Upload
manoj-kumar
View
152
Download
7
Embed Size (px)
DESCRIPTION
hana on bw
Citation preview
March 2012
BW on HANA
© 2012 SAP AG. All rights reserved. 2
Legal Disclaimer
The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the
permission of SAP. This presentation is not subject to your license agreement or any other service or subscription
agreement with SAP. SAP has no obligation to pursue any course of business outlined in this document or any
related presentation, or to develop or release any functionality mentioned therein. This document, or any related
presentation and SAP's strategy and possible future developments, products and or platforms directions and
functionality are all subject to change and may be changed by SAP at any time for any reason without notice. The
information on this document is not a commitment, promise or legal obligation to deliver any material, code or
functionality. 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. This
document is for informational purposes and may not be incorporated into a contract. SAP assumes no
responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally
or grossly negligent.
All forward-looking statements are subject to various risks and uncertainties that could cause actual results to
differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking
statements, which speak only as of their dates, and they should not be relied upon in making purchasing
decisions.
© 2012 SAP AG. All rights reserved. 3
Session goals
1. What is BW-on-HANA?
2. Integration between
BW and HANA
3. How BW will be further
optimized for HANA.
© 2012 SAP AG. All rights reserved. 4
Agenda
BW-on-HANA Overview
Write Performance incl. demo
BW-on-HANA combined with HANA Data Mart incl. demo
Outlook: HANA optimized BW
Summary
BW-on-HANA Overview
© 2012 SAP AG. All rights reserved. 6
A Typical Data Warehouse Architecture
data information
© 2012 SAP AG. All rights reserved. 7
EDW = DB + X*
* X is an EDW application running on top of the DB
SQL
Storage / persistence
ACID
partitioning
indexing
clustering
Processing engines
calculations
aggregation
planning
data mining / predictive
search
Back-up, recovery, fail-over
Modeling & application building
analytic models
DW containers
data flows
transformations
security
conventions / standards (e.g. naming)
Lifecycle of models + data
incl. impact analysis + propagation
online, nearline, offline data
Scheduling + monitoring
Data integrity + compliance
Extraction + connectivity
© 2012 SAP AG. All rights reserved. 8
BW-on-HANA
SAP
Extractors
Data
Services
HANA
BW managed table schema
SAP Business Objects Tools & Clients
BW Application
© 2012 SAP AG. All rights reserved. 9
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 HANA DB ("NewDB") lower TCO
(2) InfoCube HANA Opt. Infocube faster loads
(3) DSO HANA Opt. DSO faster loads + queries
(4) Planning HANA Planning Engine faster planning
(5) Consumption of "pure-play HANA artifacts" agility
Those benefits have been confirmed in PoCs and ramp-up projects.
Write Performance
© 2012 SAP AG. All rights reserved. 11
BW-on-HANA Write Performance
HANADB optimized DataStore-Object:
• Write Performance: Data Activation pushed down to
database and improved up to factor 15
• Excellent Query performance on all DataStores
HANADB optimized Planning:
• Calculations inclusive Write back are performed
directly on the database and improved up to factor 10
Reporting
DataSources
Reporting
DataSources
Data Harmonization
Business Rules
HANADB optimized InfoCube:
• Write Performance: Load improved up to factor 5
• Excellent query performance on all InfoCubes
• More flexible modeling
New reporting option on the DataStore-Object
© 2012 SAP AG. All rights reserved. 12
HANA optimized InfoCubes Faster data loads and easier modeling
Facts
MD MD
MD MD
F
Facts
D
D
MD MD
MD MD
F E
Conversion/New
Traditional InfoCubes tailored to a relational DB consist
of 2 Fact Tables and the according dimension tables
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 required
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 required
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 caused by SAP intentionally or grossly negligent.
