Gluecon InfiniteGraph Presentation: Scaling the Social Graph in the Cloud

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Darren Wood, InfiniteGraph Lead Architect, addresses the developer audience at Glue Conference 2010 in Colorado (May 27, 2010), where he discusses the technical challenges to running queries traversing relationships to 4, 5 or more degrees of separation, across extremely large graph datasets in the cloud.

Technology

Complex graph traversal
across large, distributed datasets

Glue Conference 2010, Colorado
Darren Wood, Lead Architect
InfiniteGraph

Copyright © InfiniteGraph

Scaling the [Social] Graph
in the [Cloud]
Darren Wood
Lead Architect, InfiniteGraph

Graph Databases (Quickly)
• Optimized around data relationships
• Small focused API (typically not SQL)
• Typical Use Cases :
– Social Graph Analysis
– Catching Bad Guys (see Booth 16)
– Fraud / Financial (more bad guys)
– Data Intensive Science
– Web / Advertising Analytics

Copyright © InfiniteGraph

Graph Databases (Almost Done)
Vertex alice = myGraph.addVertex(new Person(“Alice”));
Vertex bob = myGraph.addVertex(new Person(“Bob”));
Vertex carlos = myGraph.addVertex(new Person(“Carlos”));
Vertex charlie = myGraph.addVertex(new Person(“Charlie”));

alice.addEdge(new Meeting(“Denver”, “5-27-10”), bob);
bob.addEdge(new Call(timestamp), carlos);
carlos.addEdge(new Payment(100000.00), charlie);
bob.addEdge(new Call(timestamp), charlie);

Alice Bob Carlos Charlie
Meets Calls Pays

Calls

Copyright © InfiniteGraph

What’s So Difficult Then ?
• Graphs grow quickly
– Billions of phone calls / day in US
– Emails, social media events, IP Traffic
– Financial transactions
• Some analytics require navigation of large
sections of the graph
• Each step (often) depends on the last
• Must distribute data and go parallel
Copyright © InfiniteGraph

First Some Good News…
• Graph algorithms naturally branch
• Can be automated or guided

Bob Carlos Charlie
Meets Calls Pays

Alice

Calls
Chuck Dave Eve
Lives Meets
With

Copyright © InfiniteGraph

Big Distributed Data
(Traditional - Huge Generalization)

Application(s)

Distributed API

Processor Processor Processor Processor

Partition 1 Partition 2 Partition 3 Partition ...n

Copyright © InfiniteGraph

Big Distributed Data
(Graph)

Application(s)

Distributed API

Processor Processor Processor Processor

Partition 1 Partition 2 Partition 3 Partition ...n

Copyright © InfiniteGraph

So What Are The Answers?
Best Effort Partitioning

Distributed API

Processor Processor

Partition 1 Partition 2

Copyright © InfiniteGraph

So What Are The Answers?
The Look Ahead Example

Application

Distributed API

Processor Processor

A C

D
B
E

Y
X

Partition 1 Partition 2

Copyright © InfiniteGraph

Which of These Work ?
• A carefully orchestrated combination of
various options 
• Can be tuned (degree of look ahead)
• Healing graph can be expensive (write cost)
• This can also be tuned/configured (external
edge thresholds)

Copyright © InfiniteGraph

Thankyou !
darren.wood@infinitegraph.com

twitter.com/infinitegraph

Copyright © InfiniteGraph

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💥 You’re lucky! We’ve found two different (lead) developers that are willing to share their valuable lessons learned about using UiPath Document Understanding! Based on recent implementations in appealing use cases at Partou and SPIE. Don’t expect fancy videos or slide decks, but real and practical experiences that will help you with your own implementations. 📕 Topics that will be addressed: • Training the ML-model by humans: do or don't? • Rule-based versus AI extractors • Tips for finding use cases • How to start 👨‍🏫👨‍💻 Speakers: o Dion Morskieft, RPA Product Owner @Partou o Jack Klein-Schiphorst, Automation Developer @Tacstone Technology

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Dubai, often portrayed as a shimmering oasis in the desert, faces its own set of challenges, including the occasional threat of flooding. Despite its reputation for opulence and modernity, the emirate is not immune to the forces of nature. In recent years, Dubai has experienced sporadic but significant floods, testing the resilience of its infrastructure and communities. Among the critical lifelines in this bustling metropolis is the Dubai International Airport, a bustling hub that connects the city to the world. This article explores the intersection of Dubai flood events and the resilience demonstrated by the Dubai International Airport in the face of such challenges.

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Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows. We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases. This video focuses on the deployment of external web forms using Jotform for Bonterra Impact Management. This solution can be customized to your organization’s needs and deployed to support the common use cases below: - Intake and consent - Assessments - Surveys - Applications - Program registration Interested in deploying web form automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.

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Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

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EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

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2. Scaling the [Social] Graph in the [Cloud] Darren Wood Lead Architect, InfiniteGraph

3. Graph Databases (Quickly) • Optimized around data relationships • Small focused API (typically not SQL) • Typical Use Cases : – Social Graph Analysis – Catching Bad Guys (see Booth 16) – Fraud / Financial (more bad guys) – Data Intensive Science – Web / Advertising Analytics Copyright © InfiniteGraph

4. Graph Databases (Almost Done) Vertex alice = myGraph.addVertex(new Person(“Alice”)); Vertex bob = myGraph.addVertex(new Person(“Bob”)); Vertex carlos = myGraph.addVertex(new Person(“Carlos”)); Vertex charlie = myGraph.addVertex(new Person(“Charlie”)); alice.addEdge(new Meeting(“Denver”, “5-27-10”), bob); bob.addEdge(new Call(timestamp), carlos); carlos.addEdge(new Payment(100000.00), charlie); bob.addEdge(new Call(timestamp), charlie); Alice Bob Carlos Charlie Meets Calls Pays Calls Copyright © InfiniteGraph

5. What’s So Difficult Then ? • Graphs grow quickly – Billions of phone calls / day in US – Emails, social media events, IP Traffic – Financial transactions • Some analytics require navigation of large sections of the graph • Each step (often) depends on the last • Must distribute data and go parallel Copyright © InfiniteGraph

7. Big Distributed Data (Traditional - Huge Generalization) Application(s) Distributed API Processor Processor Processor Processor Partition 1 Partition 2 Partition 3 Partition ...n Copyright © InfiniteGraph

11. Which of These Work ? • A carefully orchestrated combination of various options  • Can be tuned (degree of look ahead) • Healing graph can be expensive (write cost) • This can also be tuned/configured (external edge thresholds) Copyright © InfiniteGraph

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