Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Big Data Analytics
Search
Matt Wood
August 01, 2012
Technology
7
1.2k
Big Data Analytics
An introduction to Big Data Analytics in the cloud.
Matt Wood
August 01, 2012
Tweet
Share
More Decks by Matt Wood
See All by Matt Wood
Field Notes from Expeditions in the Cloud
mza
2
400
A Platform for Big Data
mza
6
750
The Data Lifecycle
mza
5
510
Provision Throughput Like a Boss
mza
0
440
Impact of Cloud Computing: Life Sciences
mza
2
860
Latency's Worst Nightmare: Performance Tuning Tips and Tricks
mza
4
1.1k
Under the Covers of DynamoDB
mza
4
1.1k
From Analytics to Intelligence: Amazon Redshift
mza
9
1k
Scaling Science
mza
3
500
Other Decks in Technology
See All in Technology
mrubyと micro-ROSが繋ぐロボットの世界
kishima
2
260
Witchcraft for Memory
pocke
1
310
AIのAIによるAIのための出力評価と改善
chocoyama
2
550
25分で解説する「最小権限の原則」を実現するための AWS「ポリシー」大全 / 20250625-aws-summit-aws-policy
opelab
9
1.1k
フィンテック養成勉強会#54
finengine
0
180
MySQL5.6から8.4へ 戦いの記録
kyoshidaxx
1
210
Uniadex__公開版_20250617-AIxIoTビジネス共創ラボ_ツナガルチカラ_.pdf
iotcomjpadmin
0
160
米国国防総省のDevSecOpsライフサイクルをAWSのセキュリティサービスとOSSで実現
syoshie
2
1.1k
2年でここまで成長!AWSで育てたAI Slack botの軌跡
iwamot
PRO
4
700
VISITS_AIIoTビジネス共創ラボ登壇資料.pdf
iotcomjpadmin
0
160
5min GuardDuty Extended Threat Detection EKS
takakuni
0
140
rubygem開発で鍛える設計力
joker1007
2
200
Featured
See All Featured
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
107
19k
The Art of Delivering Value - GDevCon NA Keynote
reverentgeek
15
1.5k
The Language of Interfaces
destraynor
158
25k
The Power of CSS Pseudo Elements
geoffreycrofte
77
5.8k
Done Done
chrislema
184
16k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
138
34k
The World Runs on Bad Software
bkeepers
PRO
69
11k
Being A Developer After 40
akosma
90
590k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
229
22k
Raft: Consensus for Rubyists
vanstee
140
7k
Docker and Python
trallard
44
3.4k
Adopting Sorbet at Scale
ufuk
77
9.4k
Transcript
Big Data Analytics w i t h A m a
z o n W e b S e r v i c e s Dr. Matt Wood An Online Seminar for Partners. Wednesday 1st August.
Hello, and thank you.
Big Data Analytics An introduction
Big Data Analytics An introduction The story of analytics on
AWS
Big Data Analytics An introduction The story of analytics on
AWS Integrating partners
Big Data Analytics An introduction The story of analytics on
AWS Integrating partners Partner success stories
INTRODUCING BIG DATA 1
Data for competitive advantage.
Customer segmentation, financial modeling, system analysis, line-of-sight, business intelligence. Using
data
Generation Collection & storage Analytics & computation Collaboration & sharing
Cost of data generation is falling.
Generation Collection & storage Analytics & computation Collaboration & sharing
lower cost, increased throughput
Generation Collection & storage Analytics & computation Collaboration & sharing
HIGHLY CONSTRAINED
Very high barrier to turning data into information.
Move from a data generation challenge to analytics challenge.
Enter the Cloud.
Remove the constraints.
Enable data-driven innovation.
Move to a distributed data approach.
Maturation of two things.
Maturation of two things. Software for distributed storage and analysis
Maturation of two things. Software for distributed storage and analysis
Infrastructure for distributed storage and analysis
Frameworks for data-intensive workloads. Software Distributed by design.
Platform for data-intensive workloads. Infrastructure Distributed by design.
Support the data timeline.
Generation Collection & storage Analytics & computation Collaboration & sharing
HIGHLY CONSTRAINED
Generation Collection & storage Analytics & computation Collaboration & sharing
Lower the barrier to entry.
Accelerate time to market and increase agility.
Enable new business opportunities.
Washington Post Pinterest NASA
“AWS enables Pfizer to explore difficult or deep scientific questions
in a timely, scalable manner and helps us make better decisions more quickly” Michael Miller, Pfizer
THE STORY OF ANALYTICS 2
EC2 Utility computing. 6 years young.
