April 2015
Beginner to intermediate
328 pages
11h 1m
English
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Chapter 4. Data storage on the batch layer
This chapter covers
- Storage requirements for the master dataset
- Distributed filesystems
- Improving efficiency with vertical partitioning
In the last two chapters you learned about a data model for the master dataset and how you can translate that data model into a graph schema. You saw the importance of making data immutable and eternal. The next step is to learn how to physically store that data in the batch layer. Figure 4.1 recaps where we are in the Lambda Architecture.
Figure 4.1. The batch layer must structure large, continually growing datasets in a manner that supports low maintenance as well as efficient creation of the batch views.
Like the last two chapters, this chapter is dedicated ...
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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.