the 5 graphs of love
DESCRIPTION
Recorded webinar: neotechnology.com/webinar-five-graphs-love The iDating industry cares about interactions and connections. Those two concepts are closely linked. If someone has a connection to another person, through a shared friend or a shared interest, they are much more likely to interact. Graph databases are optimized for querying connections between people, things, interests, or really anything that can be connected. Dating sites and apps worldwide have begun to use graph databases to achieve competitive gain. Neo4j provides thousand-fold performance improvements and massive agility benefits over relational databases, enabling new levels of performance and insight. Amanda Laucher discusses the five graphs of love, and how companies like eHarmony, Hinge and AreYouInterested.com, are now using graph algorithms to create more interactions and connections.TRANSCRIPT
![Page 1: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/1.jpg)
�1
Amanda Laucher Neo Technology @pandamonial
(Neo4j)-[:POWERS] ->(Love)
![Page 2: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/2.jpg)
�2
Most of your favorite dating sites
![Page 3: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/3.jpg)
�3
The 5 Graphs of Love
![Page 4: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/4.jpg)
�4
The 5 Graphs of Love
• The Friends-of-Friends Graph
!
!
!
!
!
!
!
![Page 5: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/5.jpg)
�5
The 5 Graphs of Love
• The Friends-of-Friends Graph
!
• The Passion Graph
!
!
!
!
!
![Page 6: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/6.jpg)
�6
The 5 Graphs of Love
• The Friends-of-Friends Graph
!
• The Passion Graph
!
• The Location Graph
!
!
!
![Page 7: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/7.jpg)
�7
The 5 Graphs of Love
• The Friends-of-Friends Graph
!
• The Passion Graph
!
• The Location Graph
!
• The Safety Graph
!
![Page 8: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/8.jpg)
�8
The 5 Graphs of Love
• The Friends-of-Friends Graph
!
• The Passion Graph
!
• The Location Graph
!
• The Safety Graph
!
• The Poser Graph
![Page 9: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/9.jpg)
๏from: California
๏appearance: very handsome
๏personality: super friendly nerd
๏interests: piano, coding
Meet Jeremy...
Jeremy
![Page 10: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/10.jpg)
๏Kerstin: his sister
๏Peter: his buddy
๏Andreas: his coworker
Jeremy has some friends
KerstinAndreas
JeremyPeter
![Page 11: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/11.jpg)
๏Michael: master hacker, divorced, 2 kids
๏Johan: technology sage, likes fast cars
๏Madelene: polyglot journalist, loves dogs
๏Allison: marketing maven, likes long walks on the beach
His friends introduced more friends
Johan
Kerstin
Allison
Andreas
Michael
Madelene
JeremyPeter
![Page 12: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/12.jpg)
๏how do we know they are friends?
๏either ask each pair: are you friends?
๏or, we can add explicit connections
๏Twitter, Facebook, LinkedIn, etc.
So, we have a bunch of people
Johan
Kerstin
Allison
Andreas
Michael
Madelene
JeremyPeter
![Page 13: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/13.jpg)
๏it's just a graph
This is really just data
Johan
Kerstin
Allison
AnnaAdamAndreas
Michael
Madelene
JeremyPeter
![Page 14: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/14.jpg)
�14
A graph?
![Page 15: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/15.jpg)
Yes, a graph...
�15
๏you know the common data structures
•linked lists, trees, object "graphs"
๏a graph is the general purpose data structure
•suitable for any connected data
๏well-understood patterns and algorithms
•studied since Leonard Euler's 7 Bridges (1736)
•Codd's Relational Model (1970)
•not a new idea, just an idea who's time is now
![Page 16: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/16.jpg)
�16
How can you use this? With a Graph Database
![Page 17: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/17.jpg)
A graph database...
�17
๏optimized for the connections between records
๏really, really fast at querying across records
๏a database: transactional with the usual operations
๏“A relational database may tell you the average age of everyone here,
but a graph database will tell you who is most likely to buy you a beer later.”
![Page 18: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/18.jpg)
What’s love got to do with it?
�18
![Page 19: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/19.jpg)
�19
Friends of Friends Graph
![Page 20: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/20.jpg)
!
๏4% likelihood of interacting with a stranger
๏10% likelihood of interacting with friend of friend
๏7% chance of interacting with 3rd degree connection (friend of friend of friend)
๏Connections mean a much larger number of interactions!