© 2012 SAP AG. All rights reserved. 13
SAP HANA-optimized DataStore object Overview Classical Architecture
Activation
Queue
Active Data
Change
Log
Activation
Process
(ABAP)
Application Server RDBMS
Relational Table
Relational Table
Relational Table
Classical Architecture
Challenges
••Data Activation
Reporting-Performance
Secondary Indexes
SID Handling
© 2012 SAP AG. All rights reserved. 14
SAP HANA optimized DataStore object Overview SAP HANA architecture
Activation
Queue
Active Data
Change
Log
Activation
Process
(C++)
Application Server SAP HANA DB
Columnar Table
Columnar table
designed as Temporal
Table
Calculation View
SAP HANA-opt. DataStores
Activation
Trigger
(ABAP)
Challenges
••Data Activation
Reporting-Performance
Secondary Indexes
SID Handling
© 2012 SAP AG. All rights reserved. 15
DataStore Objects in SAP NetWeaver BW 7.30 Table Structures for HANA Optimized DataStore Objects
Maps activation request SID
to commit ID used in history
index (NewDB internal
usage)
DataStore
SID Module uses
Status of SID creation
Source dependent check
Activation Queue
/[Namespace]/A[DataStore]40
Standard column based table
Type „Insert Only“ (no primary key)
Uniqueness checked by SQL statement
(DBMS exit)
Active Data Table
/[Namespace]/A[DataStore]00
Temporal table (History table)
Additional field „IMO__INT_KEY“
Automerge ‘off’ as application triggers
smartmerge
„Old“ external key
Change Log
/BI0/B*
Table is replaced by calculation view
(Extraction process uses history index
to create a ‚change log view‘ of the data)
© 2012 SAP AG. All rights reserved. 16
HANA Optimized DataStore Objects Mapping Between Application Server and HANA DB
History Index
(column based) Main Index
(column based) Delta Index
Column based table Calculation View
Standard column based table
Type „Insert Only“ (no primary key)
Uniqueness checked by SQL
statement (DBMS exit)
Temporal table
Additional field „IMO__INT_KEY“
Auto merge off
„Old“ external key
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
© 2012 SAP AG. All rights reserved. 17
SAP HANA-optimized DataStore object SAP HANA-optimized SID Handling (Anti-Join)
Classical Architecture
0COMPCODE 0DEBITOR 0SALESORG 0AMOUNT
1 0001 0000001 1000 10
2 0001 0000021 1000 20
3 0001 0000054 1000 100
4 0001 0000001 1000 20
Activation Queue
0COMPCODE 0DEBITOR 0SALESORG 0AMOUNT
1 0001 0000001 1000 10
2 0001 0000021 1000 20
3 0001 0000054 1000 100
4 0001 0000001 1000 20
0COMPCODE SID
0001 00001
0DEBITOR SID
0001 00005
0021 00006
0SALESORG SID
1000 00008
SAP HANA-optimized
SELECT * FROM Activation Queue
SELECT DISTINCT InfoObject
FROM Activation Queue
WHERE InfoObject NOT IN
SELECT *
FROM SID-Table
0DEBITOR
0000054
© 2012 SAP AG. All rights reserved. 18
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 DSO„s first
BW-on-HANA combined w/ HANA Data Mart
© 2012 SAP AG. All rights reserved. 20
BW-on-HANA combined w/ HANA Data Mart
This 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 and
consumed the same way with native EXCEL via BW-MDX
© 2012 SAP AG. All rights reserved. 21
Chapter 1 - HANA Data Mart raw data
view
any table schema
SLT
Data
Services
HANA
MDX via HANA-ODBO
© 2012 SAP AG. All rights reserved. 22
Chapter 2 - HANA Data Mart analytic model
view
any table schema
SLT
Data
Services
HANA
MDX via HANA-ODBO
© 2012 SAP AG. All rights reserved. 23
Chapter 3 - HANA Data Mart native EXCEL consumption
view
any table schema
SLT
Data
Services
HANA
MDX via HANA-ODBO
© 2012 SAP AG. All rights reserved. 24
