Oracle TimesTen In-Memory Database 18 · Oracle Database In-Memory Option • Dual-Format In-Memory...

Copyright©2018,Oracleand/oritsaffiliates.Allrightsreserved.|

OracleTimesTenIn-MemoryDatabase18.1ScaleoutFunctionality,ArchitectureandPerformance

ChrisJenkinsSeniorDirector,In-MemoryTechnologyTimesTenProductManagement


BestIn-MemoryDatabases:ForBothOLTPandAnalytics

Application Application Application

Application Application Application

OracleTimesTen In-MemoryDatabase• Lightweight,highly-availableIMDB• Primaryusecase:ExtremeOLTP• Microsecond responsetime• MillionsofTPSoncommodityhardware

OracleDatabaseIn-MemoryOption• Dual-FormatIn-MemoryDatabase• Primaryusecase:RealTimeAnalytics• BillionsofRows/Sec scanrate• Fastermixed-workloadenterpriseOLTP

Ø Fewerindexesneededtosupportanalytics

In-MemoryforOLTP

In-MemoryforAnalytics

3


20+YearsofExtremePerformanceandReliabilityOracleTimesTen– ClassLeadingIn-MemoryDatabase

4

• FirstcommercialIn-MemoryRDBMS

• ReplicationforHA• OnlineUpgrades• Application-tier

CacheforOracleDatabase

• Parallellogmanager• PL/SQLandOCISupport• OracleClusterwareIntegrationforreplicationmanagement• CacheGridforScaleOut• ODP.NETSupport• BLOB,CLOB,NCLOBdatatypes

• ParallelReplication• In-MemoryAnalytics• ColumnarCompression• IndexAdvisor• OracleRSupport• In-MemoryStarJoin• OracleGoldenGateIntegration

• ParalleldataimportfromOracleDatabase

• Paralleldatabaserestart

• Highlyconcurrentrangeindexes

• ParallelReplicationwithcommitorderoptimization

• OracleRACintegration• NationalLanguage

Support• OracleDataTypes

support• SQLDeveloper

Integration• EnterpriseManager

integration

TimesTen 6TimesTen 7

Pre-Oracle acquisition TimesTen 11g11.2.1

TimesTen 11g11.2.2

TimesTen 11.2.2.xEnhancements

1996|

2005

TimesTen 18.1

with Scaleout

• DistributedFault-TolerantIn-MemoryDatabase

• Allactivedatacopies• TransparentdistributedSQLexecution

• ACIDTransactions• GlobalSecondaryIndexes

• Andmore…

2006|

2008

2009|

2011

2012|

2013

2014|

20172018


MostWidelyUsedCommercialRelationalIMDBDeployedbythousandsofcompanies

5


MultipleDeploymentOptionsOracleTimesTenIn-MemoryDatabaseTimesTenClassic

1. Standalone/ReplicatedRelationalIMDB• Lowlatency/highthroughputapplications• ISV/OEMembeddedsolutions

2. CacheforOracleDatabase• AccelerateOracleDatabaseOLTPapplications• HAoptionviaTimesTenReplication

Microsecondresponsetime,millionsofTPSthroughput

TimesTenScaleout– newin18.1

3. Distributed,SharedNothing,RelationalIMDB• Highthroughoutandstoragecapacity• Transparentdatadistribution• Elasticscalability• Faulttolerant

HundredsofmillionsofTPSthroughput

Application

Application

Application

Application

6

Copyright©2018,Oracleand/oritsaffiliates.Allrightsreserved.| 7

TimesTenScaleoutBenefitsFast&Scalable

…

• Lowlatencyandhighthroughput

• Addelementsonlinetoincreasethroughputandcapacity

FaultTolerant

• Nosinglepointoffailure• Fullypersistent• K-SafetyforHA• Allelementsactiveforreadsandwrites

…

SingleDBimage

• Appearsasasingledatabasetoapplications

• Datalocationtransparency• Connecttoanyelementandaccessalldata

• Noneedtode-normalize

Customers OrdersProducts LineItems

• HighlycompatiblewithOracledatatypes,SQL&PLSQL

• ManylanguagesandAPIs• Monitoringandmanagementfromasinglelocation

• DeployonpremisesorintheCloud

Easytodevelopfor,Easytodeploy

RESTAPIs


TimesTenScaleout- DatabaseElements

• Eachdatabaseconsistsofelements• Eachelement storesaportionofdatafromitsdatabase• Eachelement hasitsownsetofcheckpointfilesandtransactionlogfilesforpersistence&recovery• Theelement isthesmallestunitfordatabasepersistence,failurerecoveryandhighavailability

