Bigtable is Google’s proprietary storage service that offers extremely fast read and write speeds. It uses a sophisticated internal architecture which learns access patterns and moves around your data to mitigate the issue of hot-spotting. In this course, Architecting Big Data Solutions Using Google Bigtable, you’ll learn both the conceptual and practical aspects of working with Bigtable. You’ll learn how to best to design your schema to enable fast reads and write speeds and discover how data in Bigtable can be accessed using the command line as well as client libraries. First, you’ll study the internal architecture of Bigtable and how data is stored within it using the 4-dimensional data model. You’ll also discover how Bigtable clusters, nodes, and instances work and how Bigtable works with Colossus – Google’s proprietary storage system behind the scenes. Next, you’ll access Bigtable using both the HBase shell as well as cbt, Google’s command line utility. Later, you’ll create and manage tables while practice exporting and importing data using sequence files. Finally, you’ll study how manual fail-overs can be handled when we have single cluster routing enabled. At the end of this course, you’ll be comfortable working with Bigtable using both the command line as well as client libraries.
Author Name: Janani Ravi
Author Description:
Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing … more