2012 BW on HANA Modelling

March 2012

BW on HANA

© 2012 SAP AG. All rights reserved. 2

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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.


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


A Typical Data Warehouse Architecture

data information


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


BW-on-HANA

SAP

Extractors

Data

Services

HANA

BW managed table schema

SAP Business Objects Tools & Clients

BW Application


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


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


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.


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


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


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)


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


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


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



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


Chapter 1 - HANA Data Mart raw data

view

any table schema

SLT

Data

Services

HANA

MDX via HANA-ODBO


Chapter 2 - HANA Data Mart analytic model

view

any table schema

SLT

Data

Services

HANA

MDX via HANA-ODBO


Chapter 3 - HANA Data Mart native EXCEL consumption

view

any table schema

SLT

Data

Services

HANA

MDX via HANA-ODBO


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


MDX via HANA-ODBO

join w/ BW data + logic

reuse BW security

enrich w/ BW hierarchies

enrich w/ BW currency logic



view

any table schema

HANA


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


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


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


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


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.


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

https://www.experiencesaphana.com/

https://www.experiencesaphana.com/

http://service.sap.com/hana

http://bit.ly/HANA_PAM



http://help.sap.com/hana

http://help.sap.com/hana

http://service.sap.com/~sapidb/011000358700001167432011E/E2E_Roadmap_BW_on_SAP_HANA.pdf





http://www.sdn.sap.com/irj/scn/weblogs?blog=/pub/wlg/27493








Contact information:

Roland Kramer

PM BW/In-Memory

[email protected]

Thank you

mailto:[email protected]

Documents

2012 BW on HANA Modelling