Element<n>

TxLogsCheckpoints

DatabaseElement

8

UnitofPersistenceandRecovery

SingleImageIn-MemoryDatabase


• Eachelementcontains:– Informationaboutallusers inthedatabase– Theschema oftheentiredatabase– Somerowsofeachtable inthedatabase

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Element1

CUSTOMER

ORDERS

PRODUCTS

Element2

CUSTOMER

ORDERS

PRODUCTS

TimesTenScaleout- DatabaseElementsA“logical”look


• DISTRIBUTE largetablesbyconsistenthashØDistributeCUSTOMERrowsonallelementsbyhashofCustomerID

• COLOCATE childtablerowswithparenttablerowtoincreaselocalityofreferenceØPlaceORDERSrowsinsameelementalongwithcorrespondingCUSTOMERrow

• DUPLICATE smallread-mostlytablesonallelementsformaximumlocalityØDuplicatethePRODUCTlistonallelements

10

TimesTenScaleout- DataDistribution

Servers

Element1 ElementN…

CUSTOMER

ORDERS

PRODUCTS

CUSTOMER

ORDERS

PRODUCTS

Distribute

Duplicate

Co-locate Co-locate

Specifiedatthetablelevel


• Consistenthashalgorithm• Byhashingthedistributionkeycolumn(s)orprimarykeycolumn(s)

• Rowsare“randomly”andevenlydistributedacrosselements

• Thedefaultdistributionmethod• Thereare‘K’copiesofeachrowforHA,where‘K’istheK-safetyfactor

• Appropriateformosttables

CREATE TABLE CUSTOMER (ID NUMBER NOT NULL PRIMARY KEY,NAME VARCHAR2(100)…

) DISTRIBUTE BY HASH;

11

DistributebyHash


CUSTOMER CUSTOMER

Distributebyhash

1,10,2244,60

2,11,2448,55


• “Child”rowsarelocatedinthesameelementsas“parent”rows

• Foreignkeysdefine“parents”and“children”

• Appropriatefortablesthat:• Arelogically“children”ofasingle“parent”table

• Parentandchildwilloftenbereferencedtogetherinqueries

• Locatingrelateddatatogetherprovidesbestperformanceprovidedaccessismainlyviathe‘reference’FK

• Multiplelevelssupported

12

DistributebyReferenceCREATE TABLE CUSTOMER (

ID NUMBER NOT NULLPRIMARY KEY,

NAME VARCHAR2(100)...

) DISTRIBUTE BY HASH;

CREATE TABLE ORDERS (ID NUMBER NOT NULL

PRIMARY KEY,CUST_ID NUMBER NOT NULL,...CONSTRAINT FK_CUSTFOREIGN KEY (CUST_ID) REFERENCES CUSTOMER(ID),...

) DISTRIBUTE BY REFERENCE(FK_CUST);

ElementN…

CUSTOMER

ORDERS

Distribute

Co-locate

Element1

CUSTOMER

ORDERSCo-locate

1,10,2244,60 2,11,2448,55

ORDERSforcustomers

1,10,2244,60

ORDERSforcustomers

2,11,2448,55


• Everyrowispresentineveryelementofthegrid

• Appropriatefortablesthatare:• Relativelysmall• Frequentlyread• Infrequentlymodified

CREATE TABLE PRODUCTS(PROD_ID NUMBER

NOT NULL PRIMARY KEY,

PROD_NAME CHAR(12) ) DUPLICATE;

13

Duplicate


1,Books2,Food3,Tools4,Toys

PRODUCTSDuplicate

PRODUCTS

1,Books2,Food3,Tools4,Toys


TimesTenScaleout- HighAvailability

• Built-inHAviamultiplecopiesofthedata(K-safety)– Automaticallykeptinsync

• All replicasareactive forreadsandwrites– Increasesthecomputecapacity

• Transactionscanbeinitiatedfrom,andexecutedon,anyreplica• Queriesandtransactionscanspanany/allelements

