Reduce IT challenges with Big Data by downloading the EMC Hadoop Starter Kit today to quickly deploy, manage and scale Hadoop clusters.

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Delivering Hadoop-as-a-Service To
Your Organization

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Why Hadoop?
Oil Exploration Medical
Imaging
Video SurveillanceMobile Sensors
Smart Grids
Social MediaInternet of Things
Dark Data
Fast and Cheap Way For Exploiting Massive Amounts of New Data Sources

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Why Hadoop?
Improve
Company
Performance
Increase Revenue
Increase Demand
Increase Spend
Efficiency
Ad
Optimization
Hyper
Targeting
Campaign
Optimization
Ad
Effectiveness
Analytics
Market Mix
Modeling
Coupon
Redemption
Increase
Customer
Acquisition
Purchase Funnel
Analysis
Increase Customer
Engagement
Customer
Segmentation
Churn Prevention
Customer Lifetime
Value
Increase Basket
Size
Affinity Analytics
Next Best Offer
Cross-Sell / Upsell
Manage Demand
Demand Analysis
Price Optimization
Build Brand Equity
Increase Reach
Digital Marketing
Social Media
Improve
Customer Loyalty
Social Graph /
Influencers
Loyalty Program
Analytics
Customer
Satisfaction
Customer Care
Analytics
Reduce Costs
Click Fraud
Transaction
Anomaly
Detection
Production Cost /
Efficiency
Supply / Demand
Forecasting
General and
Administrative
Workforce
Analytics
Employee Churn
IT / Security
Analytics
Save Money Or Make Money

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Hadoop Overview
Hadoop
is an open-source framework from Apache that allows
for parallel batch processing of very large data sets
MapReduce
is the Hadoop process that divides the workload so
multiple devices can process it
HDFS
is the file system for the data. It provides data
protection and locality with multiple mirrors (usually 3
times)

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IT Challenges With Hadoop
• Time consuming and complex creating
shadow IT
• Bare metal capacity utilization is low
• Multiple Hadoop Distribution deployments
creating data siloes

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Typical Enterprise Deployment
• Multiple, siloed
clusters to manage
• Redundant common
data in separate
clusters
• Peak compute and I/O
resource is limited to
number of nodes in
each independent
cluster
Production
Test
Experimentation
Dept A: Recommendation engine Dept B: Ad targeting
Production
Test
Experimentation
Log files
Social data
Historical cust behavior

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What If You Consolidate & Virtualize?
Production
Test
Production
Test
Experimentation Experimentation
One physical platform to support
multiple virtual big data clusters
Experimentation
Production
recommendation engine
Production
Ad Targeting
Test/Dev
Recommendation engine Ad targeting

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EMC Hadoop Starter Kit
• Support for major
Hadoop distributions
• Quickly deploy, manage,
and scale Hadoop
clusters
• GUI simplifies
management tasks
• Elastic scaling optimizes
cluster performance and
resource utilization
Consolidate And Virtualized Hadoop With EMC Isilon And Vmware
HDFS
NameNode
Data
name
node
name
node
name
node
name
node
datanode
Apache

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Why Shared Storage For Hadoop?

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Hadoop Bare Metals Deployment
Hadoop DAS Environment
1
Dedicated Storage Infrastructure
– One-off for Hadoop only
2
Lacking Enterprise Data Protection
– No Snapshots, replication, backup
3
Poor Storage Efficiency
– 3X mirroring
4
Fixed Scalability
– Rigid compute to storage ratio
5
Manual Import/Export
– No protocol support
1x
1x
2x
2x
3x
2x
3x
3x
1x
NameNode

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Hadoop On EMC Isilon Scale Out NAS
1
Scale-Out Storage Platform
– Multiple applications & workflows
2
End-to-End Data Protection
– SnapshotIQ, SyncIQ, NDMP Backup
3
Industry-Leading Storage Efficiency
– >80% Storage Utilization
4
Independent Scalability
– Add compute & storage separately
5
Multi-Protocol
– Industry standard protocols
– NFS, CIFS, FTP, HTTP, HDFS

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EMC Isilon Addresses Hadoop Challenges
1
Dedicated Storage Infrastructure
– One-off for Hadoop only
2
Lacking Enterprise Data Protection
– No Snapshots, replication, backup
3
Poor Storage Efficiency
– 3X mirroring
4
Fixed Scalability
– Rigid compute to storage ratio
5
Manual Import/Export
– No protocol support
1
Scale-Out Storage Platform
– Multiple applications & workflows
2
End-to-End Data Protection
– SnapshotIQ, SyncIQ, NDMP Backup
3
Industry-Leading Storage Efficiency
– >80% Storage Utilization
4
Independent Scalability
– Add compute & storage separately
5
Multi-Protocol
– Industry standard protocols
– NFS, CIFS, FTP, HTTP, HDFS

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Why Virtualize Hadoop?

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Hadoop with Virtualization
Combined
Storage/
Compute
VM
Hadoop in VM
• VM lifecycle
determined
by Datanode
• Limited elasticity
• Limited to Hadoop
Multi-Tenancy
Storage
Comput
e
VM
VM
Separate Storage
• Separate compute
from data
• Elastic compute
• Enable shared
workloads
• Raise utilization
Storage
T1 T2
VM
VM
VM
Separate Compute Tenants
• Compute cluster per tenant
• Stronger VM-grade security
and resource isolation
• Enable deployment of
multiple Hadoop runtime
versions
Elastic, Multi-Tenant

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Virtualized Hadoop Performance
Native vs. Virtual, 32 hosts, 16 disks/host
Source: http://www.vmware.com/resources/techresources/10360

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Example Deployment With Pivotal HD
• Pre-requisities
– Isilon OneFS version 6.5.5 or
higher
– VMware vSphere 5.0 (or later)
Enterprise or Enterprise Plus
• Download Vmware Big Data
Extensions (Free)
• Configure Isilon cluster for
HDFS (Free license)
• Configure Big Data Extensions
to use Pivotal HD
• Deploy Hadoop Cluster
• Run a simple program to test

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Hadoop Data Services
Real-time, Interactive, And Batch Processing

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Results
 Fast deployment with native Hadoop integration,
enabling rapid launch of new service
 Delivered high performance scalability
 Simplified platform administration
Challenges
 Rapidly launch new market intelligence service for
fashion retailers
 Support large and growing volumes of Big Data
Solution
• Pivotal Greenplum Database
• Pivotal HD
 EMC Isilon
 Pivotal Data Science Labs
WGSN
Retail
“Performance, scalability, and tight integration with Hadoop
were the key reasons we chose Isilon. We also felt very
comfortable with the partnership between EMC and
Pivotal. In the end, the EMC and Pivotal solution offered
the ideal balance of storage and compute with the right
level of support.”

19. 19© Copyright 2014 EMC Corporation. All rights reserved.© Copyright 2014 EMC Corporation. All rights reserved.
Download Hadoop Starter Now
• Rapid provisioning
• High availability
• Elasticity
• Multi-tenancy
• Portability
https://community.emc.com/docs/DOC-26892