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The Artificial Intelligence Infrastructure Workshop

You're reading from   The Artificial Intelligence Infrastructure Workshop Build your own highly scalable and robust data storage systems that can support a variety of cutting-edge AI applications

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800209848
Length 732 pages
Edition 1st Edition
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Authors (6):
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Bas Geerdink Bas Geerdink
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Bas Geerdink
Chinmay Arankalle Chinmay Arankalle
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Chinmay Arankalle
Kunal Gera Kunal Gera
Author Profile Icon Kunal Gera
Kunal Gera
Kevin Liao Kevin Liao
Author Profile Icon Kevin Liao
Kevin Liao
Gareth Dwyer Gareth Dwyer
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Gareth Dwyer
Anand N.S. Anand N.S.
Author Profile Icon Anand N.S.
Anand N.S.
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Toc

Table of Contents (14) Chapters Close

Preface
1. Data Storage Fundamentals 2. Artificial Intelligence Storage Requirements FREE CHAPTER 3. Data Preparation 4. The Ethics of AI Data Storage 5. Data Stores: SQL and NoSQL Databases 6. Big Data File Formats 7. Introduction to Analytics Engine (Spark) for Big Data 8. Data System Design Examples 9. Workflow Management for AI 10. Introduction to Data Storage on Cloud Services (AWS) 11. Building an Artificial Intelligence Algorithm 12. Productionizing Your AI Applications Appendix

8. Data System Design Examples

Activity 8.01: Building the Complete System with Pipelines and Queues

Solution

  1. Import the random and time standard libraries, as well as the Queue and Thread classes from their respective modules:
    from queue import Queue
    from threading import Thread
    import random
    import time

    We imported the modules that we will use to design our next mock system.

  2. Initialize the mock dataset and put it into a queue, as shown in the following query:
    urls = ['url1-', 'url1-', 'url2-', 'url3-', 'url4-', \
    'url5-', 'url6-', 'url7-', 'url8-', 'url9-', 'url10-']
    seen = set()
    url_queue = Queue()
    for url in urls:
        url_queue.put(url)

    We created 11 mock URLs and a seen set to find duplicates. We then created a queue for our URLs and added each URL to the queue.

  3. Set up queues for each of the components, as shown in the following...
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