July 2022
Intermediate to advanced
304 pages
9h 15m
English
book
Algorithms and Data Structures for Massive Datasets
by Dzejla Medjedovic, Emin Tahirovic, Ines Schweigert
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7 Sampling from data streams
This chapter covers
- Sampling from an infinite landmark stream
- Incorporating recency by using a sliding window and how to sample from it
- Showcasing the difference between a representative and biased sampling strategy on a landmark stream with a sudden shift
- Exploring R and Python packages and libraries for writing and executing tasks on data streams
We are ready to fully appreciate sampling as a single task staged in the analysis tier. Although we have already shown that this division of the streaming data architecture is not so clear-cut, we will imagine the stream processor sampling the incoming stream in this tier. This will help to introduce the sampling algorithm without any additional complexity coming from ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.