BW on HANAMarch 2012
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Session goals 1. What is BW-on-HANA?2. Integration between BW and HANA 3. How BW will be further optimized for HANA.
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AgendaBW-on-HANA Overview Write Performance incl. demo BW-on-HANA combined with HANA Data Martincl. demo
Outlook: HANA optimized BW Summary
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BW-on-HANA Overview
A Typical Data Warehouse Architecture
data
information
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EDWSQL
=
DB
+
X*Modeling & application buildinganalytic models DW containers data flows transformations security conventions / standards (e.g. naming)
Storage / persistence ACID partitioning indexing clustering calculations aggregation planning data mining / predictive search
Processing engines
Lifecycle of models + data incl. impact analysis + propagation online, nearline, offline data
Scheduling + monitoringData integrity + compliance Extraction + connectivity* X is an EDW application running on top of the DB
Back-up, recovery, fail-over
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BW-on-HANA
SAP Business Objects Tools & Clients
BW Application
BW managed table schema SAP Extractors Data Services
HANA 2012 SAP AG. All rights reserved. 8
BW-on-HANA BW-on-HANA = BW 7.3 on HANA 1.0
How does BW-on-HANA differ from a standard BW 7.3?(1) Classic DB + BWA(2) InfoCube (3) DSO
HANA DB ("NewDB") HANA Opt. Infocube HANA Opt. DSO
lower TCO faster loads faster loads + queries
(4) Planning
HANA Planning Engine
faster planning agility
(5) Consumption of "pure-play HANA artifacts"
Those benefits have been confirmed in PoCs and ramp-up projects.
2012 SAP AG. All rights reserved.
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Write Performance
BW-on-HANA Write PerformanceReporting HANADB optimized InfoCube: Write Performance: Load improved up to factor 5 Excellent query performance on all InfoCubes More flexible modeling Reporting
HANADB optimized DataStore-Object:Business Rules
Write Performance: Data Activation pushed down to database and improved up to factor 15 Excellent Query performance on all DataStoresDataSources
New reporting option on the DataStore-ObjectData Harmonization
HANADB optimized Planning:DataSources
Calculations inclusive Write back are performed directly on the database and improved up to factor 10
2012 SAP AG. All rights reserved.
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HANA optimized InfoCubesFaster data loads and easier modelingTraditional InfoCubes tailored to a relational DB consist of 2 Fact Tables and the according dimension tablesMD D Facts F MD E
HANA optimized InfoCubes tailored to HANA represent flat structures without dimension and E tables: Up to 5 times faster data loads Creation of DIM Ids no longer requiredMD
D MD Conversion/New MD MD F Facts
Simplified data modeling Faster remodeling of structural changes After the migration to BW7.3, SP5 all InfoCubes remain unchanged Tool support for converting standard InfoCubes Preliminary lab result: 250 Million records in 4 minutes
No changes of processes, MultiProvider, Queries requiredMD MD
This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in this document, except if such damages were c aused by SAP intentionally or grossly negligent.
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SAP HANA-optimized DataStore objectOverview Classical Architecture Challenges Data ActivationRelational Table Relational Table Reporting-Performance Secondary Indexes
Activation QueueActive Data Change Log Activation Process (ABAP)
Relational Table
SID Handling
Application Server
RDBMS
Classical Architecture 2012 SAP AG. All rights reserved. 13
SAP HANA optimized DataStore objectOverview SAP HANA architecture Challenges Data ActivationReporting-Performance Secondary Indexes
Activation Queue
Columnar Table Columnar table designed as Temporal Table
Active DataChange Log Activation Trigger (ABAP)
Calculation View
SID Handling
Activation Process (C++)
Application Server
SAP HANA DB
SAP HANA-opt. DataStores 2012 SAP AG. All rights reserved. 14
DataStore Objects in SAP NetWeaver BW 7.30Table Structures for HANA Optimized DataStore ObjectsSource dependent check
Change Log /BI0/B*Table is replaced by calculation view (Extraction process uses history index to create a change log view of the data)
SID Module
uses
Active Data Table/[Namespace]/A[DataStore]00
DataStore
Temporal table (History table)Additional field IMO__INT_KEY Automerge off as application triggers smartmerge Old external key
Activation Queue
/[Namespace]/A[DataStore]40
Status of SID creation Maps activation request SID to commit ID used in history index (NewDB internal usage) 2012 SAP AG. All rights reserved.
Standard column based table
Type Insert Only (no primary key)Uniqueness checked by SQL statement (DBMS exit)
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HANA Optimized DataStore ObjectsMapping Between Application Server and HANA DB
Column based table
History Index (column based) Main Index (column based) Delta Index
Calculation View
Standard column based table
Temporal table
Type Insert Only (no primary key)Uniqueness checked by SQL statement (DBMS exit)
Additional field IMO__INT_KEYAuto merge off
Table replaced by calc view (uses history index to create a change log view of the data) View calculates technical key on the fly Multiple updates for a particular key are consolidated into one
Old external key
2012 SAP AG. All rights reserved.
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SAP HANA-optimized DataStore objectSAP HANA-optimized SID Handling (Anti-Join)0COMPCODE1 2
0DEBITOR 0000001 0000021
0SALESORG 1000 1000
0AMOUNT 10 20
0DEBITOR 0000054
0001 0001
34
00010001
00000540000001
10001000
10020
SELECT DISTINCT InfoObject FROM Activation Queue WHERE InfoObject NOT IN SELECT * FROM SID-Table
SELECT * FROM Activation Queue 0COMPCODE12
0SALESORG1000
SID00008
0DEBITOR
0SALESORG
0AMOUNT
00010001 0001 0001
00000010000021 0000054 0000001
10001000 1000 1000
1020 100 20
0DEBITOR 0001
SID 00005
0COMPCODE0001
SID00001
3 4
0021
00006
Activation Queue
Classical Architecture 2012 SAP AG. All rights reserved.
SAP HANA-optimized17
BW system copy post In-Memory conversion steps transaction RSMIGRHANADB
For the full DSO conversion HANA 1.0 Rev. 26 is necessary Note 1687660 HANADB: Full DataStore conversion only as of revision 26 Run ONLY for selected InfoCubes and DSOs first
2012 SAP AG. All rights reserved.
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BW-on-HANA combined w/ HANA Data Mart
BW-on-HANA combined w/ HANA Data MartThis demo focuses on how an analytical model is created on raw data in SAP HANA this data is consumed with native EXCEL via HANA-MDX
this data is combined with the value-add BW model an
