SAP – DB2 V10.5 mit BLU Acceleration Die neue IBM In-Memory Technologie eröffnet neue Möglichkeiten für Ihr Business SAP auf DB2 Entwicklungs-Team SAP - DB2 Development Entwicklung von SAP Code Entwicklung von DB2 Code für SAP-spezifische Funktionen SAP Development Support Zusammenarbeit mit DB2 Service Gemeinsames IBM and SAP Team SAP - DB2 Integration Center Integration von neuem DB2 Code mit existierenden SAP Releases DB2 QA für jeden neuen DB2 code level mit SAP Anwendungen weit vor IBM GA SAP Development Support Zusammenarbeit mit DB2 Service Gemeinsames iBM und SAP Team SAP auf DB2 ist ein vollständig integriertes Produkt SAP auf DB2 ist ein voll integriertes Produkt Integrierte Installation der DB2 Software mit SAP install * Integrierter Hochverfügbarkeits Setup mit SAP install * One-step SAP-DB2 Konfiguration: DB2_WORKLOAD=SAP Komplette DB2 Administration und Monitoring mit SAP DBA Cockpit One-stop Support Alle Kunden erhalten "One-stop Support" durch SAP – nur ein einziger Kontakt Gemeinsames IBM und SAP Support Team Synchronisierte Wartungszyklen IBM DB2 folgt der SAP 7+2 Wartungsstrategie *as of SAP NetWeaver 7.0 SR3 and SAP Applications based on NW 7.0 SR3 DB2 Optimiert für SAP - Roadmap Eine Auswahl der “SAP on DB2 Technology Highlights” DB2 Optimierungen für SAP COPA und andere SAP Anwendungen SAP COPA Profitabilitäts-Kalkulation • Komplexe SQL Queries mit grosser Zahl aggregierter Zeilen (ähnlich zu BW) Kandidat für Column-store und In-memory Technologie COPA: Nutzung DB2 10.5 Parallel Processing (ohne BLU) • GLEICHE Hardware !!! • DB2 parallel degree: 1 -> 8 bis zu 4x schneller • DB2 parallel degree: 1 -> 16 bis zu 7x schneller SAP COPA Profitability Calculation 12,00 Without parallel processing, run time (h) 10,00 With parallel processing, run time (h) COPA: Resulte mit DB2 9.7 • GLEICHE Hardware !!! • bis zu 3.8x schneller mit DB2 parallel processing • im Schnitt 1.8x schneller mit DB2 parallel processing hours 8,00 6,00 4,00 2.7 Average 1.5 Average 2,00 0,00 1 2 3 4 5 6 7 8 9 SAP Bank Analyzer / SAP Retail • Study on Horizontal Scalability of a Typical SAP Bank Analyzer Scenario on IBM DB2 10.1 pureScale and POWER7 (http://scn.sap.com/docs/DOC-43486) • SAP Enterprise Data Warehouse for Point of Sales Data Optimized for IBM DB2 for Linux, UNIX, and Windows on IBM Power Systems (http://scn.sap.com/docs/DOC-14457) 6 DB2 Nearline-Storage für SAP-BW – niedrigere Kosten, bessere OnlinePerformance Separate SAP BW Online Daten und Near-Line Storage (NLS) Daten Vollkommen transparent für SAP BW Anwendung – keine Änderung der Anwendung notwendig ! Kleine, schnelle Online Datenbank für häufig genutzte Daten Grosse (und langsamere) NearLine Datenbank für „archivierte“ Daten DB2 Alleinstellungsmerkmal TransparentAccess Access Transparent SAP NetWeaver BW BI OLAP BW OLAP BI Data Manager DBInterface Interface DB Layer Layer DBMS Relational DB DB Relational Interface Interface SAP- BW Online Database high performance storage General NLS General Near-Line Interface Interface TREX NLS /Partner DB2 LUW Near-Line Interface Interface Near-Line DB2 Database low cost storage 7 DB2 10.5 Optimiert für SAP Anwendungen Höchste Performance & niedrige Kosten Verfügbarkeit DB2 10.5 ist seit Juni 2013 verfügbar DB2 10.5 für SAP ist seit August 2013 verfügbar DB2 10.5 für SAP mit BLU Acceleration erwartet bis Ende 2013 Lizenz OEM: BLU wird Bestandteil der SAP DB2 ASL Lizenz sobald zertifiziert Direkt: DB2 Advanced Enterprise Server Edition beinhaltet BLU (ohne zusätzliche Kosten) "IBM is working closely with SAP to certify DB2 10.5 in similar time frame as previous major releases. This usually occurs about 8 weeks, give or take, after we GA, so, assume late August for the certification statement from SAP. As with any release, this includes evaluation and exploitation of all features in this release where appropriate (including BLU acceleration). We would be happy to help arrange and participate in a joint meeting/call with you, SAP and IBM to discuss SAP's plans further.