Learning Apache Cassandra - Second Edition by Sandeep Yarabarla

By Sandeep Yarabarla

Key Features

  • Install Cassandra and manage multi-node clusters
  • Design wealthy schemas that catch the relationships among diversified facts types
  • Master the complicated positive aspects on hand in Cassandra 3.x via a step by step educational and construct a scalable, excessive functionality database layer

Book Description

Cassandra is a disbursed database that sticks out due to its powerful characteristic set and intuitive interface, whereas delivering excessive availability and scalability of a allotted info shop. This e-book will introduce you to the wealthy characteristic set provided by means of Cassandra, and empower you to create and deal with a hugely scalable, performant and fault-tolerant database layer.

The booklet begins by means of explaining the hot beneficial properties carried out in Cassandra 3.x and get you place up with Cassandra. Then you will stroll via facts modeling in Cassandra and the wealthy characteristic set on hand to layout a versatile schema. subsequent you will learn how to create tables with composite partition keys, collections and user-defined varieties and get to understand various easy methods to stay away from denormalization of information. you'll then continue to create user-defined capabilities and aggregates in Cassandra. Then, you'll manage a multi node cluster and notice how the dynamics of Cassandra swap with it. eventually, you'll enforce a few application-level optimizations utilizing a Java client.

By the top of this e-book, you can be totally outfitted to construct strong, scalable Cassandra database layers on your applications.

What you'll learn

  • Install Cassandra
  • Create keyspaces and tables with a number of clustering columns to prepare similar data
  • Use secondary indexes and materialized perspectives to prevent denormalization of data
  • Effortlessly deal with concurrent updates with assortment columns
  • Ensure info integrity with light-weight transactions and logged batches
  • Understand eventual consistency and use the correct consistency point in your situation
  • Understand facts distribution with Cassandra
  • Develop easy program utilizing Java motive force and enforce application-level optimizations

About the Author

Sandeep Yarabarla is a qualified software program engineer operating for Verizon Labs, dependent out of Palo Alto, CA. After graduating from Carnegie Mellon collage, he has labored on a number of huge information applied sciences for a spectrum of businesses. He has built purposes essentially in Java and Go.

His adventure contains dealing with quite a lot of unstructured and based information in Hadoop, and constructing facts processing purposes utilizing Spark and MapReduce. instantly, he's operating with a few state of the art applied sciences equivalent to Cassandra, Kafka, Mesos, and Docker to construct fault-tolerant and hugely scalable applications.

Table of Contents

  1. Getting Up and operating with Cassandra
  2. The First Table
  3. Organizing comparable Data
  4. Beyond Key-Value Lookup
  5. Establishing Relationships
  6. Denormalizing facts for optimum Performance
  7. Expanding Your info Model
  8. Collections, Tuples, and User-Defined Types
  9. Aggregating Time-Series Data
  10. How Cassandra Distributes Data
  11. Cassandra Multi-Node Cluster
  12. Application improvement utilizing the Java Driver
  13. Peeking less than the Hood
  14. Authentication and Authorization

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