JeremyPeterJohan
Jennifer
Allison
AnnaAdamAndreas
Michael
Madelene
According to SNAP Interactive if you are a female user, you have a:
![Page 21: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/21.jpg)
�21
Friends of friends = larger dating pool
![Page 22: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/22.jpg)
Friends
Peter JenniferAndreasJeremy
![Page 23: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/23.jpg)
Friends of friends
PeterJohan
Jennifer
Allison
Andreas
Jeremy
MadeleneFrank
Amanda
Jeremy
![Page 24: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/24.jpg)
Friends of friends of friends
![Page 25: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/25.jpg)
�25
Find Jeremy’s FoFs
![Page 26: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/26.jpg)
�26
Demo - Find who Jeremy shares the most friends with
![Page 27: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/27.jpg)
JakePeter JenniferAndreas
:WORKS_FOR:FRIENDS:FRIENDS
Complicated Relationships
![Page 28: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/28.jpg)
:WANTS_TO_DATE
JakePeter JenniferAndreas
:WORKS_FOR:FRIENDS:FRIENDS
Friends
![Page 29: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/29.jpg)
Awkward!!
JakePeter JenniferAndreas
:WORKS_FOR:FRIENDS:FRIENDS
Friends
:WANTS_TO_DATE
![Page 30: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/30.jpg)
:WANTS_TO_DATE
Awkward
:WANTS_TO_DATE
JakePeter JenniferAndreas
:WORKS_FOR:FRIENDS:FRIENDS
Friends of Friends
![Page 31: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/31.jpg)
:WANTS_TO_DATE
:WANTS_TO_DATE
JakePeter JenniferAndreas
:WORKS_FOR:FRIENDS:FRIENDS
:NO_DATE
Too complex!
Friends of Friends
![Page 32: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/32.jpg)
Friends of Friends of Friends
:WANTS_TO_DATE :WANTS_TO_DATE
JakePeter JenniferAndreas
:WORKS_FOR:FRIENDS:FRIENDS
:NO_DATE
:NO_DATE
:WANTS_TO_DATE
:WANTS_TO_DATE
![Page 33: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/33.jpg)
Friends of Friends of Friends
![Page 34: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/34.jpg)
Friends of Friends of Friends
![Page 35: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/35.jpg)
๏from: UK
๏seeking: Females
๏appearance: Hot, hot, hot!
๏personality: Fun loving, easy going
๏interests: cooking, chemistry
Jon
Meet Jon...
![Page 36: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/36.jpg)
�36
Location Graph
![Page 37: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/37.jpg)
Jon wants to find a date and refuses to have a long distance relationship
�37
![Page 38: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/38.jpg)
�38
Location Graph*Neo4j Spatial
![Page 39: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/39.jpg)
�39
Passion Graph
![Page 40: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/40.jpg)
Jon wants to find someone he can share his passions
with.
�40
![Page 41: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/41.jpg)
Jon
:REPORTED_INTEREST
Match Specific Interests
Cooking
![Page 42: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/42.jpg)
Jon
:REPORTED_INTEREST
Match Specific Interests
![Page 43: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/43.jpg)
Jon
:REPORTED_INTEREST
JenniferAnne Julia
Match Specific Interests
![Page 44: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/44.jpg)
�44
Safety Graph
![Page 45: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/45.jpg)
Jon uses social networks
Jon
![Page 46: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/46.jpg)
Let’s dig into his Twitter
![Page 47: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/47.jpg)
He follows some strange people
![Page 48: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/48.jpg)
…and tweets about strange things!
![Page 49: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/49.jpg)
Some basic word analysis
![Page 50: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/50.jpg)
Let’s update based on behavior
:DEMONSTRATED_INTEREST
Jon
![Page 51: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/51.jpg)
Any ladies ok with this?
![Page 52: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/52.jpg)
Jennifer Jane Maria
Any ladies ok with this?
![Page 53: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/53.jpg)
�53
Passion Graph
![Page 54: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/54.jpg)
Jon loves the New England Patriots
�54
Jon:HAS_INTEREST
![Page 55: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/55.jpg)
�55
Sports
:IS_A
:IS_A
:IS_A:IS_A
![Page 56: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/56.jpg)
�56
Sports
:HAS_TEAM
:HAS_TEAM
:HAS_TEAM
:HAS_TEAM
:HAS_TEAM
:IS_A:IS_A
:IS_A
:IS_A
![Page 57: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/57.jpg)
�57
Sports
:HAS_TEAM
:HAS_TEAM
:HAS_TEAM
:HAS_TEAM
:HAS_TEAM
:IS_A:IS_A
:IS_A
:IS_A
Jon
![Page 58: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/58.jpg)
�58
Sports
Jon
![Page 59: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/59.jpg)
�59
Find ladies who like football
![Page 60: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/60.jpg)
�60
Jennifer Katie Greta
Find ladies who like football
![Page 61: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/61.jpg)
�61
Poser Graph
![Page 62: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/62.jpg)
Jon has no luck with online dating. All of his interactions are with
spam profiles.
