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Introduction to Graph Analytics and Oracle Cloud Service

Hans Viehmann Jean Ihm Korbi Schmid Product Manager EMEA Product Manager US Engineering Manager Oracle Oracle Oracle

@SpatialHannes @JeanIhm

October 22, 2018

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Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle’s products may change and remains at the sole discretion of Oracle Corporation.

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Program Agenda

Product Introduction

Use Cases

Feature Overview

Demo

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Following, no follow back

Follower, no follow back

Follow each other

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Oracle’s Spatial and Graph Strategy Enabling Spatial and Graph use cases on every platform

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Oracle Big Data Spatial and Graph

Oracle Database Spatial and Graph

Spatial and Graph in Oracle Cloud

Database Cloud Service Exadata Cloud Service

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Two Graph Data Models

RDF Data Model

• Data federation • Knowledge representation • Semantic Web

Social Network Analysis

 Financial  Retail, Marketing  Social Media  Smart Manufacturing

Linked Data Semantic Web

Property Graph Model

• Path Analytics • Social Network Analysis • Entity analytics

 Life Sciences  Health Care  Publishing  Finance

Use Case Graph Model Industry Domain

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Graph Database Features:

• Scalability, Performance, Security • Graph Analytics • Graph Query Language • Graph Visualization • Standard Interfaces • Integration with Machine Learning tools

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Courtesy Tom Sawyer Perspectives

Courtesy Linkurious

Courtesy Tom Sawyer Perspectives

Courtesy Linkurious

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Oracle Big Data Spatial and Graph

• Available for Big Data platform – Hadoop, HBase, Oracle NoSQL

• Supported both on BDA and commodity hardware – CDH and Hortonworks

• Database connectivity through Big Data Connectors or Big Data SQL

• Part of Big Data Cloud Service

Oracle Spatial and Graph (DB option)

• Available with Oracle 12.2/18c (EE) • Using tables for graph persistence • In-database graph analytics

– Sparsification, shortest path, page rank, triangle counting, WCC, sub graph generation…

• SQL and PGQL queries possible • Included in Database Cloud Services

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Oracle Products Supporting Property Graphs

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Use Cases

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Graph Analysis for Business Insight

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Identify Influencers

Discover Graph Patterns in Big Data

Generate Recommendations

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• Customer profitability analysis – Part of larger Hadoop/Big Data project

• Analysis of banking transactions – Focus on corporate customers

• Identification of undesired behavioural patterns, eg. – Customers using other banks to make large

numbers of transactions – Many of which flow back to Banco Galicia

• Increase fees, terminate contracts, or move activities to Banco Galicia

• Implemented by Oracle Consulting

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Banco de Galicia

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• Creating Knowledge Graphs from all kinds of content – Social media networks, documents, images,

audio, video, structured data – Using machine learning (text analysis,

classification, entity extraction, face recognition, speech2text, ...)

• Enabling relationship analysis and semantic search

• bigCONNECT platform built by mWARE – Running on Big Data Applicance, Big Data Cloud

Service or commodity Hadoop

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Romanian Police Force BIG DATA since 2012

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Ministry of Finance, Eastern Europe • Detecting relationships between people,

accounts, companies – Similar to Paradise Papers

• Identifying suspicious patterns – Circular money transfers – Connections (existing path/shortest path) to

companies in tax havens

• Ingesting accounting data in SAF-T format – Hadoop-based processing (Oozie, Spark, Hive) – Terabytes of data, rapidly growing

• Interactive graph analysis in Apex with Cytoscape.js

EU VAT fraud

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• Management of Bill-of-materials – Automotive manufacturing process – Supporting high variance and short

innovation cycles

• Data coming from various sources • Complex PGQL queries to associate

parts and subcomponents – Performance as key requirement – Happy with response times and

scaleability

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Mazda

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Feature Overview

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Oracle Graph Analytics Architecture

Scalable and Persistent Storage

Graph Storage Management

Graph Analytics In-memory Analytic Engine

Blueprints & SolrCloud / Lucene

Property Graph Support on Apache HBase, Oracle NoSQL or Oracle 12.2

REST W eb Service

Python, Perl, PHP, Ruby, Javascript, …

Java APIs

Java APIs/JDBC/SQL/PLSQL

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Interacting with the Graph

• Access through APIs – Implementation of Apache Tinkerpop Blueprints APIs – Based on Java, REST plus SolR Cloud/Lucene support for text search

• Scripting – Groovy, Python, Javascript, ... – Apache Zeppelin integration, Javascript (Node.js) language binding

• Graphical UIs – Cytoscape, plug-in available – Commercial Tools such as TomSawyer Perspectives

On-premise product geared towards data scientists and developers

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Example: Betweenness Centrality in Big Data Graph Code

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analyst.vertexBetweennessCentrality(pg) .getTopKValues(15)

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• Finding a given pattern in graph – Fraud detection – Anomaly detection – Subgraph extraction – ...

• SQL-like syntax but with graph pattern description and property access – Interactive (real-time) analysis – Supporting aggregates, comparison,

such as max, min, order by, group by

• Proposed for standardization by Oracle – Specification available on-line – Open-sourced front-end (i.e. parser)

Pattern matching in Property Graphs using PGQL

https://github.com/oracle/pgql-lang

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