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Building a Distributed Data Pipeline

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Tom Lous
Tom Lous

Spark, Akka, MLlib, Kafka, Spray Presentation & demo for http://www.daysofcode.nl/ @daysofcode

Logiciels
1  sur  6
BUILDING A DISTRIBUTED MACHINE LEARNING AT SCALE
BACKGROUND DATA ▸Data is everywhere ▸Data, unapplied, is useless ▸How can we turn high volume & velocity data into value?
BACKGROUND PIPELINE ▸Process the data continuously ▸Apply several processing steps COLLECT MODEL DEPLOY INTEGRA TE
SOLUTION ANALYSE THE STOCK MARKET YAHOO.C OM YAHOO.C OM (PREFETCHED) COLLECTO R MESSAGE BROKER STREAMIN G STORAGE MODEL MACHINE LEARNING MLlibWEBSERVI CE USER / CLIENTS
DEMO DEMO (FINGERS CROSSED)
DONE QUESTIONS? ▸?

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Building a Distributed Data Pipeline