Embarrassingly parallel problems. Scale out systems Queue based distribution. Small,
medium and high scale.
None
None
None
EC2 Utility computing. 6 years young. Cost optimization.
Achieving economies of scale 100% Time
Reserved capacity Achieving economies of scale 100% Time
Reserved capacity Achieving economies of scale 100% Time On-demand
Reserved capacity Achieving economies of scale 100% Time On-demand UNUSED
CAPACITY
Bid on unused EC2 capacity. Spot Instances Very large discount.
Perfect for batch runs. Balance cost and scale.
$650 per hour
Pattern for distributed computing. Map/reduce Software frameworks such as Hadoop.
Write two functions. Scale up.
Pattern for distributed computing. Map/reduce Software frameworks such as Hadoop.
Write two functions. Scale up. Complex cluster configuration and management.
Managed Hadoop clusters. Amazon Elastic MapReduce Easy to provision and
monitor. Write two functions. Scale up. Optimized for S3 access.
Input data S3 UNDER THE HOOD i i
Elastic MapReduce Code Input data S3 UNDER THE HOOD i
i
Elastic MapReduce Code Name node Input data S3 UNDER THE
HOOD i i
Elastic MapReduce Code Name node Input data S3 Elastic cluster
UNDER THE HOOD i i
Elastic MapReduce Code Name node Input data S3 Elastic cluster
HDFS UNDER THE HOOD i i
Elastic MapReduce Code Name node Input data S3 Elastic cluster
HDFS Queries + BI Via JDBC, Pig, Hive UNDER THE HOOD i i
Elastic MapReduce Code Name node Output S3 + SimpleDB Input
data S3 Elastic cluster HDFS Queries + BI Via JDBC, Pig, Hive UNDER THE HOOD i i
Output S3 + SimpleDB Input data S3 UNDER THE HOOD
i i
None
None
None
None
None
None
None
None
None
None
None
None
None
None
Performance
Performance Compute performance
Intel Xeon E5-2670 Cluster Compute 10 gig E non-blocking network
Placement groupings 60.5 Gb UNDER THE HOOD i i
Intel Xeon E5-2670 Cluster Compute 10 gig E non-blocking network
Placement groupings 60.5 Gb UNDER THE HOOD i i + GPU enabled instances
Performance Compute performance
Performance Compute performance IO performance
NoSQL Unstructured data storage.
Predictable, consistent performance DynamoDB Unlimited storage No schema for unstructured
data Single digit millisecond latencies Backed on solid state drives
...and SSDs for all. New Hi1 storage instances.
2 x 1Tb SSDs hi1.4xlarge 10 GigE network HVM: 90k
IOPS read, 9k to 75k write PV: 120k IOPS read, 10k to 85k write UNDER THE HOOD i i
Netflix “The hi1.4xlarge configuration is about half the system cost
for the same throughput.” http://techblog.netflix.com/2012/07/benchmarking-high-performance-io-with.html
EBS Elastic Block Store
Provisioned IOPS Provision required IO performance
Provisioned IOPS Provision required IO performance + EBS-optimized instances with
dedicated throughput
Generation Collection & storage Analytics & computation Collaboration & sharing
Performance + ease of use
PARTNER INTEGRATION 3
Extend platform with partners
Innovate on behalf of customers
Remove undifferentiated heavy lifting
Rolled the Amazon Hadoop optimizations into MapR MapR distribution for
EMR Choice for EMR customers Easy deployment for MapR customers
Hadoop distribution MapR distribution for EMR Integrated into EMR NFS
and ODBC drivers High availability and cluster mirroring
Enterprise data toolchain Informatica on EMR “Swiss army knife” for
data formats Data integration Available to all on EMR
AWS Marketplace Karmasphere, Marketshare, Acunu Cassandra, Metamarkets, Aspera and more.
aws.amazon.com/marketplace
PARTNER SUCCESS STORIES 4
Razorfish
3.5 billion records 71MM unique cookies 1.7MM targeted ads per
day
3.5 billion records 71MM unique cookies 1.7MM targeted ads per
day 500% improvement in return on ad spend.
Cycle Computing + Schrodinger
30k cores, $4200 an hour (compared to $10+ million)
Marketshare + Ticketmaster Optimize live event pricing
Reduced developer infrastructure management time by 3 hours a day
Thank you!
Q & A
[email protected]
@mza on Twitter