This blog provides an insight in to the how SAP Netweaver BW 7.3 is going to benefit from the SAP’s In Memory technology SAP HANA. I have tried to collate all the information available into this one blog to help members get an overview about SAP NW BW7.3 on SAP HANA.
I have explained briefly what are the New additions in SAP Netweaver BW 7.3 and What is SAP HANA. Then we take a look at how BW 7.3 is going to get benefited when using SAP HANA. The blog also highlights briefly various structural changes that the BW objects will be undergoing when SAP HANA is used as an underlying database
SAP Netweaver BW 7.3 Features
SAP BW 7.3 is the latest version of SAP BW. With the enhanced modeling capabilities of SAP BW 7.3 development efforts and maintenance overheads can be reduced considerably. It comes with lot of features like:
- Allows creating graphical design of the data flows thereby giving a visual interpretation of how the flow would look like, when fully developed.
- Wizard based data flow modeling and generation of all related data flow objects.
- With BW 7.3 existing data flow can be copied using the Data Flow Copy tool to create similar data models.
- BW 7.3 provides a workbench like UI to migrate data flows.
- BW 7.3 introduces the concept of Hybridprovider which combines the real time transaction data with historical data.
- BW 7.3 also introduces a new type of modeling object called SPO(Semantic Partition Object)
SAP HANA Overview
SAP HANA is a flexible, multi-purpose, data-source-agonistic in-memory appliance that combines SAP software components optimized on hardware It includes a number of integrated SAP software components including the SAP in-memory computing engine, real-time replication service, data modeling and data services. SAP HANA allows: accelerated BI scenarios off any data source; better operational planning, simulation and forecasting; fast analysis and better decision making off accelerated SAP ERP transactional data, better storage, search and ad-hoc analysis of very large data volumes.
- SAP HANA has the capability to analyze information in real-time at unprecedented speeds on large volumes of non-aggregated data.
- SAP HANA can create flexible analytic models based on real-time and historic business data.
- SAP HANA minimizes data duplication.
SAP BW 7.3 on SAP HANA
Till now SAP HANA was running side by side SAP NetWeaver BW. But in November 2011 SAP has launched SAP NetWeaver BW 7.3x running on HANA as the underlying In-Memory DB Platform. With version 7.30 SP5 it is possible to run run SAP BW on SAP HANA as database platform. This enables us to leverage the In-Memory capabilities of HANA and create SAP-HANA-optimized BW objects.
SAP BW 7.3 on SAP HANA:
- Provides an integrated engine for all the data management and in memory processing of analytical capabilities
- Allows the Database and BWA to merge in once instance. BW on HANA delivers BWA functionality for BW objects locally. There is no need for a separate BWA.
- Simple administration of the database and singe set of administration tools.
- Improved load performance for the DSO’s.
- Excellent query performance
- Accelerated In-Memory planning functions.
- HANA supports column based storage, hence the compression rate will be higher and less data has to be materialized.
Difference between BW 7.3 running on HANA as against running on any DB
SAP Netweaver BW 7.3 on any Database | SAP Netweaver BW 7.3 on HANA |
Supports Standard Datastore Objects | Supports In-Memory based Datastore objects |
Includes both Database server and SAP Netweaver BWA | Includes just the SAP HANA In-Memory Platform |
Support Standard InfoCubes | Support In-Memory based InfoCubes |
Support BW Integrated Planning | Supports In-Memory Planning Engine |
HANA data marts running side-by-side BW | Objects created in HANA studio and BW Staging from HANA. |
SAP BW 7.3 powered by SAP HANA
To migrate to SAP HANA as database pure DB conversion is possible. No separate implementation required.
Once the DB conversion activity has been completed, conversion of InfoCubes and DSOs into new Hana-optimized object types needs to be performed so as to make optimal use of new In-Memory technology. Objects can be converted on an object-by-object basis.
Below diagram depicts how the system architecture will look like after the migration
After the DB conversion, BW objects like DSO, InfoCubes can also be converted to leverage the In-Memory capabilities. These BW objects are then referred as In-Memory optimized DSO and In-Memory optimized InfoCubes respectively.
In-Memory optimized DSO
DataStore Objects forms an integral part of a data model in SAP BW. It is usually utilize to store information or data at a detail level. A DSO is also useful if we want to extract Delta information from datasources. At times with huge amount of data the activation process and the reporting on a DSO takes a lot of time, thereby affecting the overall performance.
In the current architecture the activation process calculates changes for each record thereby creating load on the database. The Delta calculations are performed on the Application server itself. A lot of lookup/roundtrips happen between the application server and database to calculate the delta information
With an In-Memory optimized DSO’s:
- Delta calculation has been completely integrated in HANA.
- Uses In-Memory data structures which helps in faster access.
- As the calculations are done in HANA itself, there are no round trips to application server.
- Helps avoiding storage of redundant data.
- The existing dataflow of the DSO remain unchanged. The DSO definition also remains unchanged after migration.
- To activate In-Memory capabilities in a Standard DSO a new setting ”In Memory Optimized” is available, when checked and activated the standard DSO is converted to In-Memory Optimized DSO.
- In-built tool provided to convert the existing Standard DSO’s to In-Memory optimized DSO’s
In-Memory optimized Infocube
InfoCubes also forms an integral part of a data model in SAP BW. They describe a self contained dataset. In the current architecture an Infocube is a set of relational tables arranged according to star schema. This star schema has a big fact table surrounded by Dimension tables. The Dimension tables are then linked to Master Data tables through SID’s
With an In-Memory optimized InfoCubes:
- In Memory optimized info cubes are structured to represent flat structures without Dimension tables and the E table.
- The Data Modeling process gets simplified as the dimensions are not physically present.
- Faster data loads to cube as there are no Dimension Id’s.
- To activate In-Memory capabilities in a Standard Infocube option is available in Infocube property, when Selected and activated the standard Infocube is converted to In-Memory Optimized Infocube.
- In-built tool provided to convert the existing Standard Infocube’s to In-Memory optimized Infocube
In-Memory Planning:
For a SAP BW server on any database the Traditional Planning runs planning function on Application server. With In-Memory the planning functions are executed on SAP HANA
- This provides a performance boost for planning capabilities like aggregation, disaggregation, conversion, revaluation.
- Performance boost for plan/actual analysis.
- No changes required to the planning models
Query Performance on In-Memory :
With SAP HANA as the underlying database the query performance also improves significantly.
Query performance on InfoCube
- Indexes on InfoCube and master are no longer required.
- In-Memory based calculation engine.
Query performance on DataStore Objects
- Acceleration via In-Memory Column storage.
- Additional acceleration via Analytical views on top of DSO
Conclusion:
With SAP HANA as underlying database, SAP BW 7.3 system can achieve:
- Excellent query performance.
- Accelerated In-Memory planning capabilities.
- Performance boost for ETL processes.
- DB and BWA merging in one instance.
- Simplified administration via one set of admin tools.
- Column based storage with highly compression rates and significantly less data to be materialized.
- Simplified data modeling and reduced materialized layers.
- Integrated and embedded flexibility for Data Marts
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