Analytics that traverse large portions of large graphs have been problematic for both RDF and LPG graph engines. In this webinar Barry Zane, former co-founder of Netezza, Paraccel and SPARQL City and current VP of Engineering at Cambridge Semantics, discusses the native parallel-computing approach taken in AnzoGraph to yield interactive, scalable performance for RDF and LPG graphs.

1. Large Scale Graph Analytics
with RDF and LPG Parallel Processing
Presenter:
Barry Zane, VP Engineering

4. ©2018 Cambridge Semantics Inc. All rights reserved.
Agenda
•Quick Review of RDF/SPARQL
•International W3C standard
•Making RDF/SPARQL a full Property Graph database
•Now better than other Property Graph approaches
•OLAP systems complimentary to OLTP systems
•One size does not fit all - you need OLTP for end-user transactions, OLAP
for analytics
•Features needed in OLAP systems not found in OLTP systems
•Big data is about inferences and aggregate insights

5. ©2018 Cambridge Semantics Inc. All rights reserved.
Quick Review of W3C Standard RDF/SPARQL 1.1
•RDF - Resource Description Framework
•Atomic “triples” describe anything
•Subject, Predicate, Object
•<Jack> <wentUp> <TheHill>
•SPARQL - SPARQL Protocol and RDF Query Language
•Declarative, like SQL
•As expressive as SQL
•Can do things SQL can’t do
•Multi-Graph
• Could use more SQL-like Analytics
• Could use more Graph Algorithms
•Needs a better way to describe properties of edges!

6. ©2018 Cambridge Semantics Inc. All rights reserved.
A Basic Graph
3 Vertexes, 3 Edges
friendOf
wentUp
isA: <Man>
birthday: 09/17/1975
Jack isA: <Woman>
Jill
TheHill
isA: <Place>
has: Water
has: Trees
partOf: <TheMountain>
wentUp
Subject Predicate Object
<Jack> <isA> <Man>
<Jack> <Birthday> “09/17/1975”^^date
<Jack> <friendOf> <Jill>
<Jack> <wentUp> <TheHill>
<Jill> <isA> <Woman>
<Jill> <wentUp> <TheHill>
<TheHill> <isA> <Place>
<TheHill> <has> “Water”
<TheHill> <has> “Trees”
<TheHill> <partOf> <TheMountain>
<Man> <subClassOf> <Human>
<Man> <gender> “Male”
<Woman> <subClassOf> <Human>
<Woman> <gender> “Female”
<friendOf> <property> “Reflexive”
<Human> <subClassOf> <Animal>
Everything is an atomic Triple that specify properties on Entities

7. ©2018 Cambridge Semantics Inc. All rights reserved.
Let’s Add Edge Properties
friendOf
metAt=<TheHill>
metDate=07/04/2018
wentUp
date=‘today’
isA: <Man>
birthday: 09/17/1975
Jack isA: <Woman>
Jill
TheHill
isA: <Place>
has: Water
has: Trees
partOf: <TheMountain>
wentUp
date=‘today’
Since triples specify properties
on Vertexes, how to we specify
properties on Edges…
… how do we specify properties
on triples?

8. ©2018 Cambridge Semantics Inc. All rights reserved.
The “Reification” Approach to Properties - Don’t Do This!
•Mathematically Pure
•Hard to Write Queries
•Wastes Storage
•Runs Slowly
Subject Predicate Object
<Jack> <isA> <Man>
<Jack> <Birthday> “09/17/1975”^^date
<Jack> <friendOf> <Jill>
<Jack> <wentUp> <TheHill>
Subject Predicate Object
<Jack> <isA> <Man>
<Jack> <Birthday> “09/17/1975”^^date
<Relationship1> <subject> <Jack>
<Relationship1> <predicate> <friendOf>
<Relationship1> <object> <Jill>
<Relationship1> <metAt> <TheHill>
<Relationship1> <metDate> “07/14/2018”
<Activity1> <subject> <Jack>
<Activity1> <predicate> <wentUp>
<Activity1> <object> <TheHill>
<Activity1> <date> “today”
We’ve turned verbs “likes” and “wentUp” into noun-sets “Relationship1” and “Activity1” !!!
In other words, these edges become vertexes.

9. ©2018 Cambridge Semantics Inc. All rights reserved.

10. ©2018 Cambridge Semantics Inc. All rights reserved.
RDF* (aka Reification Done Right) and SPARQL*
friendOf
metAt=<TheHill>
metDate=07/04/2018
wentUp
date=‘today’
isA: <Man>
birthday: 09/17/1975
Jack isA: <Woman>
Jill
TheHill
isA: <Place>
has: Water
has: Trees
partOf: <TheMountain>
wentUp
date=‘today’
Subject Predicate Object
<Jack> <isA> <Man>
<Jack> <Birthday> “09/17/1975”^^date
<Jack> <friendOf> <Jill>
<<<Jack> <friendOf> <Jill>>> <metAt> <TheHill>
<<<Jack> <friendOf> <Jill>>> <metDate> “07/04/2018”^^date
<Jack> <wentUp> <TheHill>
<<<Jack> <wentUp> <TheHill>>> <date> “today”^^date
<Jill> <isA> <Woman>
<Jill> <wentUp> <TheHill>
<<<Jill> <wentUp> <TheHill>>> <date> “today”^^date
<TheHill> <isA> <Place>
<TheHill> <has> “Water”
<TheHill> <has> “Trees”
<TheHill> <partOf> <TheMountain>
<Man> <subClassOf> <Human>
<Man> <gender> “Male”
<Woman> <subClassOf> <Human>
<Woman> <gender> “Female”
<likes> <property> “Reflexive”
<Human> <subClassOf> <Animal>

