The newly released Neo4j Connector for Apache Spark can be used to read and write data between the two systems. In this demo I show how to use the investigative Data from the FinCEN files to have a full pipeline up an running. Notebook is in https://github.com/jexp/fincen

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Analytics & Graphs:
Neo4j Connector for Apache Spark

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Michael Hunger
Director Developer Relations
Java Champion
Twitter: @mesirii
medium.com/@mesirii
github.com/jexp

3. Connections in Data are as
Valuable as the Data Itself
Networks of People Transaction Networks Knowledge Networks
E.g., Risk management, Supply
chain, Payments
E.g., Employees, Customers,
Suppliers, Partners,
Influencers
E.g., Enterprise content,
Domain specific content,
eCommerce content

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The FinCEN files?
obtained and published Suspicious Activity Reports (SARs)
submitted by global financial institutions to the

6. ● Insider trading
● Transactions linked to money laundering,
terrorism financing or other crimes.
● Odd dealings, also involving shell companies
● Transactions by individuals known or suspected to have links to
criminal or terrorist organizations, or on sanction lists
These activities are required to be reported WITHIN 30-60 days.
In the FinCEN files - this is rarely the case.
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Suspicious Activity
Reports

7. Property Graph - Simply Powerful
Entity
Sender
Entity
Receiver
Nodes represent
objects (nouns)
Relationships are directional
Relationships connect nodes
are represent actions (verbs)
Relationships can have
properties (name/value pairs)
Nodes can have
properties
(name/value pairs)
name: A Global Bank
address: New York City
amount: 1208209000
date: 2015-03-01
name: A Shady Bank
address: n/a
:TRANSFERRED

8. Analytics
Tooling
Graph Transactions
Data Integration
Dev.
& Admin
Drivers & APIs Discovery & Visualization
Graph Analytics &
Data Science
Developers
Admins
Applications Business Users
Data Analysts
Data Scientists
Native Graph Technology for Applications & Analytics

9. for Graph Data Science™
Graph Data Science
Embeddings Prediction
Centralities Pathfinding
Clustering
Scalable Graph Algorithms &
Analytics Workspace
Native Graph
Creation & Persistence
Neo4j
Database
Visual Graph Exploration
& Prototyping
Neo4j
Bloom
Practical Integrated Intuitive
neo4j.com/graph-data-science

10. 10
Big Picture

11. Simplest Examples (Python)
Read Write
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spark.read.format("org.neo4j.spark.DataSource")
.option("url", "bolt://localhost:7687")
.option("labels", "Entity").load()
# Custom Cypher Query
spark.read.format("org.neo4j.spark.DataSource")
.option("url", "...")
.option("query",
"MATCH (n:Entity) RETURN n.id as id")
.load().show(10)
df.write.format("org.neo4j.spark.DataSource")
.mode("Overwrite")
.option("url", "...")
.option("labels", ":Entity").save()
# Custom Cypher Query
df.write.format("org.neo4j.spark.DataSource")
.option("url", "...")
.option("query",
"CREATE (:Entity {id: event.id})")
.save()

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Demo
Pipeline
SQL
Nodes
Table
Relationships
DF
DFML-Compute GRAPH
COMPUTE
LOADCSV

13. Demo
13

14. Source CSV Data (Filings)
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15. Save Graph
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16. Show Graph
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17. Check Graph
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18. Compute Graph - Centralities
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19. Compute Graph - Clustering/Embeddings
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Next:
Graph-Embeddings
KNN Similarity
Train ML-Models
neo4j.com/graph-data-science

21. Free O'Reilly Book
neo4j.com/books
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Connector: neo4j.com/developer/spark
Sandbox: neo4j.com/try-neo4j
Notebook: github.com/jexp/fincen

23. Thank You!
Questions?
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