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Learning Google BigQuery

You're reading from Learning Google BigQuery A beginner's guide to mining massive datasets through interactive analysis

Product type Paperback

Published in Dec 2017

Publisher Packt

ISBN-13 9781787288591

Length 264 pages

Edition 1st Edition

Languages

Python

Tools

BigQuery

Concepts

Database Administration

Authors (3):

Berlyant

Haridass

Brown

View More author details

Table of Contents (17) Chapters

Title Page

Credits

Foreword

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

Dedication

Preface

1. Google Cloud and Google BigQuery FREE CHAPTER

2. Google Cloud SDK

3. Google BigQuery Data Types

4. BigQuery SQL Basic

5. BigQuery SQL Advanced

6. Google BigQuery API

7. Visualizing BigQuery Data

8. Google Cloud Pub/Sub

Querying nested and repeated records

Google BigQuery supports loading of JSON files into BigQuery tables. JSON format data can contain nested datatypes and repeated datatypes. The example table shown in the following screenshot has an Employee_Names column as RECORD datatype. Each record in that column has two columns, one to store the first name and one to store the last name. Create the table as shown in this screenshot:

Download the following file to load to this new table. The file is a JSON file that contains the records to be loaded into this table from JSON format: https://github.com/hthirukkumaran/Learning-Google-BigQuery/blob/master/chapter1/employeedetails.json.

Upload the file to your Google Cloud Storage bucket using the gsutil command as shown here:

gsutil cp employeedetails.json gs://myfirstprojectbucket201706/employeedetails.json

Run the following command to load the JSON file into the new table using the bq utility. The --source_format flag is used to specify the format of the...

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Authors (3)

Berlyant

Berlyant

See other products by Berlyant

Haridass

Haridass

Thirukkumaran Haridass currently works as a lead software engineer at Builder Homesite Inc. in Austin, Texas, USA. He has over 15 years of experience in the IT industry. He has been working on the Google Cloud Platform for more than 3 years. Haridass is responsible for the big data initiatives in his organization that help the company and its customers realize the value of their data. He has played various roles in the IT industry and worked for Fortune 500 companies in various verticals, such as retail, e-commerce, banking, automotive, and presently, real estate online marketing.

See other products by Haridass

Brown

Brown

Eric Brown currently works as an analytics manager for PMG advertising in Austin, Texas. Eric has over 11 years of experience in the data analytics field. He has been working on the Google Cloud Platform for over 3 years. He oversees client web analytics implementations and implements big data integrations in both Google BigQuery and Amazon Redshift. Eric has a passion for analytics, and especially for visualization and data manipulation through open source tools such as R. He has worked in various roles in various verticals, such as web analytics service providers, media companies, real-estate online marketing, and advertising.

See other products by Brown

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