book

Cassandra: The Definitive Guide

by Eben Hewitt

November 2010

Intermediate to advanced

328 pages

9h 38m

English

O'Reilly Media, Inc.

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Why Apache Cassandra?Is This Book for You?What’s in This Book?Finding Out MoreConventions Used in This BookUsing Code ExamplesSafari® EnabledHow to Contact UsAcknowledgments
What’s Wrong with Relational Databases?A Quick Review of Relational DatabasesRDBMS: The Awesome and the Not-So-MuchTransactions, ACID-ity, and two-phase commitSchemaSharding and shared-nothing architectureSummaryWeb ScaleThe Cassandra Elevator PitchCassandra in 50 Words or LessDistributed and DecentralizedElastic ScalabilityHigh Availability and Fault ToleranceTuneable ConsistencyBrewer’s CAP TheoremRow-OrientedSchema-FreeHigh PerformanceWhere Did Cassandra Come From?Use Cases for CassandraLarge DeploymentsLots of Writes, Statistics, and AnalysisGeographical DistributionEvolving ApplicationsWho Is Using Cassandra?Summary
Installing the BinaryExtracting the DownloadWhat’s In There?Building from SourceAdditional Build TargetsBuilding with MavenRunning CassandraOn WindowsOn LinuxStarting the ServerRunning the Command-Line Client InterfaceBasic CLI CommandsHelpConnecting to a ServerDescribing the EnvironmentCreating a Keyspace and Column FamilyWriting and Reading DataSummary
The Relational Data ModelA Simple IntroductionClustersKeyspacesColumn FamiliesColumn Family OptionsColumnsWide Rows, Skinny RowsColumn SortingSuper ColumnsComposite KeysDesign Differences Between RDBMS and CassandraNo Query LanguageNo Referential IntegritySecondary IndexesSorting Is a Design DecisionDenormalizationDesign PatternsMaterialized ViewValueless ColumnAggregate KeySome Things to Keep in MindSummary
Data DesignHotel App RDBMS DesignHotel App Cassandra DesignHotel Application CodeCreating the DatabaseLoading the schemaData StructuresGetting a ConnectionPrepopulating the DatabaseThe Search ApplicationTwissandraSummary
System KeyspacePeer-to-PeerGossip and Failure DetectionAnti-Entropy and Read RepairMemtables, SSTables, and Commit LogsHinted HandoffCompactionBloom FiltersTombstonesStaged Event-Driven Architecture (SEDA)Managers and ServicesCassandra DaemonStorage ServiceMessaging ServiceHinted Handoff ManagerSummary
KeyspacesCreating a Column FamilyTransitioning from 0.6 to 0.7ReplicasReplica Placement StrategiesSimple StrategyOld Network Topology StrategyNetwork Topology StrategyReplication FactorIncreasing the Replication FactorPartitionersRandom PartitionerOrder-Preserving PartitionerCollating Order-Preserving PartitionerByte-Ordered PartitionerSnitchesSimple SnitchPropertyFileSnitchCreating a ClusterChanging the Cluster NameAdding Nodes to a ClusterMultiple Seed NodesDynamic Ring ParticipationSecurityUsing SimpleAuthenticatorProgrammatic AuthenticationUsing MD5 EncryptionProviding Your Own AuthenticationMiscellaneous SettingsAdditional ToolsViewing KeysImporting Previous ConfigurationsSummary

Query Differences Between RDBMS and CassandraNo Update QueryRecord-Level Atomicity on WritesNo Server-Side Transaction SupportNo Duplicate KeysBasic Write PropertiesConsistency LevelsBasic Read PropertiesThe APIRanges and SlicesSetup and Inserting DataUsing a Simple GetSeeding Some ValuesSlice PredicateGetting Particular Column Names with Get SliceGetting a Set of Columns with Slice RangeCountsReversedGetting All Columns in a RowGet Range SlicesMultiget SliceDeletingBatch MutatesBatch DeletesRange GhostsProgrammatically Defining Keyspaces and Column FamiliesSummary
Basic Client APIThriftThrift Support for JavaExceptionsThrift SummaryAvroAvro Ant TargetsAvro SpecificationAvro SummaryA Bit of GitConnecting Client NodesClient ListRound-Robin DNSLoad BalancerCassandra Web ConsoleHector (Java)FeaturesThe Hector APIHectorSharp (C#)ChirperChiton (Python)Pelops (Java)Kundera (Java ORM)Fauna (Ruby)Summary
LoggingTailingGeneral TipsFollowing alongWarning signsOverview of JMX and MBeansMBeansIntegrating JMXInteracting with Cassandra via JMXCassandra’s MBeansorg.apache.cassandra.concurrentorg.apache.cassandra.dborg.apache.cassandra.gmsorg.apache.cassandra.serviceStorageServiceStreamingServiceCustom Cassandra MBeansRuntime Analysis ToolsHeap Analysis with JMX and JHATDetecting Thread ProblemsHealth CheckSummary
Getting Ring InformationInfoRingRange TokensGetting StatisticsUsing cfstatsUsing tpstatsBasic MaintenanceRepairFlushCleanupSnapshotsTaking a SnapshotClearing a SnapshotLoad-Balancing the Clusterloadbalance and streamsDecommissioning a NodeUpdating NodesRemoving TokensCompaction ThresholdChanging Column Families in a Working ClusterSummary
Data StorageReply TimeoutCommit LogsMemtablesConcurrencyCachingBuffer SizesUsing the Python Stress TestGenerating the Python Thrift InterfacesGetting ThriftRunning the Python Stress TestStartup and JVM SettingsTuning the JVMSummary
What Is Hadoop?Working with MapReduceCassandra Hadoop Source PackageRunning the Word Count ExampleOutputting Data to CassandraHadoop StreamingTools Above MapReducePigHiveCluster ConfigurationUse CasesRaptr.com: Keith ThornhillImagini: Dave GardnerSummary
Nonrelational DatabasesObject DatabasesXML DatabasesSoftwareAG TaminoeXistOracle Berkeley XML DBMarkLogic ServerApache XindiceSummaryDocument-Oriented DatabasesIBM LotusApache CouchDBMongoDBRiakGraph DatabasesFlockDBNeo4JKey-Value Stores and Distributed HashtablesAmazon DynamoProject VoldemortRedisColumnar DatabasesGoogle BigtableHBaseHypertablePolyglot PersistenceSummary

Content preview from Cassandra: The Definitive Guide

Preface

Why Apache Cassandra?

Apache Cassandra is a free, open source, distributed data storage system that differs sharply from relational database management systems.

Cassandra first started as an incubation project at Apache in January of 2009. Shortly thereafter, the committers, led by Apache Cassandra Project Chair Jonathan Ellis, released version 0.3 of Cassandra, and have steadily made minor releases since that time. Though as of this writing it has not yet reached a 1.0 release, Cassandra is being used in production by some of the biggest properties on the Web, including Facebook, Twitter, Cisco, Rackspace, Digg, Cloudkick, Reddit, and more.

Cassandra has become so popular because of its outstanding technical features. It is durable, seamlessly scalable, and tuneably consistent. It performs blazingly fast writes, can store hundreds of terabytes of data, and is decentralized and symmetrical so there’s no single point of failure. It is highly available and offers a schema-free data model.

Is This Book for You?

This book is intended for a variety of audiences. It should be useful to you if you are:

A developer working with large-scale, high-volume websites, such as Web 2.0 social applications
An application architect or data architect who needs to understand the available options for high-performance, decentralized, elastic data stores
A database administrator or database developer currently working with standard relational database systems who needs to understand how to implement ...