�62
![Page 63: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/63.jpg)
Find real people with at least 1 social network & minimum 2 posts
�63
![Page 64: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/64.jpg)
�64
Find ladies who aren’t spam bots
![Page 65: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/65.jpg)
Put it all together
�65
![Page 66: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/66.jpg)
�66
Find Jon’s perfect date
![Page 67: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/67.jpg)
�67
JenniferJon:PERFECT_FOR
![Page 68: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/68.jpg)
�68
JenniferJon:HAS_DATE_WITH
![Page 69: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/69.jpg)
�69
Jon & Jennifer delete their profiles and go off into the sunset!
JenniferJon
![Page 70: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/70.jpg)
Jon Jennifer
Love
[:FOUND]
[:AIDS]
[:AIDS]
[:AIDS]
[:AIDS]
[:AIDS][:POWERS]
![Page 71: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/71.jpg)
�71
Amanda Laucher Neo Technology
(Neo4j)-[:POWERS] ->(Love)
![Page 72: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/72.jpg)
RDBMS/Other vs. Native Graph Database
Performance Challenges with Connected Data
Connectedness of Data Set
Resp
onse
Tim
e
RDBMS / Other NOSQL# Hops: 0-2 Degree: < 3
Size: ThousandsNeo4j
# Hops: Tens to Hundreds Degree: Thousands+ Size: Billions+
1000x faster
![Page 73: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/73.jpg)
Neo Technology, Inc Confidential
Core Industries & Use Cases:
Web / ISV Financial Services
Telecomm-unications
Network & Data Center Management
Master Data Management
Social
Geo
Core Industries & Use Cases: Software
Financial Services
Telecommunications
Health Care & Life Sciences
Web Social,HR & Recruiting
Media & Publishing
Energy, Services, Automotive, Gov’t, Logistics, Education,
Gaming, Other
Network & Data Center Management
MDM / System of Record
Social
Geo
Recommend-ations
Identity & Access Mgmt
Content Management
BI, CRM, Impact Analysis, Fraud Detection, Resource
Optimization, etc.
Accenture
Aviation
Neo4j Adoption SnapshotSelect Commercial Customers* (some NDA)
*Community Users Not Included
![Page 74: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/74.jpg)
Neo Technology, Inc Confidential
Graph Database Deployment
ApplicationOther
Databases
ETL
Graph Database Cluster
Data Storage & Business Rules Execution
Reporting
Graph- Dashboards&Ad-hocAnalysis
Graph Visualization
End User Ad-hoc visual navigation & discovery
Bulk Analytic Infrastructure
(e.g. Graph Compute Engine)
ETL
Graph Mining & Aggregation
Data Scientist
Ad-HocAnalysis
![Page 75: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/75.jpg)
*“Find all direct reports and how many they manage, up to 3 levels down”
(SELECT T.directReportees AS directReportees, sum(T.count) AS count FROM ( SELECT manager.pid AS directReportees, 0 AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") UNION SELECT manager.pid AS directReportees, count(manager.directly_manages) AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT manager.pid AS directReportees, count(reportee.directly_manages) AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT manager.pid AS directReportees, count(L2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT T.directReportees AS directReportees, sum(T.count) AS count FROM ( SELECT manager.directly_manages AS directReportees, 0 AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") UNION SELECT reportee.pid AS directReportees, count(reportee.directly_manages) AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION
(continued from previous page...) SELECT depth1Reportees.pid AS directReportees, count(depth2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT T.directReportees AS directReportees, sum(T.count) AS count FROM( SELECT reportee.directly_manages AS directReportees, 0 AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT L2Reportees.pid AS directReportees, count(L2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT L2Reportees.directly_manages AS directReportees, 0 AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") ) !
Experiencing Query Pain Actual HR Query* (in SQL)
![Page 76: The 5 Graphs of Love](https://reader033.vdocuments.net/reader033/viewer/2022042714/54b6b7a14a79593e4f8b4612/html5/thumbnails/76.jpg)
MATCH (boss)-‐[:MANAGES*0..3]-‐>(sub), (sub)-‐[:MANAGES*1..3]-‐>(report) WHERE boss.name = “John Doe” RETURN sub.name AS Subordinate, count(report) AS Total
Experiencing Query Pain Same Query*, using Cypher
*“Find all direct reports and how many they manage, up to 3 levels down”