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Frying your infrastructure. Are RDBMS really useful in a distributed realtime enterprise system ?. Overview. Quick SAP application infrastructure runthrough SAP application evolution: Enterprise Services & Smart Items Oops: frying the old infrastructure
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Frying your infrastructure Are RDBMS really useful in a distributed realtime enterprise system ?
Overview • Quick SAP application infrastructure runthrough • SAP application evolution: Enterprise Services & Smart Items • Oops: frying the old infrastructure • Lessons from the Web Services rewrite • Conclusions and SAP Research ideas
...on a common infrastructure • Portal (People, Roles, KM, Collaboration) • Exchange Infrastructure (Process Integration, Messaging) • Business Warehouse (Analytics) • APO (Planning, Optimization) • Search (TREX) • Web Application Server (Everything...) • (i.e. SAP takes a pretty broad definition of „application server“)
Connectivity Layer Web Client Web Browser Internet Communication Manager (HTTP/SOAP/etc.) Integration Layer Presentation Layer (JSP/etc.) • Presentation Logic • Navigation • Interaction with Client • Integration Tools: • Java Connector • .NET Connector • XML/XSLT • SOAP • WSDL Proxies • BAPI/RFC • IDoc • etc. Dispatcher Dispatcher Business Layer (J2EE/ABAP) • Business Logic • Status Administration • Locking/Enqueue Dispatcher Persistence Layer Database Interface (JDBC/OpenSQL) Anatomy of a workhorse: SAP Web Application Server Web Application Server ABAP/J2EE Database Server
Remarks on SAP Applications • SAP Web Application Server • Very robust, complete resource isolation (even for J2EE) • RDBMS (ab-) used as a persistence layer for almost everything • Not particularly lightfooted • Heavyweight sessions • Accrued portability layering over the years • SAP Application Design • Database transactions only used for error rollbacks • Locking mostly handled at AppServer level (Enqueues) • Isolation mostly handled at application level
Global Industry Survey: The world in 2010 Interviewing more than 4000 executives and managers • The ability to adapt strategy and business models quickly will be a critical source of competitive advantage • Firms will focus increasingly on speed of innovation and customer retention to create long-term value • Market consolidation will continue, lots of mergers and splits • People are the biggest asset and the biggest cost factor
Flexibility: From monolithic applications to Web Services Information Technology Solutions Process InnovationSolutions UI UI UI Composite Application Functionalcomponents SAP NetWeaver DB DB • 3 tier applications • Coded transactions • Best practices • Service-oriented applications • Model-driven applications • Best practices and platform
Attaching the real world: Eliminating media breaks Manual data entry Voice input Barcodescanning Smart Items RFID • Digital world („Bits“): • Inter- and cross-company information systems (e.g.: ERP systems) • Local, regional and global communication networks (e.g.: Internet) • Physical world („Atoms“): • Human beings • Products • Production means State-of-the-art Next Generation Smart Items Degree of automation Source: M-Lab, 2001 (http://www.m-lab.ch/)
Performance matters: Realtime Application Scenarios • Asset Tracking • Hospital inventory • Machines and parts • Supply Chains • Emergency Response • Vehicle dispatch & tracking • Workplace safety • Security • Behavior mining • Intrusion detection
Putting it all together: Retail example Global Master Data Management (Exchange & Consolidation) Multi-Channel Sales Operations Store Operations Business Data Warehouse e-Commerce,Catalog &Call Center In-StoreCustomer Service CustomerLoyalty Mgmt StoreInventory Mgmt POS CustomerOrder Mgmt PersonalizedPromotions StoreWorkforce/Task Mgmt Demand Intelligence & Analytics Demand Forecast Collaborative Collaborative RevenuePlanning & Optimization Multi Echelon Inventory Planning & Optimization Merchandise & Assortment Planning & Optimization Workforce Planning & Optimization Collaborative Enterprise & Merchandise Operations RetailMaster Data InventoryMgmt EnterpriseOperations OperationalPurchasing Finance HumanResource … Sourcing Distribution Center Operations SupplyPlanning Supply ChainEvent Mgmt WarehouseManagement Product Design & Introduction Multi-ChannelOrderFulfillment Foreign TradeManagement TransportationManagement
Infrastructure challenges • Event Rates • Hundreds of readers in a warehouse • Bursts of hundreds of events per reader per second • Reaction times on the order of seconds in some scenarios • Data Volumes • Billions of objects in a large organization (retail forecast & replenishment) • Some organizations are required to maintain history over 3 or more years • Analytics need to deal • Cost efficiency • Sometimes do this on a shoestring budget • Deal with unpredictable load patterns (the curse of business flexibility) • Keep it all manageable
Net result: Frying your infrastructure • General purpose RDBMS no longer a good fit for these tasks • Good at • Transactions on a few records at a time • Search with well (pre-) designed queries • Not so good at: • Very long running transactions • Mass operations • Ad hoc analytics • Streams
Observations from the Enterprise Services rewrite • You can do without distributed transactions for even very complex business systems • Database-based consistency can be replaced with message-based consistency • Extremely stylized use of DB • model generated • transaction design patterns • A lot of DB functionality factored out (by design): • No cross-component transactions (design rule) • Search (capturing updates allows for separate engine) • Analytics designed for separate engine
SAP Enterprise Services • SAP comitted to Enterprise Services across the board • New design opens up lots of flexibility in the lower stack • Sufficiently coherent data replication in multiple special purpose engines possible • Web services semantics require application level recovery already, negating a lot of RDBMS „comforts“ • Special engines already (partly) there: • Search (TREX) • Analytics (EUCLID) • Planning/Optimization (APO)
Research Idea: Special purpose engines for everything • Mass operations (prediction) • Computation -> Data (integrated processing, LiveCache) • Data -> Computation (mass data services, SAP Research) • Streams • Luckily, not yet a big problem for us (other than prediction) • SAP Research looking for partners • Very fast „simple“ RDBMS for the rest • Fast keyed search, update • Speaking of device evolution: Give me a few Mbyte of MRAM per machine