“ - Torsten Ziegler, Development Manager SAP DB2 porting Team, SAP BLU Acceleration Eine neue Generation von Daten-Management Innovationen • 8-25x schneller bei Reports und Analysen1 bis zu 1000x schneller bei manchen Queries2 BLU Acceleration • 10x Storageeinsparung3 • Nahtlos integriert in neue DB2 Version 10.5 für einfache “out of the box” Nutzung auf bestehender Infrastruktur 1 Based on internal IBM testing of sample analytic workloads comparing queries accessing row-based tables on DB2 10.1 vs. columnar tables on DB2 10.5. Performance improvement figures are cumulative of all queries in the workload. Individual results will vary depending on individual workloads, configurations and conditions. 2 Based on internal IBM tests of pure analytic workloads comparing queries accessing row-based tables on DB2 10.1 vs. columnar tables on DB2 10.5. Results not typical. Individual results will vary depending on individual workloads, configurations and conditions, including size and content of the table, and number of elements being queried from a given table. 3 Client-reported testing results in DB2 10.5 early release program. Individual results will vary depending on individual workloads, configurations and conditions, including table size and content. Warum ist BLU Acceleration einzigartig ? Unerreichte IBM Forschungs- und Entwicklungs-Innovationen Dynamic In-Memory Actionable Compression Spaltenorientierte In-Memory Verarbeitung mit dynamischer Auslagerung nicht genutzter Daten auf Storage Einzigarte Datenkomprimierung mit Beibehaltung der Sortierreihenfolge ermöglicht Nutzung der Daten ohne Dekomprimierung C1 C2 C3 C4 C5 C6 C7 C8 Encoded Instructions Parallel Vector Processing Multi-core und SIMD Parallelverarbeitung (Single Instruction Multiple Data) Data Data Skipping Results Irrelevante Daten werden bei der Verarbeitung übersprungen Super Fast, Super Easy—Create, Load and Go! Keine Indices, keine Aggregate, Kein Tuning, Keine SQL- oder Schema-Änderungen BLU Acceleration Illustration 10TB Query in Sekunden oder schneller Das System: 32 cores, 1TB memory, 10TB Tabelle mit 100 Spalten und Daten über 10 Jahre Die Query: Wie viele Abschlüsse hatten wir in 2010? SELECT COUNT(*) from MYTABLE where YEAR = ‘2010’ Das Ergebnis: In Sekunden oder weniger weil jede CPU nur 8 MB Daten untersuchen muss DATA DATA DATA DATA DATA DATA DATA DATA DATA 10TB data DATA DATA DATA Actionable Compression reduziert Daten auf 1TB In-memory Column Processing reduziert zu 10GB Data Skipping Reduziert zu 1GB Parallel Processing 32MB linearer Scan auf jedem Core via DATA Vector Processing Scan so schnell wie bei 8MB durch SIMD DATA Ergebnis in Sekunden oder weniger DATA 11 DB2 BLU - Seamless Integration into DB2 Built seamlessly into DB2 – integration and coexistence Column-organized tables can coexist with existing, traditional tables Same schema, same storage, same memory Same SQL, language interfaces, and administration Column-organized tables or combinations of column-organized and row-organized tables can be accessed within the same SQL statement Dramatic simplification – Just “Load and Go” Faster deployment Fewer database objects required to achieve same outcome Requires less ongoing management Due to its optimized query processing and fewer database objects required Simple migration Conversion from traditional row table to BLU Acceleration is easy Users only notice speed-ups; DBAs only notice less work! DB2 BLU Integration into SAP BW Integration into SAP BW Workbench SAP ABAP Dictionary extension to support BLU tables as new table type BLU conversion of existing BW objects DBA Cockpit: Support of new performance metrics for BLU tables Configuration for BLU feature is fully compatible with SAP settings - DB2_WORKLOAD=SAP 13 DB2 BLU Conversion of existing BW Objects • Report SAP_CDE_CONVERSION_DB6 – – Non-BLU -> BLU in online mode BLU -> BLU / Non-BLU in read-only mode • Select an InfoCube or all InfoCubes • "Get Dependent Tables" determines the tables belonging to the BW Object 14 Planned SAP BW Adoption for DB2 10.5 BLU Feature • • • SAP NetWeaver BW 7.00 and higher Support expected to start with DB2 10.5 FP1 (End of 2013) DB2 10.5 BLU extensions are delivered with SAP BW support packages 15 How fast is it? Results from the DB2 10.5 2nd Alpha Customer Tests Workload Speedup over DB2 10.1 Common Large Financial Services Company 46.8x 8x-25x Global ISV Mart Workload 37.4x Analytics