Roadmap:OperatingPentahoatScaleJensBleuelSeniorProductManager,Pentaho

Agenda– WorkerNodes

HearaboutnewupcomingcapabilitiesforscalingoutthePentahoplatforminlargeenterpriseoperations.Thiswillcover8.0androadmaptopics.

• WorkerNodes:OverviewandBusinessBenefits

• HowisthisdifferentfromAEL/HadoopMapReduce

• TypicalCustomerScenarios

• Architecture&CapabilitiesincludingMonitoring&Logging

• ImprovementsinRelatedAreas

• Demonstration

• Availability&Roadmap

WorkerNodes– Overview

• WorkerNodescanscaleworkitemsacrossmultiplenodes(containers)like:

– PDIjobsandtransformations(in8.0)– Reportexecutions(notin8.0)– […]

• Itoperateseasilyandsecurelyacrossanelasticarchitecture,whichaddsadditionalmachineresourcesastheyarerequiredforprocessing

• WorkerNodescanoperateonpremiseorinthecloud

• UsesPopulartechnologiesunderthehoodsuchasDocker(ContainerPlatform),Chronos(Scheduler)andMesos/Marathon(ContainerOrchestration)

WorkerNode(a)

WorkerNode(b)

WorkerNode(c…)DistributeandScale

WorkerNodes– BusinessBenefits

Largeenterprisesneedtheabilitytoseamlesslyandefficientlyspinupresourcestohandle100s+workitemsatdifferenttimes,withdifferentdependenciesandprocessingrequirements.WorkerNodesaddressestheseneedsanddelivers:• FastertimetovalueandreducedTCObecauseitenablescustomerstodeploytheirownscale-outprocesseswithoutrequiredservices• Managechangingworkloadsmoreefficientlybyspinningresourcesupanddownasneeded• Increasedbusinessagilitythankstocontainerization– whichenablesportabilityofprocessesacrosson-prem andcloudenvironmentswithouttheneedtore-engineerthem.– Eveninpureon-prem,WNprovideselasticityandresourceoptimization.

HowIsThisDifferentfromAEL/HadoopMapReduce?

Thesetwoarchitecturescanalsobecombined:WithinaWorkerNode,aPDItransformationcanalsoscaleoutwithAELorMapReduce

SCALEOUTONDATA

SCALEOUTONPROCESSES(WORKITEMS)

AEL/HadoopMapReduce(simplified):• Dataisdistributedacrossnodes• Theprocessingtakesplaceatthenodelevel• Helpsinscaleoutdatavolume

WorkerNodes(simplified):• WorkItemslikePDIJobs,PDITransformationsgetdistributedacrossnodes– thisisabouttheprocessingandorchestration(incontrasttodistributingdata)

• HelpsinscaleoutPentahoprocesses

TypicalCustomerScenarios

CustomerType TypicalNumberofWorkItems Scale-OutNeed

Small Upto10 No

Medium 10through100 Sometimes

Enterprisewithonedepartment +/- 100 Yes

Enterprisewithmultipledepartments Hundredsorthousands Yes

TypicalCustomerExamples– SLA’sandTimeWindows

• NeedtomeetcustomerSLA’s– Datafromhundredsofsourcesneedtogetcollectedandaggregated– ThisisdonebyhundredsofPDIjobsandtransformations– Allthesejobsandtransformationsneedtobefinishedwithinadefinedtimewindow(forexamplebetween5amand7am)sothatthedataisavailableandaccurateforthetargetaudience

• WorkerNodesprovidesthetechnologytorunprocessesinparallelandscaleoutwhenneeded,forexampleatpeaktimes(endofmonth)

TypicalCustomerExamples– SharedServices

Exampleofoneproject:

• 800dailybatchesfromdifferentdepartmentsinanenterprise

• Oneserverwith120GBmemoryandmanyCPUs

• ThismachinehostslotsofVMinparallel

Issue:Whenthereistoomuchworkload,onemachineisnotenough

• WorkerNodessolvesthisinscalingoutonacluster

TypicalCustomerExamples– ScalableonDemand

• Needtosupportgrowingdatavolumesandcustomerrequirements

• WorkerNodesprovidesaflexibleandscalablearchitectureon-promiseorinthecloudforgrowingdemand

• Thisisseamlessanddoesnotneedtochangetheunderlyingarchitecture

WorkerNode(1)

WorkerNode(2)

WorkerNode(3)DistributeandScale

WorkerNode(1)

WorkerNode(2)

WorkerNode(3)DistributeandScale

WorkerNode(4)

WorkerNode(5)

BASETIMES PEAKTIMES

WORKERNODES

OrchestrationFramework

ContainerFramework

WorkerNodes– Newin8.0

• Containerizedscale-out• PentahoPDI“workitems”

PentahoServerWN1e.g.KJB

WN2e.g.KTR

WN…n“Executor”

Orchestration(Scheduler,monitoring,security,etc.)

