用一項服務取代五項服務 – 在 AWS 上使用 MySQL HeatWave.pdf

1、Replace Five Services with One Using MySQL HeatWave Natively on AWSMandy PangSenior Principal Product ManagerMySQL HeatWaveMySQL and HeatWave Summit2024AgendaCopyright 2024,Oracle and/or its affiliates.All rights reserved.Complexity of using AWS servicesMySQL HeatWave on AWSCustomer success storiesC

2、opyright 2024,Oracle and/or its affiliates.All rights reserved.OLTPData Platform ComplexityYou start with an OLTP database application Copyright 2024,Oracle and/or its affiliates.All rights reserved.AnalyticsOLTPData Platform ComplexityYou start with an OLTP database application Analytics will give

3、LOB managers valuable insightsETLRDSCopyright 2024,Oracle and/or its affiliates.All rights reserved.Machine LearningOLTPETLData Platform ComplexityYou start with an OLTP database application Analytics will give LOB managers valuable insightsMachine learning predictions will improve the customer expe

4、rienceETLETLRDSRedshiftAnalyticsCopyright 2024,Oracle and/or its affiliates.All rights reserved.Machine LearningOLTPETLData Platform ComplexityYou start with an OLTP database application Analytics will give LOB managers valuable insightsMachine learning predictions will improve the customer experien

5、ceLakehouse will deliver insights into unstructured dataETLETLLakehouseETLRDSRedshiftAnalyticsSageMakerCopyright 2024,Oracle and/or its affiliates.All rights reserved.AnalyticsMachine LearningGen AIOLTPETLETLETLETLETLData Platform ComplexityYou start with an OLTP database application Analytics will

6、give LOB managers valuable insightsMachine learning predictions will improve the customer experienceLakehouse will deliver insights into unstructured dataGenerative AI will give results in natural languageETLETLETLETLLakehouseRDSRedshiftSageMakerAthenaCopyright 2024,Oracle and/or its affiliates.All

7、rights reserved.AnalyticsMachine LearningGen AIOLTPETLETLETLETLETLData Platform ComplexityYou start with an OLTP database application Analytics will give LOB managers valuable insightsMachine learning predictions will improve the customer experienceLakehouse will deliver insights into unstructured d

8、ataGenerative AI will give results in natural languageVector store provides context to LLM for more relevant resultsETLETLETLETLLakehouseVector storeETLETLRDSRedshiftSageMakerAthenaBedrockCopyright 2024,Oracle and/or its affiliates.All rights reserved.ETLETLETLETLETLData Platform Complexity at AWSET

9、LETLETLETLETLETLRDSRedshiftSageMakerAthenaGlueComplex ETL processesStale and obsolete dataDifficult to maintain Security vulnerabilitiesRequires specialized skills5 Separate Cloud ServicesBedrockOpenSearchMySQL HeatWave overviewTransactions,real-time analytics,machine learning and GenAI across data

10、warehouse and data lake in one serviceMySQL HeatWaveAnalyticsOLTPSocial,eCommerce,IoT,gaming,fintech apps.Analytics and ML Social,eCommerce,IoT,gaming,fintech apps.Analytics and ML toolstoolsObject StoreDatabase Database exportsexportsIn-database MLDatabase exportsStreaming dataData SourcesEnterpris

11、e AppsWeb/SocialLog filesIoTMySQL MySQL storagestorageFor both non-MySQL and MySQL workloadsMySQL AutopilotQueriesQueriesResultsResultsVector store*Vector store*GenAIGenAI*Coming soon*Coming soonOracle AWS accountMySQL HeatWave on AWSCONSOLE,CONTROL PLANE,AND DATA PLANE RUN NATIVELY IN AWSMachineLea

12、rningAutopilotAnalyticsTransactionProcessingConsoleControl planeData planeDataApplicationsAWS CloudCustomer AWS HeatWave8.1MySQL HeatWave on AWS current availabilityOracle CloudWorld Copyright 2023,Oracle and/or its affiliates12N.Virginia(us-east-1)TOKYO(ap-northeast-1)MUMBAI(ap-south-1)AWS Commerci

13、al RegionFRANKFURT(eu-central-1)LONDON(eu-west-2)20X FASTER THAN REDSHIFT,16X FASTER THAN SNOWFLAKE,16X FASTER THAN BIG QUERY,5X FASTER THAN SYNAPSE TPC-H 4TBFaster than Redshift,Snowflake,Big Query,Synapse020406080100120140Average Execution Time(Sec)*Benchmark queries are derived from the TPC-H ben

