Learn how to build applications to process highly connected data by working backwards from your questions to your graph data model.

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Work Backwards to Your Graph Data
Model & Queries with Amazon Neptune
Ian Robinson
Data Architect
AWS
D A T 3 3 0
Mike Personick
Sr. Software Dev Engineer
AWS

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Agenda
Introduction to Amazon Neptune
Overview of the data modelling process
How to apply the property graph building blocks
”Slow motion” example of developing a model and queries

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Related breakouts
Monday, November 26
On-Ramp to Graph Databases and Amazon Neptune - DAT335
4:45 p.m. | Mirage, St. Thomas B
Tuesday, November 27
Migrating to Amazon Neptune - DAT338
11:30 a.m. | Venetian, Level 4, Lando 4305
Wednesday, November 28
Getting Started with Amazon Neptune and Amazon SageMaker Jupyter Notebooks - DAT359
2:30 p.m. | Aria West, Level 3, Starvine 10, Table 7

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Amazon Neptune
Fast, reliable graph database
Optimized for storing and querying highly connected data

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Fully managed graph database
Fast Reliable Open
Query billions of
relationships with
millisecond latency
Six replicas of your data
across three AZs with full
backup and restore
Build powerful queries
easily with Gremlin and
SPARQL
Supports Apache
TinkerPop & W3C RDF
graph models
Easy

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Do I have a graph workload?
Complex domain model Variable schema Connected queries
Large dataset
Many different entities
Similar entities may have
different properties
Highly connected
Entities connected in
many different ways
Navigate connected structure
Take account of strength,
weight, or quality of
relationships
Variable structure
Social
networking
Recommendations Knowledge
graphs
Fraud detection Life sciences Network & IT
operations

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Working backwards—Design for queryability

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Working backwards—Design for queryability

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Working backwards—Design for queryability

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Working backwards—Design for queryability

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Working backwards—Design for queryability

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Working backwards—Design for queryability

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Use property graph primitives to build your model
Vertices
Entities (things with identity, complex value types)
Properties Entity attributes + metadata
Labels Roles, grouping, tagging
Edges
Relationships between entities, variable structure
Properties Relationship strength, weight, or property + metadata
Labels Relationship semantics

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Vertex and edge IDs
Neptune will create UUID IDs for new vertices and edges
Alternatively, you can supply your own string-based IDs
All vertex IDs must be unique
All edge IDs must be unique
You must supply your own IDs when bulk loading data
You can also create id properties
Avoid doing this: it creates confusion

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Labels
Tags, keyless properties
Typically used to “type” a vertex, or name a relationship
Vertices must have one or more labels
Neptune will create a “vertex” label if you don’t supply one
Edges must have exactly one label

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Edges—The routes to success
Performance depends on how much of the graph a query must “touch”
Choose domain-meaningful edge labels
Discover only what is absolutely necessary
“Grey out” unnecessary portions of the graph

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How fine-grained should my edge labels be?
Is it an open or extensible set of label values?
Do you need to query across values in the set? (for example, all addresses)

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Bi-directional relationships
Ignore edge direction in queries g.V().hasLabel('Person').
both('FRIENDS')

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Uni-directional relationships
Be explicit about edge direction in queries g.V().hasLabel('Person').
out('FOLLOWS’)
g.V().hasLabel('Person').
in('FOLLOWS')

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Multiple edges between vertices

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You can even have self-edges

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Example scenario
Employment history application
People, companies, roles
Use cases
1. Find the companies where X has worked, and their roles at those companies
2. Find the people who have worked for a company at a specific location during a particular
time period
3. Find the people in more senior roles at the companies where X worked

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What questions would we have to ask of our data?
Find the companies where X has worked, and their roles at those
companies
Which companies has X worked for, and in what roles?

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Identify entities, relationships, and attributes
Find the companies where X has worked, and their roles at those
companies
Which companies has X worked for, and in what roles?
Companies Company Entity
X Person Entity
Worked for Worked for Relationship
Roles Role Attribute?

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Identify candidate vertices, labels, and properties
Company Entity Vertex Company
Person Entity Vertex Person
Worked for Relationship Edge WORKED_FOR
Role Attribute? Property? role
name
CompanyPerson

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Entity or attribute? Vertex or property?
Is role an entity or an attribute?
Does it have identity (or is it a value type)? X
Is it a complex type (with multiple fields)? X
Are there any structural relations between values? ?
Keep it simple
Prefer properties to vertices/edges until the need arises

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Model 1

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Traversal 1
Which companies has Li worked for, and in what roles?

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Create dataset
(g.
addV('Person').property(id,'p-1').property('firstName','Martha').property('lastName','Rivera').
addV('Person').property(id,'p-2').property('firstName','Richard').property('lastName','Roe').
addV('Person').property(id,'p-3').property('firstName','Li').property('lastName','Juan').
addV('Person').property(id,'p-4').property('firstName','John').property('lastName','Stiles').
addV('Person').property(id,'p-5').property('firstName','Saanvi').property('lastName','Sarkar').
addV('Company').property(id,'c-1').property('name','Example Corp').
addV('Company').property(id,'c-2').property('name','AnyCompany').
V('p-1').addE('WORKED_FOR').to(V('c-1')).property('role','Principal Analyst').
V('p-2').addE('WORKED_FOR').to(V('c-1')).property('role','Senior Analyst').
V('p-3').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-4').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-5').addE('WORKED_FOR').to(V('c-2')).property('role','Manager').
V('p-3').addE('WORKED_FOR').to(V('c-2')).property('role','Associate Analyst').
toList())

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Create dataset
(g.
addV('Person').property(id,'p-1').property('firstName','Martha').property('lastName','Rivera').
addV('Person').property(id,'p-2').property('firstName','Richard').property('lastName','Roe').
addV('Person').property(id,'p-3').property('firstName','Li').property('lastName','Juan').
addV('Person').property(id,'p-4').property('firstName','John').property('lastName','Stiles').
addV('Person').property(id,'p-5').property('firstName','Saanvi').property('lastName','Sarkar').
addV('Company').property(id,'c-1').property('name','Example Corp').
addV('Company').property(id,'c-2').property('name','AnyCompany').
V('p-1').addE('WORKED_FOR').to(V('c-1')).property('role','Principal Analyst').
V('p-2').addE('WORKED_FOR').to(V('c-1')).property('role','Senior Analyst').
V('p-3').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-4').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-5').addE('WORKED_FOR').to(V('c-2')).property('role','Manager').
V('p-3').addE('WORKED_FOR').to(V('c-2')).property('role','Associate Analyst').
toList())

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Create dataset
(g.
addV('Person').property(id,'p-1').property('firstName','Martha').property('lastName','Rivera').
addV('Person').property(id,'p-2').property('firstName','Richard').property('lastName','Roe').
addV('Person').property(id,'p-3').property('firstName','Li').property('lastName','Juan').
addV('Person').property(id,'p-4').property('firstName','John').property('lastName','Stiles').
addV('Person').property(id,'p-5').property('firstName','Saanvi').property('lastName','Sarkar').
addV('Company').property(id,'c-1').property('name','Example Corp').
addV('Company').property(id,'c-2').property('name','AnyCompany').
V('p-1').addE('WORKED_FOR').to(V('c-1')).property('role','Principal Analyst').
V('p-2').addE('WORKED_FOR').to(V('c-1')).property('role','Senior Analyst').
V('p-3').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-4').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-5').addE('WORKED_FOR').to(V('c-2')).property('role','Manager').
V('p-3').addE('WORKED_FOR').to(V('c-2')).property('role','Associate Analyst').
toList())

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Create dataset
(g.
addV('Person').property(id,'p-1').property('firstName','Martha').property('lastName','Rivera').
addV('Person').property(id,'p-2').property('firstName','Richard').property('lastName','Roe').
addV('Person').property(id,'p-3').property('firstName','Li').property('lastName','Juan').
addV('Person').property(id,'p-4').property('firstName','John').property('lastName','Stiles').
addV('Person').property(id,'p-5').property('firstName','Saanvi').property('lastName','Sarkar').
addV('Company').property(id,'c-1').property('name','Example Corp').
addV('Company').property(id,'c-2').property('name','AnyCompany').
V('p-1').addE('WORKED_FOR').to(V('c-1')).property('role','Principal Analyst').
V('p-2').addE('WORKED_FOR').to(V('c-1')).property('role','Senior Analyst').
V('p-3').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-4').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-5').addE('WORKED_FOR').to(V('c-2')).property('role','Manager').
V('p-3').addE('WORKED_FOR').to(V('c-2')).property('role','Associate Analyst').
toList())

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Create dataset
(g.
addV('Person').property(id,'p-1').property('firstName','Martha').property('lastName','Rivera').
addV('Person').property(id,'p-2').property('firstName','Richard').property('lastName','Roe').
addV('Person').property(id,'p-3').property('firstName','Li').property('lastName','Juan').
addV('Person').property(id,'p-4').property('firstName','John').property('lastName','Stiles').
addV('Person').property(id,'p-5').property('firstName','Saanvi').property('lastName','Sarkar').
addV('Company').property(id,'c-1').property('name','Example Corp').
addV('Company').property(id,'c-2').property('name','AnyCompany').
V('p-1').addE('WORKED_FOR').to(V('c-1')).property('role','Principal Analyst').
V('p-2').addE('WORKED_FOR').to(V('c-1')).property('role','Senior Analyst').
V('p-3').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-4').addE('WORKED_FOR').to(V('c-1')).property('role','Analyst').
V('p-5').addE('WORKED_FOR').to(V('c-2')).property('role','Manager').
V('p-3').addE('WORKED_FOR').to(V('c-2')).property('role','Associate Analyst').
toList())

