SAP HANA Sizing Guide for Performance & Scalability

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Performance & Scalability, SAP
2017
Sizing SAP HANA

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© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Introduction and Basics of HANA Sizing
Initial Sizing
Migration Sizing
Agenda

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SAP HANA Sizing – In a Nutshell
Customer Interested in SAP
S/4HANA
New SAP HANA system
(Greenfield Sizing)
Existing SAP system migrated to
HANA
(Migration Sizing)
Use HANA Quick Sizer Use Migration Reports
Connect with hardware vendor and check for
sample configuration or get started with SAP
CAL
Find deployment options: Appliances, SAP
Tailored Datacenter Integration (TDI), Cloud via
SAP Cloud Appliance Library (CAL)

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SAP HANA Sizing KPIs – Game Changer
▪ Different sizing approach: HANA
sizing vs. sizing of traditional DB
▪ Memory is the leading driver for
HANA sizing
▪ Massive parallelization in analytical
scenarios will have an influence on
Response Times; hence CPU
requirement will get more important
for analytical scenarios
▪ Mixed transactional and
analytic workloads now
possible with SAP HANA but
compete for shared resources
▪ Disk is required for data persistence and for logging
data
▪ Disk sizing depends on type of store which is used
▪ Sufficient I/O performance required to enable
processes to run with acceptable data throughput and
storage system latency.
Disk size
Disk I/O
▪ Compared to anyDB, more CPU power is required to
fully benefit from the parallel processing capabilities of
HANA for optimal response times
CPU
▪ Memory sizing is determined by the data footprint in
SAP HANA (business and meta data in column and
row store)
▪ Memory is also used by other components (e.g.
HANA caches) and for processing of requests
Memory
▪ Network sizing typically focuses on the bandwidth and
is described in gigabits per second (gbps)
Front-end
Network
Load

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Memory: Leading Driver for SAP HANA Sizing
▪ The main driver for memory sizing is the table data of the planned SAP HANA
system
▪ Most tables are located in the highly compressed column store of SAP HANA
▪ For working memory of the database and temporary calculations, almost the
same size as for table data is required additionally
▪ A SAP HANA database includes further memory areas, such as code, stack,
caches, operating system and other system files. These areas are typically small
compared to a typical database

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Approaches to SAP HANA Sizing
General Information: Different Memory Areas in SAP HANA
Relevant memory parts
1. The memory area allocated for
table data, either row store or
column store.
2. Subsequently, the buffer for
dynamic and temporary
computations is assumed to be
equal to the table data size
3. “Offset” refers to space required
for code and stack, caches and
services and the operating system.
 Note: Used memory consists of
temporary memory parts and table
data, either in row store or in
column store. HANA code and
stack is also included, but usually
negligible.
Operating System
HANA caches and services (code and
stack included)
HANA Table data
(row store and column store)
Temporary memory
Pool
Sizing
“offset”
Results
of sizing
reports
Room
to grow
Depends on node size
~50 GB
Table footprint
(measured)
Equal to table footprint
(assumed)
Sizes

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Greenfield Sizing for SAP S/4HANA
For greenfield sizing for SAP S/4HANA,
use HANA version of Quick Sizer
Please note:
The basics of the calculations
are the same in HANA QS and
in the Classic QS, e.g. the think
times of the different user types
(low, medium, high) are the
same

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Data Aging
Data aging is a business data management concept for reducing the
memory footprint in
SAP HANA
▪ Only operationally relevant (“hot”/current) data is loaded into main memory of SAP
HANA
▪ Other (“cold”/historical) data remains primarily stored on disk, not affecting hot data
performance, yet cold data remains accessible via SQL on request

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Since February 2016, a data aging logic has been implemented in Quick
Sizer.
There are two residence periods. One for memory (aging period) and one for
disk (archiving period)
HANA Quick Sizer News
Data Aging in HANA Quick Sizer
▪ There are aging objects available, if the aging column (residence time in memory) is changeable. Per default
the aging period has been set to 24 months
▪ There are no aging objects available, if the aging column (residence time in memory) is empty and highlighted
in blue.
▪ Since March 2017: Introduction of ‘What if analysis for the retention times (disk/memory)’

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Example What-If Analysis Data Aging
Option 1: HANA Memory Result – 4,2 TB for S/4HANA Server (24 month residence time in memory)
Option 2: HANA Memory Result – 8,9 TB for S/4HANA Server (no data aging)

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The goal of sizing for Sizing SAP S/4HANA Embedded Analytics is
▪ To determine how many CPU Cores/Threads and memory are required for the
processing of target number of parallel queries (without index support)
▪ And at the same time achieving the average target response time
Sizing SAP S/4HANA Embedded Analytics
Object page
Overview page Analytical List Page

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The SAP S/4HANA embedded analytics Sizing has been implemented
in August 2017
Quick Sizer Update
Sizing SAP S/4HANA embedded analytics

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Process for greenfield sizing
Please consider to start with an OLTP sizing, e.g. SAP Simple Finance. Then you
get the name of the tables from result level ‘Key Capabilities’ and the respective
disk table lines from default result level 'software components'. This information
can be used as input for your SAP S/4HANA embedded analytics sizing.
Example Analytical Fiori Applications
Input
Result

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Sizing Report for SAP S/4HANA
Report /SDF/HDB_SIZING
▪ Described in SAP Note 1872170 – Suite on HANA sizing report
Scope
▪ Runs on SAP_BASIS 620 and higher
▪ Is suitable for sizing of all Business Suite products (ERP, CRM, SCM, SRM, etc.)
▪ Not suitable for BW (Refer to SAP Note 1736976 – Sizing Report for SAP
Business Warehouse on HANA)
Functionality
▪ Estimates the maximum memory consumption of the database, if migrated to
SAP HANA
▪ Is independent of the source database provider
▪ Considers distribution of tables to row and column store
▪ Considers differences for secondary indexes
▪ Considers compression of legacy database

