Book Image

Learning Google BigQuery

By : Thirukkumaran Haridass, Mikhail Berlyant, Eric Brown
Book Image

Learning Google BigQuery

By: Thirukkumaran Haridass, Mikhail Berlyant, Eric Brown

Overview of this book

Google BigQuery is a popular cloud data warehouse for large-scale data analytics. This book will serve as a comprehensive guide to mastering BigQuery, and how you can utilize it to quickly and efficiently get useful insights from your Big Data. You will begin with getting a quick overview of the Google Cloud Platform and the various services it supports. Then, you will be introduced to the Google BigQuery API and how it fits within in the framework of GCP. The book covers useful techniques to migrate your existing data from your enterprise to Google BigQuery, as well as readying and optimizing it for analysis. You will perform basic as well as advanced data querying using BigQuery, and connect the results to various third party tools for reporting and visualization purposes such as R and Tableau. If you're looking to implement real-time reporting of your streaming data running in your enterprise, this book will also help you. This book also provides tips, best practices and mistakes to avoid while working with Google BigQuery and services that interact with it. By the time you're done with it, you will have set a solid foundation in working with BigQuery to solve even the trickiest of data problems.
Table of Contents (9 chapters)
Free Chapter
Google Cloud and Google BigQuery


BigQuery supports creating views, but they are not materialized views and the underlying query for a view is executed each time someone runs a query on the view. A view can be defined using legacy SQL or standard SQL, but the limitation is that if a view is defined in legacy SQL, then the queries executed using that view must also be in legacy SQL. The same applies to views that are defined using standard SQL; they can be used only in standard SQL statements. User-defined functions cannot be used in the query to define the views.

The BigQuery web console provides an option to save a query as a view, as shown in the following screenshot. Click on the Save View button as shown in this screenshot and choose the dataset under which the view has to be saved; provide a view name and save it:

To change the view definition, navigate to the view in the BigQuery web console and open...