Key FeaturesInstall Cassandra and set up multi-node clustersDesign rich schemas that capture the relationships between different data typesMaster the advanced features available in Cassandra 3.x through a step-by-step tutorial and build a scalable, high performance database layerBook DescriptionCassandra 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 youll walk through data modeling in Cassandra and the rich feature set available to design a flexible schema. Next youll 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, youll be fully equipped to build powerful, scalable Cassandra database layers for your applications.What you will learnInstall CassandraCreate keyspaces and tables with multiple clustering columns to organize related dataUse secondary indexes and materialized views to avoid denormalization of dataEffortlessly handle concurrent updates with collection columnsEnsure data integrity with lightweight transactions and logged batchesUnderstand eventual consistency and use the right consistency level for your situationUnderstand data distribution with CassandraDevelop simple application using Java driver and implement application-level optimizationsAbout the AuthorSandeep Yarabarla is a professional software engineer working for Verizon Labs, based out of Palo Alto, CA. After graduating from Carnegie Mellon University, he has worked on several big data technologies for a spectrum of companies. He has developed applications primarily in Java and Go.His experience includes handling large amounts of unstructured and structured data in Hadoop, and developing data processing applications using Spark and MapReduce. Right now, he is working with some cutting-edge technologies such as Cassandra, Kafka, Mesos, and Docker to build fault-tolerant and highly scalable applications.Table of ContentsGetting Up and Running with CassandraThe First TableOrganizing Related DataBeyond Key-Value LookupEstablishing RelationshipsDenormalizing Data for Maximum PerformanceExpanding Your Data ModelCollections, Tuples, and User-Defined TypesAggregating Time-Series DataHow Cassandra Distributes DataCassandra Multi-Node ClusterApplication Development Using the Java DriverPeeking under the HoodAuthentication and Authorization