Book Image

Learning Apache Cassandra - Second Edition

Book Image

Learning Apache Cassandra - Second Edition

Overview of this book

Cassandra is a distributed database that stands out thanks to its robust feature set and intuitive interface, while providing high availability and scalability of a distributed data store. This book will introduce you to the rich feature set offered by Cassandra, and empower you to create and manage a highly scalable, performant and fault-tolerant database layer. The book starts by explaining the new features implemented in Cassandra 3.x and get you set up with Cassandra. Then you’ll walk through data modeling in Cassandra and the rich feature set available to design a flexible schema. Next you’ll learn to create tables with composite partition keys, collections and user-defined types and get to know different methods to avoid denormalization of data. You will then proceed to create user-defined functions and aggregates in Cassandra. Then, you will set up a multi node cluster and see how the dynamics of Cassandra change with it. Finally, you will implement some application-level optimizations using a Java client. By the end of this book, you'll be fully equipped to build powerful, scalable Cassandra database layers for your applications.
Table of Contents (14 chapters)

Deleting columns


Upon further consideration, we may decide that location is a better column name than city_state. Cassandra does not allow us to rename existing data columns; however, since we haven't put any data in the city_state column yet, we can achieve our goals simply by dropping the city_state column and adding a location column instead:

ALTER TABLE "users" DROP "city_state"; 
ALTER TABLE "users" ADD "location" text;

The DROP command within the ALTER TABLE statement looks just like the ADD command, except that we need not specify the column's type—only its name is sufficient. Looking at the output of DESCRIBE again, we've now got the columns set up the way we'd like:

Before we proceed with table operations, let's change the email of user alice to maintain similarity. Remember, we changed the email earlier in Chapter 2, The First Table. We can do the same again:

INSERT INTO "users"  
("username", "email")   
VALUES ('alice', '[email protected]');

Now that we've got our expanded schema, we...