11. ©2018 Cambridge Semantics Inc. All rights reserved.
Even More Powerful Than Other Property Graph Approaches
isA: <Man>
birthday: 09/17/1975 AccordingTo: MotherGoose
birthday: 06/12/1975 AccordingTo: Aesop
birthday: 06/12/1975 AccordingTo: Grimm
Jack
Subject Predicate Object
<Jack> <isA> <Man>
<Jack> <birthday> “09/17/1975”^^date
<Jack> <birthday> “06/12/1975”^^date
<<<Jack> <birthday> 09/17/1975>> <accordingTo><MotherGoose
>
<<<Jack> <birthday> 06/12/1975>> <accordingTo><Aesop>
<<<Jack> <birthday> 06/12/1975>> <accordingTo><Grimm>
Properties, such as provenance,
can be applied to Vertexes,
not just edges!!!

12. ©2018 Cambridge Semantics Inc. All rights reserved.
RDF*/SPARQL* Acknowledgements
•Extends RDF and SPARQL - https://www.w3.org/TR/sparql11-query/
•Specification and Model Created by:
•Olaf Hartig, Linköping University, Sweden
•Bryan Thompson
•First implemented by Blazegraph
•https://arxiv.org/pdf/1406.3399.pdf
•https://arxiv.org/pdf/1409.3288.pdf
•AnzoGraph is the first OLAP-oriented Graph Database to use this approach for handling rich
data

13. ©2018 Cambridge Semantics Inc. All rights reserved.
Inferences - RDFS, RDFS+, OWL
friendOf
wentUp
isA: <Man>
birthday: 09/17/1975
gender: Male
isA: Human
Jack
isA: <Woman>
gender: Female
isA: Human
Jill
TheHill
isA: <Place>
has: Water
has: Trees
partOf: <TheMountain>
wentUp
Everything is an atomic Triple that specify properties on Entities
friendOf
•Automatically adds new triples.
•Triggered and controlled by other
triples in the dataset
•RDFS - Basic Inferences
•RDFS+ - Popular Extensions
•OWL - Most complete
•Used for:
•Simplifying queries
•Harmonizing datasets
•Formalizing relationships
•Keeps load files normalized
•Denormalization

14. ©2018 Cambridge Semantics Inc. All rights reserved.
How OLAP Adds to the OLTP World
•Key functionality
•Windowed Aggregates
•CUBE, ROLLUP, Grouping Sets
•80+ added scalar functions and aggregates
•Named Queries for re-use of prior work
•Views for re-use and providing alternate perspectives
•Native, Parallel Processing for Query Performance
•“Tell me about populations and trends”
•Not just “Tell me about Jack”

15. ©2018 Cambridge Semantics Inc. All rights reserved.
Where the rubber meets the road…
•Let’s write some queries!!!
•Anzo customers generally use the “point and click” interface of Anzo
HiRes to automatically write their queries.
•AnzoGraph customers write SPARQL* queries, so let’s do so…
•There will not be a quiz.

16. ©2018 Cambridge Semantics Inc. All rights reserved.
Example OLTP Queries (1)
SELECT $person $place
WHERE {
$person <wentUp> $place
}
person | place
--------+---------
Jack | TheHill
Jill | TheHill
Who went up places? (generic search)
How are Jack and Jill related? (OLTP)
SELECT $relationship
WHERE {
<Jack> $relationship <Jill>
}
relationship
--------------
friendOf

17. ©2018 Cambridge Semantics Inc. All rights reserved.
Example OLAP Queries (2)
What are the most common relationships among people? (OLAP, Inference)
SELECT $relationship (COUNT(*) AS $count)
WHERE {
$person1 <isA> <Human> .
$person2 <isA> <Human> .
$person1 $relationship $person2
}
GROUP BY $relationship
ORDER BY DESC($count) LIMIT 10
relationship | count
--------------+-------
friendOf | 2
What are the most popular dates to go places? (OLAP, RDF*)
date | count | place
------------+-------+---------
2018-09-15 | 2 | TheHill
SELECT $date (COUNT(*) AS $count) $place
WHERE {
<< $person <wentUp> $place >> <date> $date
}
GROUP BY $place $date
ORDER BY DESC($count) LIMIT 10

18. ©2018 Cambridge Semantics Inc. All rights reserved.
Example Graph Algorithm Query (3)
Who are the most popular people? (PageRank)
SELECT $person $rank
FROM <tickit>
WHERE {
SERVICE <csi:page_rank> {
[] <csi:binding-vertex> $person;
<csi:binding-rank> $rank;
<csi:edge-label> <friend>;
<csi:max-iterations> 20;
}
}
ORDER BY DESC($rank) $person
LIMIT 5
person | rank
-------------+----------
person23501 | 1.807055
person16101 | 1.748871
person3083 | 1.746725
person19289 | 1.736759
person36749 | 1.731948

19. ©2018 Cambridge Semantics Inc. All rights reserved.
What Did We Learn?
•RDF/SPARQL is an International W3C Standard that describes how
Graph Databases should be managed and queried.
•The RDF*/SPARQL* extensions to the standard make RDF/SPARQL
databases even more capable.
•One size does not fit all - you need OLTP for end-user transactions,
OLAP for analytics
•OLAP database systems require capabilities irrelevant to OLTP
databases.

20. ©2018 Cambridge Semantics Inc. All rights reserved.
Next Step: Download free 60-day trial at AnzoGraph.com

21. ©2017 Cambridge Semantics Inc. All rights reserved.
Questions?