K-safety,AllActive

A’

A

B’

BC

C’

D

D’

14

DataSpaceGroup1

DataSpaceGroup2

ReplicaSet1

ReplicaSet2

ReplicaSet3

ReplicaSet4


DatabaseFaultTolerance– NoApplicationDownTimeProvidedonefullcopyofthedatabaseisavailable

• Ifmultipleelementsfail,applicationswillcontinueprovidedthereisonecompletecopyofthedatabase− AutomaticfailoverforC/Sconnections

• Elementsrecoverautomaticallyafterfailure

• Ifanentirereplicasetisdown,thatdataisunavailableuntilitrecovers− Applicationcanexplicitly chooseto

acceptpartialresults

15

B’

A

C

A’

B

C’

D D’

DataSpaceGroup1

DataSpaceGroup2

ReplicaSet1

ReplicaSet2

ReplicaSet3

ReplicaSet4


TimesTenScaleout- ElasticScalability

Adding(andremoving)replicasets- Dataredistributedtonewelements- Workloadautomaticallyusesthenewelements

- Connectionswillstarttousenewelements

- Throughputincreasesduetoincreasedcomputeresources

Expandandshrinkthedatabasebasedonbusinessneeds

16

E’E

B’

A

C

A’

B

C’

D D’

ReplicaSet1

ReplicaSet2

ReplicaSet3

ReplicaSet4

ReplicaSet5

DataSpaceGroup1

DataSpaceGroup2


CentralizedInstallationandManagement• AllTimesTenScaleoutmanagementandadminoperationsareperformedfromasinglehost– Installingsoftware– Patchingsoftware– Configuration– Databasecreationandmanagement– Backupandrestore– Monitoring– Collectingdiagnostics

• Commandlineinterface• SQLDeveloper(GUI)interface

17


RS1_DSG1 RS1_DSG22PC

RS2_DSG1 RS2_DSG2

RS3_DSG1 RS3_DSG2

RS4_DSG1 RS4_DSG2

MGMT1

MGMT2

InternalNetwork

ExternalNetwork

2PC

2PC

2PC

…ZooKeeper

MembershipManagement

SSH&SCP

MOUNT/SCP

SSH

Managementinstances

DatainstancesRepositoryStorageHosts

REPO1

TimesTenScaleoutArchitectureOverview

18

SQL


Twomodes,supportedforall APIs(ODBC,OCI,JDBC,ODP.NET,…)TimesTenApplicationConnectivity

19

Host1

DatabaseElement

SharedMemory

App1

App2

AppN

…

Directmode• Appsrunonsamehostasdatabaseelement• Appsdirectlymapdatabasesharedmemory(viaTTengine)• Nocontextswitches,noIPCfordatabaseaccess• Ultralowlatency(inprocessdirectmemoryaccess)

TTServer1

TTServer2

TTServerN

…

Host2

App1

App2

AppN

…

Network

Client/servermode• TCP/IPconnectionsbetweenappandTTserverprocesses• TTServerprocessisamulti-threadeddirectmodeapp• Eachinteractioninvolves1ormoren/wroundtrips• MoreprocessesonDBhost,morecontextswitches• Moreoverhead,higherlatency

Youcanmixandmatchthesemodesasdesiredbasedonyourrequirements.


FactorsinfluencingTimesTenScaleoutperformance

1. Network Networkperformanceisvery important,especiallylatency

2. CPU,RAM,Storage Hardwarecapacityandperformanceisimportant

3. Numberofmachines/VMs One(ormore)Scaleoutinstancespermachine/VM

4. NumberofScaleout instances Onedatabaseelementperinstance

5. Datadistributionchoices Hash,reference,duplicate;distributionkeys

6. Localindexes Fasterdataaccess,slowerDML

7. Globalindexes Muchfasterdataaccess,muchslowerDML

8. Application Design,implementation,connectivitymode,datalocalityoptimisations (routingAPI)

Foragivenschema,datasetandSQLworkload


TimesTenScaleout:UnmatchedTransactionThroughput

5.003.22510.213.637

19.803.43639.244.125

76.167.743

144.211.475

0

20.000.000

40.000.000

60.000.000

80.000.000

100.000.000

120.000.000

140.000.000

160.000.000

0 10 20 30 40 50 60 70

SQLTransactions/secWorkload

• ThebenchmarkisanOLTPworkloadcalledTPTBM

• Mixedworkloadwith80%read /20% update (keybased)

