Hands on Google Cloud SQL and Cloud Spanner: Deployment, Administration and Use Cases with Python

ISBN-13: 9781484255360 / Angielski / Miękka / 2019 / 331 str.

Navin Sabharwal; Shakuntala Gupta Edward

Spis treści

Chapter 1: Google Cloud Platform

Chapter Goal: Enable the readers in getting started with the platform. 

Sub - Topics

1.1 Introduction to Google Cloud Platform (GCP)

1.2 Introduction to GCPs data technologies offerings

1.3 Getting started with the platform

1.4 Accessing Google Cloud Platform

Chapter 2: Cloud SQL

Chapter Goal: Introduce the readers to Google’s fully managed SQL database service - CloudSQL.

Sub - Topics

2.1 Relational data model

2.2 Introduction to Cloud SQL

2.3 Getting started with CloudSQL 

2.4 Provisioning a MySQL instance

2.5 Provisioning a PostgreSQL instance

Chapter 3: Working with CloudSQL

Chapter Goal: Enable users to work with CloudSQL.

Sub - Topics

3.1 Getting started with Cloud Shell

3.2 Using CloudSQL with Python

Chapter 4: Administering CloudSQL instances

Chapter Goal: Cover the administrative aspects of the database service starting from scaling, high availability, backup to security. Everything which is important from the database administration perspective a user need to be aware of. 

Sub - Topics

4.1 Backups

4.2 Replication

4.3 Security

Chapter 5: Cloud Spanner

Chapter Goal: Introduce the readers to the term NewSQL and then Google’s very own NewSQL offerings – Cloud Spanner.

Sub - Topics

5.1 What’s new in NewSQL

5.2 Introduction to Google Cloud Spanner

5.3 Origin

5.4 Spanner and CAP theorem

5.5 Best fit

Chapter 6: Cloud Spanner Explained

Chapter Goal: Enable users to understand Cloud Spanner Data Model and all its important aspects such as the architectural components, replica types, read/write methodology etc. 

Sub - Topics

6.1 Cloud Spanner objects

6.2 Architecture overview

6.3 Replica types

6.4 Operations

6.5 Understanding Operations with an example

Chapter 7: Working with Cloud Spanner

Chapter Goal: Cover the creation of an instance taking a pause in understanding what happens under the hood, good to know pointers from administrative perspective, following that start working with the schema, read and write using the web console and use the instance with Python code. 

Sub - Topics

7.1 Create Instance

7.2 Create database and schema

7.3 Reading and writing data using Cloud Shell

7.4 Using CloudSpanner with Python

7.5 Wrap up

Chapter 8: Best Practices

Chapter Goal: Cover crucial pointers which enables the users to work the way out around the drawbacks or limitations of the offerings 

O autorze

Navin Sabharwal is an innovator, thought leader, author, and consultant in the areas of AI, machine learning, cloud computing, Big Data Analytics, software product development. Responsible for IP development & service delivery in the areas of AI and machine learning, automation products, GCP, cloud computing, public cloud AWS and Microsoft Azure

Navin has created niche award-winning products and solutions and has filed numerous patents in diverse fields such as IT services, assessment engines, ranking algorithms, capacity planning engines, and knowledge management. 

Shakuntala Gupta Edward is an accomplished consultant in areas of data and analytics with 16 years of experience. Shakuntala is a Big Data architect and is responsible for database design, database architecture, best practices for big data technologies, product development using database, Big Data, NOSQL, analytics and machine learning technologies. 

Blurb

Discover the methodologies and best practices for getting started with Google Cloud Platform relational services – CloudSQL and CloudSpanner.

The book begins with the basics of working with the Google Cloud Platform along with an introduction to the database technologies available for developers from Google Cloud.  You'll then take an in-depth hands on journey into Google CloudSQL and CloudSpanner, including choosing the right platform for your application needs, planning, provisioning, designing and developing your application. 

The book provides sample applications using Python to connect to CloudSQL and CloudSpanner, and uses features provided by the engines. Practical best practices are provided for implementation in the last chapter. which allow you to try out the examples and extend them in interesting ways.

 

Hands On Google Cloud SQL and Cloud Spanner is a great starting point to apply GCP data offerings in your technology stack and the code used allows you to try out the examples and extend them in interesting ways.

You will:

• Get started with Big Data technologies on the Google Cloud Platform 
• Review CloudSQL and Cloud Spanner  from basics to administration
• Apply best practices and use Google’s CloudSQL and CloudSpanner offering
• Work with code in Python notebooks and scripts