Bringing Value of Big Data to Business: SAP's Integrated Strategy [1]

Group 6 - Ziqi Fan, Sheng Chen

SAP’s Integrated Big Data Strategy

• SAP is attempting to create an integrated approach that allows companies to perform all the following operations in one environment– Analytics;– Make big data operational;– Support applications for high resolution

management .

Architecture Vision of SAP’s Integrated Big Data

SPA HANA [2]

• SAP HANA, an in memory database is the key to SAP’s integrated strategy. 

• HANA DB takes advantage of the low cost of main memory (RAM), data processing abilities of multi-core processors and the fast data access of solid-state drives relative to traditional hard drives to deliver better performance of analytical and transactional applications.

SPA HANA [2]

• It offers a multi-engine query processing environment which allows it to support both relational data as well as graph and text processing for semi- and unstructured data management within the same system.

• HANA DB is 100% ACID compliant.

Main-Memory DB Query Optimization [3]

• Logical Optimization– Almost same like that in conventional database

• Physical Optimization– goal : minimize execution costs with respect to a

given cost model– Quite different from that in conventional database

due to lack of I/O as dominant cost factor• A “simple” cost model

T = TMem + TCPU

Main-Memory DB Query Optimization

• CPU Cost

TCPU = c0 + c1 · n + c2 · mc0 - fix startup costs

c1 - per tuple costs for processing input tuples

c2 - per tuple costs for producing output tuples

n - # input tuples

m - # output tuples

Main-Memory DB Query Optimization

• Memory Access Cost

Mis - # cache miss of level i for sequential access

Mir - # cache miss of level i for random access

lis - cache latency of level i for sequential access

lir - cache latency of level i for random access

Estimating Mis and Mi

r is very difficult !

Main-Memory DB Query Optimization

• Basic Access Pattern

– single sequential traversal

– repetitive sequential traversal

– single random traversal

– random access

– etc.

• Compound Access Pattern

– Nested loop Join

– Hash-join

– etc.

Reference

• [1] Dan Woods, “Bringing Value of Big Data to Business: SAP's Integrated Strategy”, Forbes, 01/05/2012 http://www.forbes.com/sites/danwoods/2012/01/05/bringing-value-of-big-data-to-business-saps-integrated-strategy/

• [2] http://en.wikipedia.org/wiki/SAP_HANA• [3] Manegold S.: Understanding, Modeling, and Improving Main-

Memory Database Performance, SIKS Dissertation Series No. 2002-17, ISBN 90 6196 5179, pp. 71-104