Utilizing Spark Streaming for analyzing a real-time sport data stream.

1. 1
U"lizing
Spark
Streaming
for
analyzing
a
real-­‐"me
sport
data
feed
Demonstra"on

2. 2
Camera
Tracking
Systems
An
array
of
cameras
around
the
field
capture
the
players
and
ball
posi6ons
LIVE
Used
by
the
NBA
since
2011-­‐2012
Tennis
“hawk
eye”

3. 3
aggregate
the
speed
and
distance
run
of
each
player
IN
REAL
TIME
Our
goal:

4. 4
• The
camera
array
sends
a
feed
of
25
frames
per
second
• Each
frame
captures
the
x,y,z
coordinates
of
every
player
• A
live
feed
of
sport
data
is
actually
preLy
serious
Big
Data!
Challenges

5. 5
Demo
Architecture
Database
Inges6on
Process
Store
Visualize
Deliver
ALL designed in Talend – NO coding

6. 6
©2015 Talend Inc
Demo
Time!

7. 7
Next
Step:
From
Analysis
to
Predic"on
Team
stats
Who
is
the
most
likely
to
score
next?
Which
team
is
going
to
win?
Individual
players
stats
Which
player
need
a
rest/bench?
Which
player
are
being
traded
(à
bring
in
historical
data)

8. 8
Free
Trial:
Talend
Big
Data
Sandbox
• A
ready-­‐to-­‐run
Docker
environment
• A
step-­‐by-­‐step
expert
guide:
the
cookbook
• Real-­‐world
scenarios
using
Spark,
KaPa,
MapReduce
&
NoSQL
• Iot
Analy"cs
• Real-­‐"me
Recommenda"on
• Clickstream
Analysis
• Weblogs
Analysis
• EDW
Offload
www.talend.com/BigDataSandbox
Hit
the
Easy
BuXon
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Hadoop,
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and
Machine
Learning