Hands On Google Cloud SQL and Cloud Spanner

Deployment, Administration and Use Cases with Python
1. Auflage 2019
ISBN: 978-1-4842-5536-0
Verlag: Apress

Buch, Englisch, 331 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 655 g

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. 
Sample applications are given that use Python to connect to CloudSQL and CloudSpanner, along with helpful features provided by the engines. You''ll also implement practical best practices in the last chapter. 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.
What You'll Learn

• 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

Who This Book Is For
Application architects, database architects, software developers, data engineers, cloud architects.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Sabharwal, Navin

Edward, Shakuntala Gupta

Fachgebiete

• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik EDV | Informatik Betriebssysteme Linux Betriebssysteme, Open Source Betriebssysteme

Inhaltsverzeichnis

Chapter 1: Google Cloud PlatformChapter 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 offerings1.3 Getting started with the platform1.4 Accessing Google Cloud Platform
Chapter 2: Cloud SQLChapter Goal: Introduce the readers to Google’s fully managed SQL database service - CloudSQL.Sub - Topics 2.1 Relational data model2.2 Introduction to Cloud SQL2.3 Getting started with CloudSQL 2.4 Provisioning a MySQL instance2.5 Provisioning a PostgreSQL instance
Chapter 3: Working with CloudSQLChapter Goal: Enable users to work with CloudSQL.Sub - Topics 3.1 Getting started with Cloud Shell3.2 Using CloudSQL with Python
Chapter 4: Administering CloudSQL instancesChapter 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 Backups4.2 Replication4.3 Security
Chapter 5: Cloud SpannerChapter 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 NewSQL5.2 Introduction to Google Cloud Spanner5.3 Origin5.4 Spanner and CAP theorem5.5 Best fit
Chapter 6: Cloud Spanner ExplainedChapter 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 objects6.2 Architecture overview6.3 Replica types6.4 Operations6.5 Understanding Operations with an example
Chapter 7: Working with Cloud SpannerChapter 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 Instance7.2 Create database and schema7.3 Reading and writing data using Cloud Shell7.4 Using CloudSpanner with Python7.5 Wrap up
Chapter 8: Best PracticesChapter Goal: Cover crucial pointers which enables the users to work the way out around the drawbacks or limitations of the offerings 

Über Autor(innen)

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 AzureNavin 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.