IBM's Recommended Approach for Optimizing Different Kinds of SAP Workloads

Agenda

Different workloads

Options for implementations

Moving workload between the layers

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Workloads and Similarities

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Workloads in the IT World

Addressing challenges with unique capabilities on H W and SW level

Transaction Processing

Operational Analytics

Mobile Data Serving

Reporting and Analytics

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Why IBM ?

• IBM is industry-leading and uniquely positioned to design/execute/implement a Big Data strategy:

– storage (DS8K, V7000, Flash, …)– server (POWER, System z, … )– appliance (Pure Flex, Pure Application, …)– software (DB2, Cognos, Tivoli, Websphere, …)

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Next Generation Database = ONE 4 ALL

Transactional Analytical Near-line Storage

SAP Business-Suite,Industry Solutions

OLTP workload

SAP BW Big Data

OLAP workload

NLS for BW

Near-line Storage

DB2 LUW DB2 LUW DB2 LUW

Agenda

Different workloads

Options for implementations

Moving workload between the layers

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Source database: 8 TB on BW 7.0 (non-Unicode)

2-tier implementation: database and application server are sharing the resources

Low hardware required for large SAP BW systems

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IBM HW x440- 40 cores & 768 GB RAM- without storage (available from customer)

Estimated HW Infrastructure for Production

Assumption yearly 20% growth

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New technology for accelerating queries• CPU-optimized unique runtime handling

• Unique encoding for speed and compression

• Unique memory management

• Vector processing (e.g. SIMD)

• Built directly into the DB2 kernel

DB2 capacity in Peta Bytes and more• One partition: 2,048 PB (uncompressed approx. 20,000 PB)

• One partition: 128 x 1010 rows per table

DB2 10.5: Acceleration for SAP Applications and Big Data Era

SAP BW scenario• Fact table with 438 Million records (~200GB)

• Size (table + indexes)

- DB2 10.1 compressed: 33 GB

- DB2 10.5 compressed: 12 GB

• DB2 parallel query degree switched ON

DB2 10.5 Test environment• 2 Intel® Xeon® processors (8 cores in total), 2.14GHz

• 32 GB RAM, SLES Linux V11

• SAP BW 7.30

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Test 1: 15 GB Bufferpool

Test 2: 7.5 GB Bufferpool

1744.17

7.09

2790.3

7.35

0

1000

2000

3000

Test 1 Test 2

DB2 V10

DB2 BLU

246

380

DB2 10.5: Performance Improvement for SAP BW

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Agenda

Different workloads

Options for implementations

Moving workload between the layers

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Workload distribution and Impacts of Program Code

• Run time consists of- front-end and back-end time- database time- application time

• Application programming and QUALITY is very important for the overall run time

• Example: Carl Friedrich Gauss (1777–1855) Sum of numbers up to 1001 + 2 + 3 + 4 + ...... + 100 = ?

100%

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Application Layer (~80% of cores and RAM)

Database Layer (~20% of cores and RAM)

• keep workload, where it fits best

• tailored building blocks for highest flexibility

• tailored performance on OS / DB / storage level

Application data is in RAM

2-tierarchitecture protects the performance between Database + application

... DB2 supports 2-tierDatabase data >98% in RAM

Workload shift from application to database layer ?

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SAP Client Copy Runtimes (2-tier vs. 3-tier)

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• 2-tier < 3-tier comparison with different configuration patterns

• Para 3-tier is almost the best compromise for performance vs. operation and license cost optimization aspects

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SAP SD Benchmark Comparison

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IBM‘s Recommended Approach

1. Use the best matching server/storage configuratio n• Appliance solutions, if the workload is the same an d not volatile

• Tailored solutions, if the workload is different an d volatile

Hint: Avoid to find the matching problem for an available solution. The solution is there to solve the problems

2. Use the matching tier-architecture• 2-tier architecture for performance sensitive envir onment

• 3-tier architecture for de-central implementation a nd separation of the layers

Hint: Avoid to include a de-central implementation approach into a 2-tier layer by force. If helpful than install a 2.5-tier layer

3. Use the matching SW technology • OLTP implementation for large number of users with short running transactions (e.g. SAP Business Suite )

• OLAP implementation for large amount of data spread over fewer users (e.g. SAP BW)

Hint: Avoid to melt OLTP and OLAP workload, because of the limitation of appliance solutions

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• Join me in the Expert Networking Lounge at Date/Time •(if appropriate, depending on your presentation time)

• Stop by the IBM booth . -IBM experts will be on hand to share IBM's extensive portfolio of breakthrough technologies, innovative solutions and comprehensive services for SAP clients.

- Ask us about cloud computing, enterprise mobility, IBM solutions for SAP applications, and social tools for business and commercial engagement.

- See demos and user cases from the IBM’s Client Center: Lab for SAP Solutions.

• Find customer case studies and more on the IBM-SAP Alliance website : www.ibm-sap.com

Further information

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