2012 11-28 rich web data modeling with graphs-1

Data modeling
. . . with graphs

@PeterBell
Wednesday, November 28, 12

- Terminology
- Examples
- Patterns
- Key takeaways

Agenda

Terminology


relational database

tables
columns
records
foreign keys


neo4j

nodes
relationships
properties


indexes


traversals


Cypher


OO language - domain objects
Object (graph|relational) mapping

Java domain objects Java domain objects
Hibernate Spring Data Neo4j
SQL Cypher
Tables/rows/columns/FKs Nodes/relationships/properties


Examples


Article
CATEGORIZED_UNDER WRITTEN_BY

ADDED_TO
Category Author
Comment
WRITTEN_BY
FOLLOWS
Commenter


Geographic


Bioinformatic


Patterns


start with a whiteboard


Handling entities


...provide a familiar and consistent Spring
based programming model while retaining
store speciﬁc features and capabilities

Restaurant
- name
- address
- cuisine

- comment
RECOMMENDS_THE
- rating

User
- ﬁrst_name
- last_name


Restaurant
- name
- address
- cuisine

RECOMMENDS_A - comment
- rating

User
- ﬁrst_name
- last_name


Restaurant SERVES
- name Cuisine
- address

- comment
RECOMMENDS_THE
- rating

User
- ﬁrst_name
- last_name


SERVES
Taj Mahal Indian cuisine

- “Great garlic nan and tandoori”
RECOMMENDS
- 4/5

Fred Jones


read sentences from graph


Indexes for starting points


User
- email_address
- ﬁrst_name
- last_name


Relationships for querying


User
- email_address
- ﬁrst_name
- last_name
- shipping_state

Select * where shipping_state = ‘Ca’?


User State
- email_address LIVES_IN - name
- ﬁrst_name
- code
- last_name


Jess
LIVES_IN

California
LIVES_IN

LIVES_IN
Andreas

Andrew


Use meaningful names


Language Country
- language_id
- country_id
- name
- name
- word count
- ﬂag url
- country_id


Language LanguageCountry Country
- language_id - language_id - country_id
- name - country_id - name
- word count - spoken_since - ﬂag url


Language Country
IS_SPOKEN_IN
- name - name
- word count - ﬂag url


Language Country
IS_SPOKEN_IN
- name - name
- word count - ﬂag url

SIMILAR_TO ADJACENT_TO

Anti-Patterns


Hefty nodes


User

- ﬁrst_name
- ship_address
- last_name
- ship_city
- email_address
- ship_state
- bill_address
- ship_zip
- bill_city
- regular_customer
- bill_state
- bill_zip


BILLS_TO Address
User
- ﬁrst_name - street_address
- last_name - city
- email_address - state
- regular_customer SHIPS_TO - zip


BILLS_TO
User Address
- ﬁrst_name - street_address
- last_name SHIPS_TO - city
- email_address - state
- zip

IS_A

Regular customer

Jess
IS_A

Regular
customer IS_A
IS_A
Andreas

Andrew


Missing nodes


EMAILED
Peter Jim


SENT TO
Peter Email Jim


Hot node


Key takeaways


Indexes for starting points
Relationships for queries
Read sentences from the graph
Look out for verb’d nouns


- Indexes for starting points
- Relationships for queries
- Read sentences from the graph
- Look out for verb’d nouns

Data modeling with graphs @PeterBell

2012 11-28 rich web data modeling with graphs-1

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2012 11-28 rich web data modeling with graphs-1