14、chmarks,but results are not comparable to published TPC-H benchmark results since these do not comply with the TPC-H specifications.*Results from Sept 2022HeatWaveHeatWave(10 nodes)Redshift(2*ra3.4xlarge)Snowflake(Medium)Google BigQuery(400 slots)MS Synapse(DW1500c)7X BETTER THAN REDSHIFT,10X BETTER

15、 THAN SNOWFLAKE,12X BETTER THAN BIG QUERY,4X BETTER THAN SYNAPSE TPC-H 4TBBetter price performance thanRedshift,Snowflake,Big Query,Synapse051015202530Average Execution Time(Sec)*Benchmark queries are derived from the TPC-H benchmarks,but results are not comparable to published TPC-H benchmark resul

16、ts since these do not comply with the TPC-H specifications*Results from Sept 2022HeatWaveOnly compute costs are considered abovePricing for Redshift is based on 1-year reserved instance,paid upfront.Snowflake is based on standard editionstandard editionPricing for Google Big Query is based on monthl

17、y flat rate commitment.Azure Synapse is based on 1-year reserved pricingHeatWave(10 nodes)Redshift(2*ra3.4xlarge)Snowflake(Medium)Google BigQuery(400 slots)MS Synapse(DW1500c)MySQL HeatWave offers up to 10 x better throughput than Aurora for OLTPAuto thread poolingTPCTPC-C_100W(10G,Data fits in Buff

18、er Pool)C_100W(10G,Data fits in Buffer Pool)01000200030004000500060007000141664128256512102420484096Throughput(Transactions/s)Throughput(Transactions/s)ConcurrencyConcurrencyMySQL HeatWaveAmazon Aurora*Benchmark queries are derived from the TPC-C benchmarks,but results are not comparable to publishe

19、d TPC-C benchmark results since these do not comply with the TPC-C specifications.Unbeatable price/performance for OLTPCopyright 2024,Oracle and/or its affiliates.All rights reserved.$59,587$228,072$225,394$188,604$0$50,000$100,000$150,000$200,000$250,000MySQL HeatWaveon AWSAmazon RDSMicrosoft Azure

20、Google Cloud SQLMySQL HeatWave on AWS for OLTP,1 Year TCO200 vCPUs,10TB StorageMySQL HeatWave:1 ECPU,all regions have the same price.Amazon RDS:Intel R5 16GB/Core,AWS US East.Azure:Memory Optimized Intel 20GB/Core,MS Azure US-East.Google:High Memory N1 Standard Intel 13GB/Core,GCP Northern Virginia.

21、3.8xUnbeatable price/performance for small OLTP AWS RDS/Aurora shape instancesCopyright 2024,Oracle and/or its affiliates.All rights reserved.$429$596$718$1,191$1,437$391$476$782$952$0$200$400$600$800$1,000$1,200$1,400$1,600MySQL HeatWave onAWSRDS MySQLRDS AuroraRDS MySQLRDS AuroraMySQL.2.16GBdb.t3.

22、mediumdb.t3.largeMySQL HeatWave vs AWS RDS t3 db instancePAYG1 year pre-paid1.39x cheaper than RDS t3.medium1.67x cheaper than Aurora t3.medium2.78x cheaper than RDS t3.large2.35x cheaper than Aurora t3.largeNote:MySQL.2.16GB(2 vCPU,16GB MEM)RDS t3.medium(2 vCPU,4GB MEM)RDS t3.large(2 vCPU,8GB MEM)H

23、eatWave AutoML:In-database machine learningEliminates tedious and laborious stepsSimple to use interface for beginner or advanced ML usersAutomatically selects algorithm and tunes itExplainable model behavior and predictionsFast training allows to quickly iterate to achieve desired outcomeIn-databas

24、e MLPreprocessingAlgorithm SelectionAdaptive SamplingHyperparameter OptimizationModel ExplainerPrediction ExplainerTuned ModelModel trainingModel inferenceModel explanationsAWS Aurora AWS Aurora exportexportAWS RedshiftAWS RedshiftexportexportHeatWaveInnoDBHeatWaveMySQLMySQL exportexportIndustries a

25、nd use cases with HeatWave AutoMLDigital MarketingCost per acquisitionTargeted campaignsCustomer classificationFinTechLoan default predictionIdentify loan extensionsLoan approvalE-CommerceVideos for usersLottery suggestionsProduct upsellGamingPlayer churn detectionAdjust game difficultyIdentify game

26、 hackersInternet Of ThingsAirport ticketingRain water levelAir pollutionEducationPredict student successMonitor student behaviorHIPPA ComplianceServicesErroneous ledge entriesPredict future lossesPredict price elasticityManufacturingReduce warranty claimsDefective part identificationDetect anomalies

