r:DID_ACTION]- >(project:Project) WHERE r.type = “published” RETURN project ORDER BY r.created_on DESC LIMIT 50 12
  • 13. © 2019 Adobe. All Rights Reserved. Adobe Confidential. OK… Cypher/graph model is flexible, so what?  Not just flexible; flexible at scale and in production  Encourages innovation and experimentation  Do more with the data you already have in DB  Cassandra – no new activity-feed-based features/improvements for 1 year+  Shows product team we can develop + iterate quickly  Slow-to-iterate/rigid db structures can become a mindset + culture? 13
  • 14. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Introduced WIPs (work in progress) (2018) 14
  • 15. © 2019 Adobe. All Rights Reserved. Adobe Confidential. 15
  • 16. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Users can react to WIPs 16
  • 17. © 2019 Adobe. All Rights Reserved. Adobe Confidential. WIP Recommendations - Challenges  Ephemeral content (WIPs only last for 24 hours) means pipeline has to be very short  Couldn’t use usual tools like Spark, periodic model re-calculation, etc.  Needed ability to calculate recommended WIPs in near-realtime  Building Spark or other pipeline would take months with uncertain results  Working with remote Adobe research team  Developed Spark recommendation pipeline for previous project  No prior experience with graph databases or Neo4j 17
  • 18. © 2019 Adobe. All Rights Reserved. Adobe Confidential. WIP Recommendations – Neo4j  Flexible graph db model already had data we needed  Cypher is pretty intuitive – research team could quickly learn  Very quick prototyping, just change the Cypher query  check if what you’re spending time on is working!  Powerful: 61 line Cypher query algorithm for prod algorithm  Still fast enough to run on-demand 18
  • 19. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Just about a month for full product dev/rollout… (early 2019) 19
  • 20. © 2019 Adobe. All Rights Reserved. Adobe Confidential. 20
  • 21. © 2019 Adobe. All Rights Reserved. Adobe Confidential. 21
  • 22. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Success Metric - Reactions 22 +20%!
  • 23. © 2019 Adobe. All Rights Reserved. Adobe Confidential. WIP Recommendations - Summary  Collaboration with algorithm-heavy with no Neo4j experience  Rapid prototyping allowed product team review of progress/quality  No pipeline = quick to production, easy rollout  Neo4j allowed us to get the feature in front of users quickly  20% increase in WIP reactions (engagement metric)  Most complex algo/pipeline might not be best solution 23
  • 24. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Returning to feed, our main experience 24
  • 25. © 2019 Adobe. All Rights Reserved. Adobe Confidential. More features, but became a bit fragmented (For You feed, 2018-2019) 25
  • 26. © 2019 Adobe. All Rights Reserved. Adobe Confidential. 26
  • 27. © 2019 Adobe. All Rights Reserved. Adobe Confidential. 27
  • 28. © 2019 Adobe. All Rights Reserved. Adobe Confidential. What if we… put it all together into one feed??  Status quo was any large-scale data view change was hard  required large migrations  extensive load-testing  new database tables, etc.  Product team confident we could deliver without lots of work/time based on ease of past Neo4j features/iterations  Consistent, infinitely-scrollable API with user activity, curated gallery activity, and recommendations  Consumable by our web and mobile apps 28
  • 29. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Building the smart For You Feed experience with Neo4j (summer 2019)  Main goals:  Bring more exposure to newly published projects from people you follow  Ability to quickly iterate on the feed across all our apps  Ability to strategically prioritize different types of feed content  Future flexibility  Relatively simple to build because data already in Neo4j  Robustness of Cypher/graph model allow for querying data in this very detailed/custom ways  Performance very important – one of most frequently accessed pages on Behance  Hard to cache 29
  • 30. © 2019 Adobe. All Rights Reserved. Adobe Confidential. New projects from people you follow + followed gallery projects on web 30
  • 31. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Projects from moodboards you follow on web 31
  • 32. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Appreciations from people you follow on web 32
  • 33. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Recommendations on web 33
  • 34. © 2019 Adobe. All Rights Reserved. Adobe Confidential. New projects from people you follow + followed gallery projects on iOS 34
  • 35. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Appreciated by people you follow on iOS 35
  • 36. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Smart For You Feed – success metric review  10% increase in projects viewed overall  240% increase in views of new projects from people you follow 36
  • 37. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Smart For You Feed - Summary  Success through experimentation and flexibility  Core to our business, hard metrics to move easily  Would’ve been difficult, time-consuming, and extremely hard to iterate with old system  Future flexibility  Deprioritize already-seen items?  Dynamically shift content prioritization based on user tastes/behavior?  Product team already thinking about these, knowing we can execute quickly 37
  • 38. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Applying this innovation structure elsewhere  Try to be open to using graph in prod for use-cases that make sense  Take a lot of care when you develop your data model  Take advantage of ease of creating proof-of-concepts in Neo4j to sell it at company  Think how you can turn complex pipelines into smaller, simpler Cypher queries that reduce app complexity  You may be surprised how much is runnable on-demand (per request) even at scale 38
  • 39. © 2019 Adobe. All Rights Reserved. Adobe Confidential. The real value  Product team can focus on innovating instead of thinking about what can’t easily be done  More complex/slightly more effective algos/pipelines aren’t always better  Value in being able to quickly iterate and change entire user-experiences by just changing Cypher queries  Easier to make measurable changes  Granular A/B tests  Use-cases and innovation can spread beyond initial feature  Other team members pitching ideas, ex. user-facing stats overhaul with Neo4j 39
  • 40. © 2019 Adobe. All Rights Reserved. Adobe Confidential. Thanks for coming! Please let me know if you have any questions! Contact: David Fox dafox@adobe.com 40

Editor's Notes

  1. Magic? Nope. Watered-down user-facing feature-set? No – more features instead! How? - Graph data model allowed us to remove Cassandra fanouts, eliminate most repeating data