book

Learning and Operating Presto

by Angelica Lo Duca, Tim Meehan, Vivek Bharathan, Ying Su

September 2023

Intermediate to advanced

191 pages

4h 32m

English

O'Reilly Media, Inc.

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Why We Wrote This BookWho This Book Is ForConventions Used in This BookUsing Code ExamplesO’Reilly Online LearningHow to Contact UsAcknowledgmentsAngelica Lo DucaTim MeehanVivek BharathanYing Su
Data Warehouses and Data LakesThe Role of Presto in a Data LakePresto Origins and Design ConsiderationsHigh PerformanceHigh ScalabilityCompliance with the ANSI SQL StandardFederation of Data SourcesRunning in the CloudPresto Architecture and Core ComponentsAlternatives to PrestoApache ImpalaApache HiveSpark SQLTrinoPresto Use CasesReporting and DashboardingAd Hoc QueryingETL Using SQLData LakehouseReal-Time Analytics with Real-Time DatabasesIntroducing Our Case StudyConclusion
Presto Manual InstallationRunning Presto on DockerInstalling DockerPresto Docker ImageBuilding and Running Presto on DockerThe Presto SandboxDeploying Presto on KubernetesIntroducing KubernetesConfiguring Presto on KubernetesAdding a New CatalogRunning the Deployment on KubernetesQuerying Your Presto InstanceListing CatalogsListing SchemasListing TablesQuerying a TableConclusion
Service Provider InterfaceConnector ArchitecturePopular ConnectorsThriftWriting a Custom ConnectorPrerequisitesPlugin and ModuleConfigurationMetadataInput/OutputDeploying Your ConnectorApache PinotSetting Up and Configuring PrestoPresto-Pinot Querying in ActionConclusion
Setting Up the EnvironmentPresto ClientDocker ImageKubernetes NodeConnectivity to PrestoREST APIPythonRJDBCNode.jsODBCOther Presto Client LibrariesBuilding a Client Dashboard in PythonSetting Up the ClientBuilding the DashboardConclusion
The Emergence of the LakehouseData Lakehouse ArchitectureData LakeFile StoreFile FormatTable FormatQuery EngineMetadata ManagementData GovernanceData Access ControlBuilding a Data LakehouseConfiguring MinIOConfiguring HMSConfiguring SparkRegistering Hudi Tables with HMSConnecting and Querying PrestoConclusion
Introducing Presto AdministrationConfigurationPropertiesSessionsJVMMonitoringConsoleREST APIMetricsManagementResource GroupsVerifiersSession Properties ManagersNamespace FunctionsConclusion
Introducing Presto SecurityBuilding Secure Communication in PrestoEncryptionKeystore ManagementConfiguring HTTPS/TLSAuthenticationFile-Based AuthenticationLDAPKerberosCreating a Custom AuthenticatorAuthorizationAuthorizing Access to the Presto REST APIConfiguring System Access ControlAuthorization Through Apache RangerConclusion
Introducing Performance TuningReasons for Performance TuningThe Performance Tuning Life CycleQuery Execution ModelApproaches for Performance Tuning in PrestoResource AllocationStorageQuery OptimizationAria ScanTable ScanningRepartitioningImplementing Performance TuningBuilding and Importing the Sample CSV Table in MinIOConverting the CSV Table in ORCDefining the Tuning ParametersRunning TestsConclusion
Introducing ScalabilityReasons to Scale PrestoCommon IssuesDesign ConsiderationsAvailabilityManageabilityPerformanceProtectionConfigurationHow to Scale PrestoMultiple CoordinatorsPresto on SparkSpillingUsing a Cloud ServiceConclusion

Overview

The Presto community has mushroomed since its origins at Facebook in 2012. But ramping up this open source distributed SQL query engine can be challenging even for the most experienced engineers. With this practical book, data engineers and architects, platform engineers, cloud engineers, and software engineers will learn how to use Presto operations at your organization to derive insights on datasets wherever they reside.

Authors Angelica Lo Duca, Tim Meehan, Vivek Bharathan, and Ying Su explain what Presto is, where it came from, and how it differs from other data warehousing solutions. You'll discover why Facebook, Uber, Alibaba Cloud, Hewlett Packard Enterprise, IBM, Intel, and many more use Presto and how you can quickly deploy Presto in production.

With this book, you will: