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Scaling Data Science with Spark, Linux, AWS, and Flintrock
--client
linuxconfza
--show
lcza18
--room yellowwood 14405 --force
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Author(s):
Helge Reikeras
Location
Yellowwood
Date
oct Mon 08
Days Raw Files
Start
10:30
First Raw Start
10:03
Duration
40:00
Offset
0:27:00
End
11:10
Last Raw End
11:32
Chapters
00:00
0:02:17
0:32:17
Total cuts_time
39 min.
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Description:
The capability to process large amounts of data in parallel is imperative to any high-performing data science operation. However, the maintenance and cost overhead of running and maintaining a large data cluster are often significant and may become prohibitive for some teams. In this talk I'll discuss a kick-ass toolchain that makes launching, dynamically scaling nodes, and disposing of large data clusters on-demand a simple task for developers, system administrators, and data scientists alike.
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2018-10-08/10_03_00.ts
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seconds: 1081.0
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