• Directmode• Localityoptimization

Configuration

• OracleBareMetalCloud64xBM.HighIO1.36

• Platform- OracleLinuxx8664-bit• CPU- [email protected]• Network- 10GEthernet• Storage- NVMe DiskStorage

144MillionSQLTransactions/Second

LinearScalability

Numberofdatabaseelements

TransactionsperSecon

d


TimesTenScaleout:UnmatchedReadScalability

39.241.446

78.705.103

154.432.274

308.344.070

616.833.030

1.236.703.781

0

200.000.000

400.000.000

600.000.000

800.000.000

1.000.000.000

1.200.000.000

1.400.000.000

0 10 20 30 40 50 60 70

SQLSelects/secWorkload

• ThebenchmarkisanOLTPworkloadcalledTPTBM

• Workloadis100%read (keybased)

• Directmode• Localityoptimization

Configuration

• OracleBareMetalCloud64xBM.HighIO1.36

• Platform- OracleLinuxx8664-bit• CPU- [email protected]• Network- 10GEthernet• Storage- NVMe DiskStorage

Numberofdatabaseelements

TransactionsperSecon

d

1.2BillionSQLSelects/Second

LinearScalability


TimesTenScaleoutSummary

• Extremeperformanceandscalability• Singledatabaseimage,datalocationtransparency• FullSQL,ACIDtransactions,fullconsistency• AutomatichighavailabilityviaK-safety• Elasticscale-outandscale-in• Easytodeployandmanage• Easyapplicationdevelopment• On-premisesorClouddeployment

23

NewfeatureinTimesTen18.1Release


TimesTen VelocityScaleBetafeedbackSamsungWithitselasticallyscalablearchitectureandstrongHA,TimesTenScaleoutisaveryattractivesolutionforthenextgenerationofnetworksystems!-- ShinDongKeun,PrincipalEngineer

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ChinaMobileDuringthebetaweexperiencedthepowerfulcapabilitiesofOracleTimesTenScaleoutwithpleasure.Wefoundittobeuniqueamongstsimilartypesofproductsandare lookingforwardtoitappliedinour nextgeneration distributedrealtime billingsystem.-- ChenZhiheng,BusinessSupportSystemPlanner


• End-to-endresponsetime<<200millisecondsviaC/Sconnectionmode

• NewLBS(locationbasedservice)modulewith2000concurrentconnectionsinpeaktime

• Easy,automatichigh-availability• NoapplicationcodechangesmovingfromTimesTen11.2.2toTimesTenScaleout

• Scalabilityforfuturegrowth

WhyTimesTenScaleout?

ChinaMobileMarketingPromotionSystem

• Industry:Telecom•Business:Business&OperationSupportSystem•Application:MarketingPromotionSystem

⁻ PromoteChinaMobileproductstovariouschannelsincludingwebsite,APPS,SMS,WeChat,etc.

⁻ 30milliontargetsubscribers⁻ 15millionpromotionsperday

• Highlyconcurrentmobilelocationsbasedquery⁻ Foreverysubscriberinthemobilecarriernetwork

• Hightransactionthroughputwithconsistentlowlatency⁻ ReadmostlyapplicationwithsmallamountofDMLandDDL

• Scalabilitytoachievehigherthroughputandcapacity

ApplicationOverview

Challenges

Solution•TimesTenScaleoutwithK=2forHighAvailability

ChongqingMobileSubsidiary

MarketingPromotionSystemsupportsover30millionsubscribersanddelivers15milliontargetedmarketingmessagesperday.


Wanttolearnmore?• TimesTenOTNPortalhttp://www.oracle.com/technetwork/database/database-technologies/timesten/overview/index.html– ProductInformation• Presentations,usecases,whitepapers,FAQs,…

– SoftwareDownloads– ProductDocumentation– ScaleoutDemo/LearningVirtualBoxVMdownload

• TimesTenQuickStartandScaleoutSampleProgramsonGitHubhttps://github.com/oracle/oracle-timesten-samples

• Contactme:ChrisJenkins([email protected])

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QA&

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Oracle TimesTen In-Memory Database 18 · Oracle Database In-Memory Option • Dual-Format In-Memory...

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