27、 in suppliesMachine learning with HeatWave is fast,cost effective,accurate and sclable faster than Redshift 25xof the cost of Redshift1%MySQL HeatWave on AWS ConsoleCopyright 2024,Oracle and/or its affiliates.All rights reserved.MonitoringInteractive Query UI&Data ManagementHeatWave MLMySQL Autopilo

28、tQuick start with a few clicksCopyright 2024,Oracle and/or its affiliates.All rights reserved.Sample DataImport sample schema such as airportdb and TPCH into the DB SystemRun sample analytics queriesEvaluate MySQL HeatWave performance and featuresStarter DB SystemCreate MySQL HeatWave instance with

29、predefined configurations and sample data pre-loaded to HeatWaveHeatWave AutoML consoleDemocratizing machine learningVisual interfaceEnables business analysts to build,train,run,and explain ML models.No SQL and no coding requiredAbility to explore“What-if”scenariosAll processing is done inside the d

30、atabaseNo additional cost to users Aiwifi migrates from Amazon RDS to MySQL HeatWave on AWSCopyright 2024,Oracle and/or its affiliates“With MySQL HeatWaves incredible performance and built-in machine learning,we knocked down previous barriers to growth.Aiwifi estimates that MySQL HeatWave replaced u

31、p to 5 external systems.Making HeatWave available on multiple cloud platforms is a very smart move by Oracle.”Eric Aguilar,CEO&CTO,Aiwifi Challenge:Aiwifi is a Mexican company developing Wi-Fi solutions that connect shoppers to websites through customized captive portals.Its value proposition is to

32、gather valuable customer data by tracking user profiles and activity.Upon starting up in 2019,Aiwifi chose AWS as its platform and Amazon RDS as the backend database.However,as the business rapidly grew and generated heavy data loads,the lack of performance became a bottleneck for sustained growth,a

33、nd database costs became a heavy challenge.In 2023,it migrated from Amazon RDS to MySQL HeatWave running natively inside AWS.Products Used:Oracle MySQL HeatWaveResults:Queries ran 13X faster and loading time on captive portals dropped by 50%,allowing Aiwifi to quickly onboard new customers without a

34、dded costsCosts were reduced by 50%.The MySQL HeatWave high performance allowed using a smaller instance and high data egress fees were eliminatedMySQL HeatWave efficiently handles complex queries on more than 40 million records to provide real-time analytics dashboardsThe need for query optimizatio

35、n was eliminated,allowing Aiwifis developers to focus on building machine learning models with HeatWave AutoMLML is used to segment their user base and create more personalized marketing content as well as to predict offers that could be of interest to different customer segmentsRead storySoftware c

36、ompany utilizing ML/GenAI50%Reduction in ML ActivityReduction in Data Cleaning,Model Selection,Model Tuning and Training Time15-25%Performance ImprovementUsing Auto-Indexing,Auto-ML and JavascriptMove processing closer to Data to improve latency(Javascript)Tech.Consolidation Seamlessly extending rel

37、ational model to support OLAP/ML/AI workloadReduction in maintaining and deploying multiple Technology stack and training Company:Provides Automation of ITSM&GRC in an Integrated PlatformUse Cases:1.Pre-configured processes and workflows eliminating spreadsheets and manual work2.Maximum visibility a

38、nd data insights allows users to correlate,analyze,and remediate issues3.Flexible Platform that can scale and simplify existing stackSolution:Leveraging HeatWave to Automate IT&Security ManagementEat EasyFood DeliveryOracle CloudWorld Copyright 2024,Oracle and/or its affiliatesDubai-based online agg

39、regator connecting thousands of its users to their favorite restaurants,making online ordering easier,reliable and convenient.Use Case Predict food deliver time.Suggest food/restaurant based on past actions.Summarize menu for the selected restaurant.Model Type Regression,Recommendation,Generative AI

40、Results Developed ML models in days that would have otherwise taken months Database developers were able to build the models without ML expertise Simplified infrastructure with no complex ETL to manage and one platform providing OLTP,Analytics,ML and GenAI Consistent interface across various ML mode

41、l types simplified learning for Eat Easy development teamMySQL HeatWave on AWSCombine FIVE AWS services into ONE MySQL HeatWave runs natively on AWS,optimized for AWS infrastructure Data doesnt leave AWS no data egress costs,and avoids compliance approvals Lowest latency access to MySQL HeatWave Tight integration with the AWS ecosystem S3,CloudWatch,PrivateLink Easier migration from other databases(e.g.,Amazon Aurora,Redshift,Snowflake)