Controller

Master(Standby)

Master(Standby)

Master(Working)

PentahoRepository

PentahoClients

WorkerNodesCapabilities

• Deployconsistentlyinphysical,virtual,andcloudenvironmentsAdaptstocustomerneeds(bare-metalvs.virtualizationvs.Cloud)andnoneedtomodifytheproductwhenthestrategychanges

• ScaleandloadbalanceservicesThishelpstodealwithpeaksandlimitedtime-windows,allocatetheresourcesthatareneeded.

• HybriddeploymentscanbeusedtodistributeloadEvenwhentheon-premise resourcesarenotsufficient,scalingoutintotheCloudispossibletoprovidemoreresources.

MonitoringandLogging

Monitoring– Overview

Monitoring– WorkerNodeExample

ImprovementsinRelatedAreasOpenandSaveDialogs

• Wheneveryousaveanewtransformation/jobintotherepository,thedefaultfolderissettotheuser’shomefolder.

PainPoint:SaveaNewJob/Transformation

Inpreviousversions:Theuserwillneedtochangethefolderforeverytimetheysaveanewtransformationorjob.

NewSaveDialogin8.0– Overview

• Remembersthelastopenedfolder!

• Justenterthefilename!(and/orchangethefolder)

• SimilartotheOpenDialogwithadditionalfunctionality(seenextslide).

NewOpenDialogin8.0– Overview

Recents

Openshowsthelastopenedfolder.Thisisabigtimesaver!

Search

ImprovementsinRelatedAreasRunConfigurations

PainPoint:RemotePentahoServerExecutionbefore 8.0

ToexecuteonthePentahoServerbefore8.0,youneedtodefineaSlaveserverandgivethecredentials. ThenexecuteontheselectedServer.

ExecuteonthePentahoServer

• ByselectingthePentahoserveroption,youdonotneedtodefineaSlaveserveranymorewhenyouwanttoexecuteremotely.

• Behindthescenes,thisoptionexecutesthetransformationorjobviatheScheduler.Thisisthesameasyouwoulddoa“ScheduleNow.”

Thisnewfunctionalityimprovestheeaseofuse,alsoforWorkerNodes

RunConfigurationswithinJobEntries

• RunConfigurationcanbeusedintheRundialogandalsointhejobentriesthatcouldexecutejobsortransformationsremotelyandonWorkerNodes

7.1 Example

8.0

Demonstration

AvailabilityandRoadmap

Availability

• WorkerNodesisEEonly

• Initially,8.0WorkerNodeswillbeLimitedAvailability– Fullysupported,productiondeployment– Distributiontoalimitednumberofcustomers

• Requiresadditionaldownloadandimplementationservices

• PentahoServer&RepositoryasaServiceincludingHighAvailability

• ImprovedMonitoringandLogging

• ExtendtootherPentahoworkitemssuchasReports

• IntegratedwithotherHitachiVantara ServicesandProducts

Roadmap

ContainerFrameworkPentahoServer

WN1e.g.KJB

WN2e.g.KTR

WN…n“Executor”

PentahoRepository

Summary

Whatwecoveredtoday:

• TheupcomingcapabilitiesforscalingoutthePentahoplatformandwhentousethem

• Howtousethenewwayofscalingoutworkitems(PentahoprocessessuchasPDIjobsandtransformations)acrossmultiplenodes

NextStepsWanttolearnmore?

• Meet-the-Expert:– PedroTeixera

• Otherrecommendedbreakoutsessions:– MattHoward:Pentaho8.0andRoadmap– RakeshSaha andJensBleuel:Roadmap:ProcessingBigData– MattCasters:PDIBestArchitecturePractices– SteveSzabo:PDISizingOverviewandCaseStudy– JonathanJarvis:UnderstandingParallelismwithPDIandAdaptiveExecutionwithSpark– MarkBurnett:UnderstandingtheBigDataTechnologyEcosystem