book

Cassandra: The Definitive Guide, 3rd Edition

by Jeff Carpenter, Eben Hewitt

April 2020

Intermediate to advanced

426 pages

12h 4m

English

O'Reilly Media, Inc.

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Why Apache Cassandra?Is This Book for You?What’s in This Book?New for the Third EditionConventions Used in This BookUsing Code ExamplesO’Reilly Interactive Katacoda ScenariosO’Reilly Online LearningHow to Contact UsAcknowledgments
What’s Wrong with Relational Databases?A Quick Review of Relational DatabasesTransactions, ACID-ity, and Two-Phase CommitSchemaSharding and Shared-Nothing ArchitectureWeb ScaleThe Rise of NoSQLSummary
The Cassandra Elevator PitchCassandra in 50 Words or LessDistributed and DecentralizedElastic ScalabilityHigh Availability and Fault ToleranceTuneable ConsistencyBrewer’s CAP TheoremRow-OrientedHigh PerformanceWhere Did Cassandra Come From?Is Cassandra a Good Fit for My Project?Large DeploymentsLots of Writes, Statistics, and AnalysisGeographical DistributionHybrid Cloud and Multicloud DeploymentGetting InvolvedSummary
Installing the Apache DistributionExtracting the DownloadWhat’s in There?Building from SourceAdditional Build TargetsRunning CassandraSetting the EnvironmentStarting the ServerStopping CassandraOther Cassandra DistributionsRunning the CQL ShellBasic cqlsh Commandscqlsh HelpDescribing the Environment in cqlshCreating a Keyspace and Table in cqlshWriting and Reading Data in cqlshRunning Cassandra in DockerSummary
The Relational Data ModelCassandra’s Data ModelClustersKeyspacesTablesColumnsCQL TypesNumeric Data TypesTextual Data TypesTime and Identity Data TypesOther Simple Data TypesCollectionsTuplesUser-Defined TypesSummary
Conceptual Data ModelingRDBMS DesignDesign Differences Between RDBMS and CassandraDefining Application QueriesLogical Data ModelingHotel Logical Data ModelReservation Logical Data ModelPhysical Data ModelingHotel Physical Data ModelReservation Physical Data ModelEvaluating and RefiningCalculating Partition SizeCalculating Size on DiskBreaking Up Large PartitionsDefining Database SchemaCassandra Data Modeling ToolsSummary
Data Centers and RacksGossip and Failure DetectionSnitchesRings and TokensVirtual NodesPartitionersReplication StrategiesConsistency LevelsQueries and Coordinator NodesHinted HandoffAnti-Entropy, Repair, and Merkle TreesLightweight Transactions and PaxosMemtables, SSTables, and Commit LogsBloom FiltersCachingCompactionDeletion and TombstonesManagers and ServicesCassandra DaemonStorage EngineStorage ServiceStorage ProxyMessaging ServiceStream ManagerCQL Native Transport ServerSystem KeyspacesSummary
Hotel Application DesignCassandra and Microservice ArchitectureMicroservice Architecture for a Hotel ApplicationIdentifying Bounded ContextsIdentifying ServicesDesigning Microservice PersistenceExtending DesignsSecondary IndexesMaterialized ViewsReservation Service: A Sample MicroserviceDesign Choices for a Java MicroserviceDeployment and Integration ConsiderationsServices, Keyspaces, and ClustersData Centers and Load BalancingInteractions Between MicroservicesSummary
DataStax Java DriverDevelopment Environment ConfigurationConnecting to a ClusterStatementsSimple StatementsPrepared StatementsQuery BuilderObject MapperAsynchronous ExecutionDriver ConfigurationMetadataDebugging and MonitoringOther Cassandra DriversSummary

WritingWrite Consistency LevelsThe Cassandra Write PathWriting Files to DiskLightweight TransactionsBatchesReadingRead Consistency LevelsThe Cassandra Read PathRead RepairRange Queries, Ordering and FilteringPagingDeletingSummary
Cassandra Cluster ManagerCreating a ClusterAdding Nodes to a ClusterDynamic Ring ParticipationNode ConfigurationSeed NodesSnitchesPartitionersTokens and Virtual NodesNetwork InterfacesData StorageStartup and JVM SettingsPlanning a Cluster DeploymentCluster Topology and Replication StrategiesSizing Your ClusterSelecting InstancesStorageNetworkCloud DeploymentAmazon Web ServicesGoogle Cloud PlatformMicrosoft AzureSummary
Monitoring Cassandra with JMXCassandra’s MBeansDatabase MBeansCluster-Related MBeansInternal MBeansMonitoring with nodetoolGetting Cluster InformationGetting StatisticsVirtual TablesSystem Virtual SchemaSystem ViewsMetricsLoggingExamining Log FilesFull Query LoggingSummary
Health CheckCommon Maintenance TasksFlushCleanupRepairRebuilding IndexesMoving TokensAdding NodesAdding Nodes to an Existing Data CenterAdding a Data Center to a ClusterHandling Node FailureRepairing Failed NodesReplacing NodesRemoving NodesUpgrading CassandraBackup and RecoveryTaking a SnapshotClearing a SnapshotEnabling Incremental BackupRestoring from SnapshotSSTable UtilitiesMaintenance ToolsNetflix PriamDataStax OpsCenterCassandra SidecarsCassandra Kubernetes OperatorsSummary
Managing PerformanceSetting Performance GoalsBenchmarking and Stress TestingMonitoring PerformanceAnalyzing Performance IssuesTracingTuning MethodologyCachingKey CacheRow CacheChunk CacheCounter CacheSaved Cache SettingsMemtablesCommit LogsSSTablesHinted HandoffCompactionConcurrency and ThreadingNetworking and TimeoutsJVM SettingsMemoryGarbage CollectionSummary
Authentication and AuthorizationPassword AuthenticatorUsing CassandraAuthorizerRole-Based Access ControlEncryptionSSL, TLS, and CertificatesNode-to-Node EncryptionClient-to-Node EncryptionJMX SecuritySecuring JMX AccessSecurity MBeansAudit LoggingSummary
Knowing When to MigrateAdapting the Data ModelTranslating EntitiesTranslating RelationshipsAdapting the ApplicationRefactoring Data AccessMaintaining ConsistencyMigrating Stored ProceduresPlanning the DeploymentMigrating DataZero-Downtime MigrationBulk LoadingCommon IntegrationsManaging Data Flow with Apache KafkaSearching with Apache Lucene, SOLR, and ElasticsearchAnalyzing Data with Apache SparkSummary

Overview

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment.

Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility.

Understand Cassandra’s distributed and decentralized structure
Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell
Create a working data model and compare it with an equivalent relational model
Develop sample applications using client drivers for languages including Java, Python, and Node.js
Explore cluster topology and learn how nodes exchange data