Reporting Vendor 13.0x improvement Global Retailer 6.1x Large European Bank 5.6x Internal Benchmark Test 3.0x DB2 = ONE 4 ALL Average diaglog response time 0,2 - 0,8 sec DB2 LUW Average diaglog response time 0,4 – 2 sec DB2 LUW DB2 LUW SAP Business-Suite, Industry Solutions SAP BW Big Data NLS for BW OLTP workload OLAP workload Near-line Storage Transactional Analytical Near-line Storage 17 DB2 - Tailored Performance for SAP Customers compared with non-virtualised and non-consolidated solution Customer runs DB2 on POWER/AIX - 180 systems, 48 production - 26 HA (LPM*) + 26 DR (PowerHA) - 2 data centers 4 POWER servers Implementation w/o virt. & consol. - 180 systems, 48 production - 26 HA + 26 DR clusters - 2 BIGGER or more data centers - 48 servers for production - 52 servers for HA+DR clusters - up to 48 servers for test/QA - up to 48 servers for dev - up to 36 servers for rest 101-232 servers * LPM - AIX live partition mobility 18 Compression and Storage Savings • Often compression and storage savings are wrong determined database size consists of ALL data stored on storage (e.g not only tables) • Comparing in-memory databases and on-disk databases should be done on the right level On-disk database RAM In-memory DB RAM On-disk database storage In-memory database storage 19 Cost Comparison for DB2 on Power vs. SAP HANA on Intel EXAMPLE: 10TB raw active user data • • DB2 10.5 BLU recommendation for 10TB of data is 500GB - 1TB of memory SAP recommendation for 10TB of data is 4TB - 5TB of memory • • DB2 10.5 BLU storage requirements for 10TB of SAP data is 1.4TB storage SAP storage requirements are = 4 * memory required = 16TB – 20TB • • DB2 10.5 BLU CPU requirements for 10TB is 32 cores of Power7+ SAP HANA CPU requirements for same database is 320 cores of Intel • Costs • DB2 10.5 on 32core 770+ server (1TB DRAM & 2TB SSD storage) • Software costs = DB2 AESE = $94K/TB = $188,000 (2TB of compressed data) • Hardware costs = $878,884 • Total = $1,066,884 (including 1st year support) • SAP HANA on 9 40-core IBM x3590 servers (512GB DRAM & 2.5TB storage each) • Software costs = SAP HANA Enterprise Edition for 2TB compressed data = $6,106,000 • Hardware costs = $$1,450,000 • Total = $7,556,000 + $1,343,320 (1st year S&S) = $8,899,320 SAP HANA is 834% more expensive than DB2 10.5 BLU on Power © 2013 IBM Corporation Was unterscheidet DB2-BLU von SAP-HANA ? DB2- BLU SAP- HANA • Wettbewerbsvorteile durch neue und schnellere Prozesse • Wettbewerbsvorteile durch neue und schnellere Prozesse • Standard- Hardware • spezielle Appliance- Hardware • Investitionssicherheit durch SAP-IBM- Kooperation • Investitionssicherheit durch „SAP- Komplettlösung“ • volle Flexibiltät bei der Plattform – Auswahl (inkl. IBM-Power-Plattform) • reduzierte Plattform- Flexibiltät (nur freigegebene x86-Systeme) • Standard DB2-Betriebsaufwendungen • spezielle Betriebsaufwendungen • Lizenzkosten in DB2 AESE inkl. • extra SAP- Lizenzzahlungen • Storage- / Server- Kosten sinken • Storage- / Server- Kosten steigen First Customer Quotes on DB2 10.5 Significantly Less Storage, Better Performance “10x. That's how much smaller our tables are with BLU Acceleration. Moreover, I don't have to create indexes or aggregates, or partition the data, among other things. When I take that into account in our mixed table-type environment, that number becomes 10-25x.” -Andrew Juarez, Lead SAP Basis and DBA “When I converted one of our schemas into DB2 10.5 with BLU Acceleration tables, the analytical query set ran 4-15x faster.” -Andrew Juarez, Lead SAP Basis and DBA “What was really impressive is the fact that we could get significantly better performance with DB210.5 using BLU Acceleration without having to create indexes or aggregates on any of the tables. That is going to save us a lot of time when designing and tuning our workloads.” - Kent Collins, Database Solutions Architect, BNSF Railway “When we compared the performance of column-organized tables in DB2 to our traditional roworganized tables, we found that, on average, our analytic queries were running 74x faster when using BLU Acceleration.” - Kent Collins, Database Solutions Architect, BNSF Railway DB2 with BLU Acceleration Super analytics Super easy THANK YOU