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Building Google Cloud Platform Solutions

You're reading from   Building Google Cloud Platform Solutions Develop scalable applications from scratch and make them globally available in almost any language

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Product type Course
Published in Mar 2019
Publisher Packt
ISBN-13 9781838647438
Length 778 pages
Edition 1st Edition
Languages
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Authors (3):
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Ted Hunter Ted Hunter
Author Profile Icon Ted Hunter
Ted Hunter
Steven Porter Steven Porter
Author Profile Icon Steven Porter
Steven Porter
Legorie Rajan PS Legorie Rajan PS
Author Profile Icon Legorie Rajan PS
Legorie Rajan PS
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Toc

Table of Contents (29) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Why GCP? FREE CHAPTER 2. The Google Cloud Console 3. APIs, CLIs, IAM, and Billing 4. Google App Engine 5. Google Kubernetes Engine 6. Google Cloud Functions 7. Google Compute Engine 8. NoSQL with Datastore and Bigtable 9. Relational Data with Cloud SQL and Cloud Spanner 10. Google Cloud Storage 11. Stackdriver 12. Change Management 13. GCP Networking for Developers 14. Messaging with Pub/Sub and IoT Core 15. Integrating with Big Data Solutions on GCP 16. Compute 17. Storage and Databases 18. Networking 19. Security 20. Machine Learning and Big Data 21. Management Tools 22. Best Practices 1. Other Books You May Enjoy Index

Storage metadata in Google Cloud Datastore


Google Datastore is a highly scalable, NoSQL document database similar to Amazon's DynamoDB and MongoDB. Individual data objects in the Datastore are called entities. An entity has one or more properties and a category of objects is called a kind. Each object is uniquely identified by a key. In this recipe, we would simulate a storage drive environment. Employees of a company are given the ability to upload files to Google Storage. The metadata is stored in Cloud Datastore to avoid overhead to the Storage API and for efficiency. The file uploaded to the Storage follows this file format:

<5-digit hash>/<[year][month][day][hour][minute][second]>/<Employee ID>/<file name>

After the data is uploaded to Storage, the metadata collected should enable us to query:

  • List all objects uploaded by an employee
  • List all objects in a time range

So, we'll design the metadata in the following format:

Kind

Drive

Entity

Data objects inserted for example...

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