Chapter 4 - BW-on-HANA combined w/ HANA Data Mart
view
any table schema
BW Application
MDX via BW-ODBO
SLT
Data
Services
SAP
Extractors
Data
Services
HANA
BW managed table schema
MDX via HANA-ODBO
join w/ BW data + logic
reuse BW security
enrich w/ BW hierarchies
enrich w/ BW currency logic
© 2012 SAP AG. All rights reserved. 25
BW-on-HANA combined w/ HANA Data Mart
view
any table schema
HANA
BW managed table schema
SAP Business Objects Tools & Clients
Analysis – Web Intelligence – Crystal Reports – Explorer – Xcelsius – Excel
Interfaces (MDX, SQL, …) Interfaces (MDX, SQL, …)
ODP
DB Connect
BW Application
Analytic Index
Virtual Provider
ODP
SLT
Data
Services
SAP
Extractors
Data
Services
Outlook: HANA optimized BW
© 2012 SAP AG. All rights reserved. 27
BW 7.30 on HANA
HANA 1.00
data write
ACID compliance
reporting + activation for
DSOs in-memory
1st EDW processing in-memory
bulk write
additional calculations in-memory
BWA 7.20
BW 7.30
BWA-only InfoCubes
BWA reporting for DSOs
MultiProvider handling and flexible
joins
calculations
logic
1st calculation scenarios in BWA
Session concept
HANA-optimized planning
transactions
The Adoption of in-memory Technology in BW
BWA 7.00
data read
aggregation
BW 7.00 BWA instead of aggregates
bulk read
Analytics
Single data operations extensibility
OLTP
© 2012 SAP AG. All rights reserved. 28
SAP BW Roadmap
BW 7.30
BW Accelerator (BWA)
Data Store Objects (DSOs)
wider set of analytic operators
flexible data models for ad-hoc
purposes
Data Warehouse Layer
managing huge data containers
excellent query performance on real-
time feeds
Business Objects Integration
reporting tools interoperability
Data Services from within BW
System Management
template-based configuration
admin cockpit
BW 7.30 on HANA
1. Classic DB + BWA HANA DB
lower TCO
2. InfoCube HANA optimized infocube
faster loads
3. DSO HANA optimized DSO
faster loads + queries
4. Planning HANA planning engine
faster planning
5. Consumption of "pure-play
HANA artifacts" agility
HANA optimized BW
guiding principles:
1. non-disruptive*
2. agile + flexible, via
more logical abstractions
unified analytic modeler
3. HANA optimized
4. stellar experience
* to an existing BW
2012 Future Direction 2011
© 2012 SAP AG. All rights reserved. 29
HANA Optimized BW
Renovated optimized for SAP HANA platform
Eclipse based editors and tools
overcome current limitations
Better Separation: Physics – Logic one physical container
multiple logical profiles
BW / Non-BW Mixed EDW Environment smooth transition between "quick & dirty" LSA++
uniform modeling concepts and environment
analytics on top of federated objects from managed
and non-managed area
Migration Tools
Summary
© 2012 SAP AG. All rights reserved. 31
Key takeaways
1. What BW-on-HANA is.
2. BW-on-HANA and HANA data
marts complement each other.
3. BW will be further optimized
for HANA.
© 2012 SAP AG. All rights reserved. 32
Further information
Experience SAP HANA: https://www.experiencesaphana.com
SAP HANA Knowledge Center: http://service.sap.com/hana – sizing
– master guide
– hardware platforms
SAP Help on HANA: http://help.sap.com/hana
BW-on-HANA – E2E implementation guide for SAP NetWeaver BW 7.3, powered by SAP HANA
– Red Bull's Migration of a BW to a BW-on-HANA System
– SDN blog 1: http://www.sdn.sap.com/irj/scn/weblogs?blog=/pub/wlg/25122
– SDN blog 2: http://www.sdn.sap.com/irj/scn/weblogs?blog=/pub/wlg/25123
Contact information:
Roland Kramer
PM BW/In-Memory
Thank you