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You're reading from Learning Google BigQuery

Product type Book

Published in Dec 2017

Publisher Packt

ISBN-13 9781787288591

Pages 264 pages

Edition 1st Edition

Languages

Python

Concepts

Database Administration

Authors (3):

Thirukkumaran Haridass

Mikhail Berlyant

Eric Brown

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Table of Contents (9) Chapters

Preface

1. Google Cloud and Google BigQuery

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

Partition tables

Partition tables are special tables that store data at a daily level in separate internal tables. This helps to improve the query performance and also reduces billing by querying data using a specified date range. The following steps outline how to create the partition table for your projects using a GUI and Google Cloud SDK.

Creating a partition table using a GUI

Download the sample file from this URL and upload it to a Google Cloud Storage bucket: https://github.com/hthirukkumaran/Learning-Google-BigQuery/blob/master/chapter1/employeedetails.csv. And note down the bucket name.

Click on the Create new table option under the Dataset menu.
To create a partition table, enable the partition option by choosing...

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Authors (3)

Thirukkumaran 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.

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Mikhail Berlyant

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Eric 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.

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