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Separating Hadoop Myths from Reality
Rob Anderson
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1
The
Myths
&
Reali.es
Surrounding
Hadoop
Rob
Anderson
VP
Systems
Engineering
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Sales
SCM
CRM
Public
Web
Logs
Produc7on
Data
Sensor
Data
Click
Streams
Loca7on
Social
Media
Billing
Enterprise
Data
Hub
Hadoop
Changes
Analy.cs
“Simple
algorithms
and
lots
of
data
trump
complex
models
”
Halevy,
Norvig,
and
Pereira,
Google
IEEE
Intelligent
Systems
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4
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Data
Warehouse
Volume
Variety
Velocity
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Big Data is hard to move…because it’s
BIG
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8
What
was
the
genius
of
Hadoop?
§ Fueling
an
industry
revolu7on
by
providing
infinite
capability
to
store
and
process
big
data
§ Expanding
analy7cs
across
data
types
§ Compelling
economics
–
20
to
100X
more
cost
effec7ve
than
alterna7ves
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Random
Wri.ng
in
MapR
S1
S2
S3 S5
S4
S1, S2, S4
S1, S3
S1, S4, S5
S2, S4, S5
S3
Client
wri.ng
data
CLDB
Ask
for
64M
block
Create
cont.
Picks
master
and
2
replica
slaves
Write
next
chunk
to
S2
S2, S3, S5
aZach
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MapR
Spout
TwiZer
TwiZer
API
TwiZerLogger
Storm
MapR
Op7onal
MapReduce
DFS
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hZp://www.flickr.com/photos/onemoreshotrog/8085462024/
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14
Hadoop
Distribu.ons
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Hadoop:
The
Disrup.ve
Technology
at
the
Core
of
Big
Data
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The
Reality
is
Architecture
MaHers
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MapR
Data
System
Architecture
Comparison
HBase
JVM
HDFS
JVM
ext3/ext4
Disks
Other
Distribu7ons
Disks
MapR
M7
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Architecture
Results
Results
with
other
distribu.ons
Results
with
MapR
M7
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Produc.on
Success
with
Hadoop
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2000+
Nodes
Fortune
100
Retailer
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1000+
Nodes
Fortune
100
Financial
Services
Company
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Produc7on
Hadoop
in
Waste
Management
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Suntory
whiskey
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Unique
Iden.ty
Ini.a.ve,
India
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Thank
you
Big
Data
Spain!
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