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Learning Google BigQuery

By : Berlyant, Haridass, Brown

3.3 (4)

Buy this Book

Learning Google BigQuery

3.3 (4)

By: Berlyant, Haridass, Brown

Buy this Book

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.

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

Google Cloud and Google BigQuery

Getting started with Google Cloud

Summary

Google Cloud SDK

Installing Google Cloud SDK

gsutil for Google Cloud Storage

Using the bq utility for BigQuery

Using the gcloud utility

Connecting to Cloud SQL using gcloud

Deploying to Google App Engine

Summary

Google BigQuery Data Types

Supported data types

Data type considerations

Converting data

Sanitizing data

When to transform your data? Before or after loading to BigQuery?

Arithmetic Operators

Comparison Operators

Date Time Functions

String Functions

Regular Expression Functions

Functions for transformation

Mastering transformation with User-Defined Functions

Summary

Programming with BigQuery API in Python

The following section covers the interaction with BigQuery API using the Python programming language. The code samples cover how to create a new dataset and new table in BigQuery, load data from Google Cloud Storage to the table, execute a query, and return the results or copy the data to a new table.

To get started in Python, make sure the Google Cloud SDK is installed and configured as mentioned in Chapter 2, Google Cloud SDK. Python version 3.6.1 was used in coding these samples. To install the BigQuery API client library for Python, run the following command from the command prompt:

pip install --upgrade google-cloud-bigquery

If the project is going to have other services as well, then it is also better to install client libraries for other services by running the command given here: