Short Presentation Title

Report
SAP HANA Customer References and Services
Harald Bolbach / IBM Associate Partner
11th June 2013
Agenda
 The SAP HANA Appliance Architecture and the Influence on the underlying Infrastructure
 IBM’s Solutions for the SAP HANA Appliance
 Customer Reference: Migros Globus’ Warehouses
 IBM’s Services for the SAP HANA Appliance
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
2
The SAP HANA Appliance Architecture and the
Influence on the underlying Infrastructure
Data Store and Characteristics in Column and Row Store
Column Store
stores tables by column
Attribute 2
Row Store
stores tables by row
Attribute 3
Attribute 1
Attribute 4
 Calculations are typically executed on single or few columns
only.
 The table is searched based on values of a few columns.
 The table has a big number of columns.
 The table has a big number of rows and columnar
operations are required (aggregate, scan, etc.).
 High compression rates can be achieved because the
majority of the columns contain only few distinct values
(compared to number of rows).
 This is typical for OLAP workloads.
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
Tuple 1
Tuple 2
A
B
Tuple X
 The application needs to process only one single record at
one time (many selects and /or updates of single records).
 The application typically needs to access the complete
record and the columns contain mainly distinct values so
compression rate would be low.
 Neither aggregations nor fast searching are required
 The table has a small number of rows (for example
configuration tables).
 This is typical for OLTP workloads.
6
SAP HANA DB Architecture
The SAP HANA DB consists of:

Several In-memory stores
 One row store
 One or more column stores

A persistence layer with
 Data
 SQL data and undo log information
 Additional HANA information, such as modeling data
 Log:
 Information about data changes (redo log)
 Directly saved to persistent storage when transaction is
committed
 Cyclical overwrite (only after backup)

A global transaction manager
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
7
IBM’s Solutions for the SAP HANA Appliance
How does IBM make sure that the data are written in a fast
and reliable manner to the disks?
The SAP HANA database holds the bulk of its data
in memory for maximum performance
but
still uses persistent storage to provide a fallback in case of failure.
Time
Data savepoint
to persistent storage (at
least every 5 minutes)
Log written
to persistent storage
(committed transactions)
SAS Drives
SSD Drives / FusionIO
optimized for
optimized for
Throughput
high IOPS / low latency
(>800MB/s)
(>100 000 IOPS)
Power
failure
Server
local
storage
GPFS Filesystem
For maximum performance and scalability
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
9
IBM Workload Optimized Solution for the SAP HANA™
appliance
Applications
 Data Center Ready
SAP HANA®
 Reliability by eliminating
single points of failure
 Reduced risk, maintainance and
administration
ITM
GPFS
TSM
FPO functionality
IBM Director
SUSE
OS
SUSE Linux Enterprise Server
Priority Support for SAP applications
Server HW
Persistence in internal disks
Integrated Backup / Restore
High Availability
Monitoring
Disaster Recovery Solutions
Security and Auditing
 Technology Services provide
a safe project start in the datacenter
eX5 - x3690 X5 and x3950 X5
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
11
11
Hardware Impact for Products on In-Memory
Migration of Database Server Only
Switching to SAP HANA does not impact application servers or frontends
(see product availability matrix)
SAP HANA appliance runs on SUSE Linux (SLES)
Frontends
Change
Migration of database
to SAP HANA
appliance
required
Application Servers
Any OS
No Change
No change of frontends
Re-use of available
application servers
Sizing of current
application servers
remains valid
Any DB/
Any OS
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
HANA migration
SAP HANA /
SUSE Linux
No change
Data model
Custom extensions
12
IBM Systems Solution for SAP HANA sizes / building blocks / upgrade path
Size
XS
S
S+
M
L
Building Block
x3690 X5
x3690 X5
x3950 X5
x3950 X5
x3950 X5
Part Number
(Sys x - config)
7147-HAx
7147-HBx
7143 - HAx
7143 - HBx
7143 – HBx +
7143 – HCx
Intel CPU
2 x E7 2870
2 x E7 2870
2 x E7-8870
4 x E7-8870
8 x E7-8870
RAM
128 GB DDR3
256 GB DDR3
256 GB DDR3
512 GB DDR3
1 TB DDR3
(8 x 16GB)
(16 x 16GB)
(16 x 16 GB)
(32 x 16 GB)
(64 x 16 GB)
Log Storage
10 x 200 GB 1.8‘‘ MLC
SSD
10 x 200 GB 1.8‘‘ MLC
SSD
1.2 TB ioDrive2 FusionIO
1.2 TB ioDrive2 FusionIO
2 x 1.2 TB ioDrive2 FusionIO
Data Storage
-
-
8 x 900 GB 10k SAS HDD
8 x 900 GB 10k SAS HDD
16 x 900 GB 10k SAS HDD
Storage Ctrl
2 x M5015
2 x M5015
1 x M5015
1 x M5015
2 x M5015
Data / Log
Storage Summary
1.6 TB RAID 5 data and
log storage
1.6 TB RAID 5 data and
log storage
5.4 TB RAID5 data storage
1 TB log storage
5.4 TB RAID5 data storage
1 TB log storage
10.8 TB RAID5 data storage
2 TB log storage
Ethernet
4 x 10 GbE, 6 x 1 GbE
4 x 10 GbE, 6 x 1 GbE
4 x 10 GbE, 6 x 1 GbE
4 x 10 GbE, 6 x 1 GbE
8x 10 GbE, 12 x 1 GbE
Upgrade Option Scale
Up or Scale out
XS - > S
Up to 16 node scale out
with HA, SAP certified
S+  M
M  L (with L-option)
L  XL or XXL
Up to 56 node scale out with
HA, SAP certified
Up to 56 node scale out with
HA, SAP certified
Software
Preload:
SLES4SAP
GPFS
SAP HANA
Preload:
SLES4SAP
GPFS
SAP HANA
Preload:
SLES4SAP
GPFS
SAP HANA
Preload:
SLES4SAP
GPFS
SAP HANA
Preload:
Addtl. GPFS lic.
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
13
IBM Systems Solution for SAP HANA
Size
XL
XXL
Building Block
x3950 X5
x3950 X5
Part Number
(Sys x - config)
tbd
tbd
Intel CPU
8 x E7-8870
8 x E7-8870
RAM
2 TB DDR3
4 TB DDR3
(128 x 16 GB
or 64 x 32 GB)
(128 x 32 GB)
Log Storage
2 x 1.2 TB ioDrive2 FusionIO
4 x 1.2 TB ioDrive2 FusionIO
Data Storage
16 x 900 GB 10k SAS HDD
24 x 900 GB 10k SAS HDD
Storage Ctrl
2 x M5015
2 x M5015, 1 x M5025
Data / Log
Storage Summary
10.8 TB RAID5 data storage
2 TB log storage
16.2 TB RAID5 data storage
4 TB log storage
Ethernet
8 x 10 GbE, 12 x 1 GbE
8x 10 GbE, 12 x 1 GbE
Upgrade Option Scale Up
or Scale out
XL  XXL
(with additional memory, ioDrive2, M5025, EXP 2524)
Software
Preload:
SLES4SAP
GPFS
SAP HANA
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
Single node only
for SAP Business Suite
on HANA
Preload:
SLES4SAP
GPFS
SAP HANA
14
SAP HANA Scale-out
Simple
 No SAN required because of IBM’s General Parallel File System
 Expand database by adding nodes with GPFS
 One part number ordering for each node (stand-alone or scale-out)
Seamless
• Highly Available through IBM GPFS

Optimizes system availability

Intelligent Cluster integrated packaging and assembly
 Speeds installation and deployment
 Reduces implementation risk
Installation and managed services
 Speeds installation
 Ensures skills transfer
 Simplifies on-going maintenance
Scalable
 Scale to 56 TB and larger using IBM GPFS*
 Supports large database requirements

Validated by SAP
 16 Node x3690 X5 and x3950 X5
 56 Node x3950 X5 with HA*
* Reference SAP Note 1650046
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
16
DB 2 Nearline Storage complements with SAP HANA
 SAP BW NLS support for SAP HANA
 Major advantage: TCO reduction
Transparent Access
Transparent
Access
SAP NetWeaver BW
Reduced data volume on SAP HANA
Reduced SAP HANA license cost
BW OLAP
HANA Interface
Smaller SAP HANA box is sufficient
BI OLAP
General NLS
Interface
DB2 NLS Interface
DB2 DBSL
 SAP note Note 1695150 - DB6:
NLS Impl. - Usage for HANA DB, MaxDB
and DB2 for i
SAP HANA
Current Data
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
DB2 NLS
Storage
Older Data
17
17
SAP HANA Appliance – Scale Out with High Availability
Production up to 56TB with 56 Nodes
Production Node 1
512GB
FAILED Node
Production
Node22
512GB
Production Node 3
512GB
Production
Node44
Standby Node
512GB
SAP HANA® DB
DB partition 2
DB partition 1
DB partition 3
- SAP HANA® DB
worker node
- SAP HANA® DB
worker node
- SAP HANA® DB
worker node
® DB
- SAP HANA
HANA®
DB
worker
standbynode
node
- index server
- statistic server
- SAP HANA® studio
- index server
- statistic server
- index server
- statistic server
- index server
- statistic server
shared filesystem - GPFS
HDD
flash
HDD
flash
HDD
flash
primary data
data01
data01(1)
log01
data02
log02
data03
log03
log03(3)
HDD replica
data02(3)
data03(2)
data01(1)
data01(1)
log01(1)
log01(1)
flash
data01(3)
data02(2)
data03(1)
data01(2)
data02(1)
data03(3)
data03(3)
log02(3)
log03(2)
Log replica
HDD
log01(3)
log02(2)
log03(1)
log01(2)
log02(1)
log03(3)
log03(3)
X3950
X3950
X3950
X3950
7143-HBx (512GB)
7143-HBx (512GB)
7143-HBx (512GB)
7143-HBx (512GB)
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
18
Customer Example - Overview of the SAP BW based on HANA
Scaleout with High Availability & Disaster Recovery available since 12.2012 s. SAP Note 1755396
Test SAP BW system
Productive SAP BW system
SAP BW 7.3
SAP BW 7.3
LPARs
SAP BW
ASCS
SAP BW
PAS
SAP BW
JAVA SCS
SAP BW
PAS
LPARs
SAP BW
ASCS
SAP BW
PAS
SAP BW
JAVA SCS
SAP BW
PAS
Synchronous replication to secondary site in metro distance
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
19
Customer Reference: Migros Globus’ Warehouses
Key Performance Indicators MzG (Effective 01/2012)
Gross Revenue
779 Mio CHF (~ 623 Mio Euro)
45 % Fashion
26 % Delicatessa
15 % Home & Household
14 % Cosmetics
Department Stores
14
Gross Revenue
78,1 Mio CHF (~ 65 Mio Euro)
Only Fashion
Selling Points
23
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
Gross Sales Floor
60‘470 m2
FTEs
2670
Gross Sales Floor
8‘780 m2 (net)
FTEs
260
21
Biggest and smalles Performance Gain during Analysis and
Reporting with SAP BW based on HANA
Supplier Evaluation
Revenue per Seller
BW on HANA: 00‘17‘‘
Legacy BW:
22‘30‘‘
Factor:
79.41
BW on HANA: 00‘08‘‘
Legacy BW:
00‘20‘‘
Factor:
2.5
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
22
IBM’s Services for the SAP HANA Appliance
Configuration of a managed IBM SAP In-Memory environment
consisting of various server and storage components
0
1
2
3
4
5
6
7
8
9
10
11
VPN Connection to
IBM‘s Service Center
1
2
3
4
System x3650 M2
1
1
2
2
3
3
System Storage
4
4
5
5
6
6
7
7
8
8
9
10
9
10
11
12
11
13
12
13
DS4700
4GB/s
2GB/s
14
14
Monitoring, Events,
Remote Operations
BladeCenter H
IBM x3650 Management
Server
(Monitoring & Deployment
Tools)
IBM Blade Center
with Blades HS22
(Linux, SAP BWA)
&
IBM DS 3X, 4X, 5X
Storage (GPFS)
or/&
7
6
5
4
3
2
1
0
E SD
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
1
2
3
4
System x3850 X5
IBM x5 Server
(Linux, GPFS, SAP
HANA)
24
Service centers & Labs working for IBM Switzerland & IBM
worldwide in the IBM SAP In-Memory Area
Walldorf & Böblingen – SAP Labs
Hyderabad – Shared Service Center
Bangalore – Dedicated Service Center
Zürich/Basel/Geneva/Lausanne – SAP & In-MDB SMEs
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
25
IBM is the only one stop shop for SAP HANA
Plan
SAP HANA
Applications
SAP HANA
Value Identification
Build
Run
Business
Analytics
Jumpstart
SAP HANA
Turnkey
Solution Setup
SAP HANA
Proof of
Concept
SAP HANA
Realization
SAP HANA
Software
OS FS
Network
Technical
Architecture
Blueprint
SAP HANA
Appliances
SAP HANA
Infrastructure
and Basis
Installation
Hardware
Business Services
Technology Services
SAP HANA
Patching/
Revision,
Firmware, OS,
File System
Upgrades/
Support
SAP HANA
Application
Management
SAP HANA
Infrastructure
Management
also available
in the IBM
Cloud
Hard- & Software
Find the details in the
Solution Letter on IBM offerings around SAP HANA
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
26
Thank you!
Contact information:
Harald Bolbach
Dipl.-Verw.Wiss.
SAP Principal - Associate Partner
IBM Schweiz AG
Global Technology Services
Vulkanstr. 106, Postfach
CH-8010 Zürich
Phone: +41 58 333 53 01/ Mobile: +41 79 403 13 52
E-Mail: [email protected]
© 2013 IBM and/or SAP AG or an SAP affiliate company. All rights reserved.
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