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Write a test
Sample data and code
Amazon SageMaker Jupyter notebooks
AWS Cloud9 cloud IDE
Gremlin console
Unit tests
Bedrock of asserted behavior
Fast feedback as you evolve your model

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Unit test
%%unittest
results = None # Which companies has Li worked for, and in what roles?
assert results == [{'company': 'Example Corp', 'role': 'Analyst'},
{'company': 'AnyCompany', 'role': 'Associate Analyst’}]
Fail
AssertionError: None != [{'company': 'Example Corp', 'role': 'Analyst'},
{'company': 'AnyCompany', 'role': 'Associate Analyst'}]

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Gremlin query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()

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Gremlin query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()

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Gremlin query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()

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Gremlin query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()

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Gremlin query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()

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Gremlin query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()

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Gremlin query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()

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Unit test
%%unittest
results = (g.V('p-3').
outE('WORKED_FOR').as_('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList())
assert results == [{'company': 'Example Corp', 'role': 'Analyst'},
{'company': 'AnyCompany', 'role': 'Associate Analyst'}]

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49. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
What questions would we have to ask of our data?
Find the people who have worked for a company at a specific location
during a particular time period
Who worked for company X, and at which locations, between Y1-Y2?

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Entities, relationships, and attributes
Find the people who have worked for a company at a specific location
during a particular time period
Who worked for company X, and at which locations, between Y1-Y2?
Locations Location Entity?
Y1-Y2 Date range or Attributes
dates (from and to)?

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Entity or attribute? Vertex or property?
Is location an entity or an attribute?
Does it have identity (or is it a value type)? ✓
Is it a complex type (with multiple fields)? ✓
Are there any structural relations between values? ?
Model location as a vertex

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We can’t ”attribute” an edge with a vertex
name
CompanyPerson
Location

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Introduce an intermediate vertex
name
CompanyPerson
Location
???

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Revised model
Represent facts/events as vertices
Connect to multiple dimensions
name
CompanyPerson
Location
Job

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Model 2

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Traversal 2
Who worked for Example Corp., and at which locations, between 2015-
2017?

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Gremlin query 2
g.V('c-1').
in('COMPANY').
or(
(has('from', between(datetime(2015,1,1), datetime(2018,1,1)))),
(has('to', between(datetime(2015,1,1), datetime(2018,1,1))))
).
project('name', 'location').
by(in('JOB').values('firstName', 'lastName').fold()).
by(out('LOCATION').values('name', 'address').fold()).
toList()

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Gremlin query 2
g.V('c-1').
in('COMPANY').
or(
(has('from', between(datetime(2015,1,1), datetime(2018,1,1)))),
(has('to', between(datetime(2015,1,1), datetime(2018,1,1))))
).
project('name', 'location').
by(in('JOB').values('firstName', 'lastName').fold()).
by(out('LOCATION').values('name', 'address').fold()).
toList()

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Gremlin query 2
g.V('c-1').
in('COMPANY').
or(
(has('from', between(datetime(2015,1,1), datetime(2018,1,1)))),
(has('to', between(datetime(2015,1,1), datetime(2018,1,1))))
).
project('name', 'location').
by(in('JOB').values('firstName', 'lastName').fold()).
by(out('LOCATION').values('name', 'address').fold()).
toList()

60. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 2
g.V('c-1').
in('COMPANY').
or(
(has('from', between(datetime(2015,1,1), datetime(2018,1,1)))),
(has('to', between(datetime(2015,1,1), datetime(2018,1,1))))
).
project('name', 'location').
by(in('JOB').values('firstName', 'lastName').fold()).
by(out('LOCATION').values('name', 'address').fold()).
toList()

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Gremlin query 2
g.V('c-1').
in('COMPANY').
or(
(has('from', between(datetime(2015,1,1), datetime(2018,1,1)))),
(has('to', between(datetime(2015,1,1), datetime(2018,1,1))))
).
project('name', 'location').
by(in('JOB').values('firstName', 'lastName').fold()).
by(out('LOCATION').values('name', 'address').fold()).
toList()

62. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 2
g.V('c-1').
in('COMPANY').
or(
(has('from', between(datetime(2015,1,1), datetime(2018,1,1)))),
(has('to', between(datetime(2015,1,1), datetime(2018,1,1))))
).
project('name', 'location').
by(in('JOB').values('firstName', 'lastName').fold()).
by(out('LOCATION').values('name', 'address').fold()).
toList()

63. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 2
g.V('c-1').
in('COMPANY').
or(
(has('from', between(datetime(2015,1,1), datetime(2018,1,1)))),
(has('to', between(datetime(2015,1,1), datetime(2018,1,1))))
).
project('name', 'location').
by(in('JOB').values('firstName', 'lastName').fold()).
by(out('LOCATION').values('name', 'address').fold()).
toList()

64. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
We’ve broken query 1!
%%unittest
results = (g.V('p-3').
outE('WORKED_FOR').as_('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList())
assert results == [{'company': 'Example Corp', 'role': 'Analyst'},
{'company': 'AnyCompany', 'role': 'Associate Analyst’}]
Fail
AssertionError: Lists differ: [] != [{'company': 'Example Corp', 'role': 'Analyst'},
{'company': 'AnyCompany', 'role': 'Associate Analyst'}]

65. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Revised query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()
g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by('role').
toList()

66. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Revised query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()
g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by('role').
toList()

67. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Revised query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()
g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by('role').
toList()

68. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Revised query 1
g.V('p-3').
outE('WORKED_FOR').as('e').
otherV().
project('company', 'role').
by('name').
by(select('e').values('role')).
toList()
g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by('role').
toList()

69. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

70. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
What questions would we have to ask of our data?
Find the people in more senior roles at the companies where X worked
Who were in senior roles at the companies where X worked?

71. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Entities, relationships, and attributes
Find the people in more senior roles at the companies where X worked
Who were in more senior roles at the companies where X worked?
Senior Roles Role Entity?

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Entity or attribute? Vertex or property?
Is role an entity or an attribute?
Does it have identity (or is it a value type)? X
Is it a complex type (with multiple fields)? X
Are there any structural relations between values? ✓
Model structural relations with edges
Promote role to being a vertex

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Role hierarchy
Role
Role Role

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Revised model
name
CompanyPerson
Location
Job
Role

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Model 3

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Traversal 3
Who were in more senior roles at the companies where Li worked?

77. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Create data to test predicates

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Create data to test predicates
assert results == [{'role': 'Principal Analyst', 'name': ['Martha', 'Rivera']},
{'role': 'Manager', 'name': ['Saanvi', 'Sarkar']}]

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Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

80. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

81. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

82. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

83. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

84. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

85. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

86. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

87. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Gremlin query 3
g.V('p-3').
out('JOB').as('j1').
out('ROLE').
repeat(out('PARENT_ROLE')).until(outE().count().is(0)).
emit().in('ROLE').as('j2').
or(
(where('j1', between('j2', 'j2')).by('from').by('from').by('to')),
(where('j1', between('j2', 'j2')).by('to').by('from').by('to')),
(where('j1', lte('j2').and(gt('j2'))).by('from').by('from').by('to').by('from'))
).
project('role', 'name').
by(out('ROLE').values('name')).
by(in('JOB').values('firstName', 'lastName').fold()).
toList())

88. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
We’ve broken query 1 (again)!
%%unittest
results = (g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by('role').
toList())
assert results == [{'company': 'Example Corp', 'role': 'Analyst'},
{'company': 'AnyCompany', 'role': 'Associate Analyst’}]
Fail
The property does not exist as the key has no associated value for the provided
element: v[j-3]:role

89. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Revised query 1
g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by('role').
toList()
g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by(out('ROLE').values('name')).
toList()

90. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Revised query 1
g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by('role').
toList()
g.V('p-3').
out('JOB').
project('company', 'role').
by(out('COMPANY').values('name')).
by(out('ROLE').values('name')).
toList()

91. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

92. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
What have we learned?
Work backwards from your use case to make a useful model
Start simple
Evolve as necessary
Your model should offer up the most efficient routes for your queries
The model is the superset of paths traversed by your queries
Use interactive development environments to develop your model and
queries
Write unit tests that give you fast feedback as you evolve your model

93. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
What have we learned?
• Work backwards from
your use case to make a
useful model
• Start simple and evolve
as necessary
• Your model should offer
up the most efficient
routes for your queries
• The model is the
superset of paths
traversed by your queries
• Use an interactive
environment to develop
your model and queries
• Write unit tests that give
you fast feedback as you
evolve your model

94. Thank you!
© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Ian Robinson
ianrob@amazon.com
Mike Personick
mprsnck@amazon.com

95. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.