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Sizing Scenarios
The report can also be used for different sizing scenario such as SAP Suite on HANA, SAP
S/4HANA Finance, SAP S/4HANA.
And you can choose the HANA version
1872170 – Suite on HANA sizing report

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How to Run the Report
Selection screen on anyDB:
▪ For a sizing of the entire database leave the “list of tables fields empty”
▪ Maximum of 100.000 records read per tables is representative enough for a full database
sizing
▪ Use higher sample size if you are sizing only a subset of tables. (I.e. For VDM, HPAs sizing)
▪ If you already know of specific table distribution between stores, specify it in the “Changes to
standard stores distributions”

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Algorithm of Sizing Report /SDF/HDB_SIZING
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• The total number of entries of each tables is read from the
database statistics
2
• A random sample of data is read from every tables in the
system
3
• Out of this sample, the report calculates the average number
of bytes per column
4
• Out of the average size per column and the total record count,
the uncompressed size of a column is calculated
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• To the uncompressed size an average compression factor is
applied to get the estimated size in HANA.
Example: A typical column
“mandt” has type c and values
such as ‘100’, ‘000’, ‘066’. The
report will calculate an average
size of 6 bytes for this column.
Example: Column “mandt” has
an average size of 6 bytes and
the tables has 100 records.
Total uncompressed size of the
column is 600 bytes.
The size estimation for keys
(primary, secondary keys, etc.)
is more complex (and more
accurate) but uses the same
metrics (avg. size per column
and record count)

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Results of Sizing Report /SDF/HDB_SIZING
The sizing report includes the sizing projections, based on the actual table sizes in
the legacy system as well as an estimation of how much the memory footprint can
be reduced using functionalities that HANA will enable.

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How to Interpret the Results of the Sizing Report
▪ Column store and row store estimations have good enough accuracy (10-20%).
Still, do not forget it is an estimation.
▪ Work Space (temporary memory) estimation uses a simple formula (data size in
memory) * 2. Based on experiences, if the work space is bigger than 3TB, it
might be oversized.
▪ Always check the top tables. Very often, you will find basis tables with
deletion/archiving potential such as idoc, workflow, application log tables, etc.
See SAP Note 706478 – “Preventing Basis tables from increasing considerably”
for more details.
▪ The total estimated memory requirement given by the report should not be
considered as the final memory sizing result. Take into account that:
– Not all the server physical memory will be available to HANA (OS and other
processes are run too).
– There should be enough space left for future data growth or functional
extension
▪ The sizing report takes a snapshot. Any growth between that date and the go-live
date should be considered.

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Data aging
▪ Workflow documents were added to the already existing data aging estimation for
Application log, Change documents and iDocs. The addition of this objects
completes the full coverage of “service objects”.
▪ Residence time for data aging objects is now changeable by the user
Memory Sizing Report News
Integration of HANA 2.0 memory consumption reduction such as MidSize LOB and smaller footprint of empty
and small tables

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SAP S/4HANA Readiness Check
▪ The report is now available in the SAP S/4HANA Readiness Check which will be
available free to anyone who has an SAP maintenance agreement (an S-user
account).

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Table distribution in scale-out landscapes is based on table groups. The
sizing report provides you with the size of the table groups.
If you want to determine the number of required nodes, based on the information given by the sizing
report, you have to check the guide SAP S/4HANA Scale-Out Sizing

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Outlook
▪ Improve “Work Space” (or temporary memory) sizing and CPU sizing
▪ Add more data aging objects to the report (especially, estimation of saving on
“application objects”)
Other planned enhancements
▪ Integrate IOPS Sizing
▪ Reflect further simplifications in data model

Conclusions & More
Information

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Conclusions
The HANA sizing approach is different from the sizing of
traditional databases
Greenfield Sizing for HANA should be done with Quick
Sizer
Migration sizing of an existing system to HANA should be
done following SAP Note 1872170
HANA-specific CPU sizing method for sizing of HANA
applications with high level of parallelization and concurrent
load has to be applied

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Sizing information and tools
Sources of published sizing documentation
www.sap.com/sizing
– Access to Quick Sizer
– Access to sizing guidelines, for example, SAP HANA accelerators
SAP Support Portal
– SAP Note 1872170 – S/4HANA memory sizing
– SAP Note 1793345 - Sizing for Suite on HANA
– SAP Note 2298290 - New Sizing Report for SAP BW/4HANA
– SAP Note 1514966 - SAP HANA 1.0: Sizing SAP In-Memory Database
– SAP Note 1767880 - Non-active data concept for BW on SAP HANA DB
HANA Sizing - General
Introduction to Sizing on SAP HANA video
HANA Quick Sizer (for greenfield sizing) & SAP SoH Migration Sizing
Greenfield Sizing with SAP Quick Sizer demo video

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Sources of Information
http://www.sap.com/sizing
▪ Sizing methodology
▪ Access Quick Sizer
▪ Access Sizing Guidelines
http://www.sap.com/benchmark
▪ Certified benchmark results
▪ Descriptions of the available benchmarks
http://www.sap.com/performance
▪ Tips for performance improvements

Contact information:
Sebastian Schmitt
sebastian.schmitt@sap.com
+49 6227 7 50189
+49 151 18874932
Thank you.

SAP HANA Sizing Guide for Performance & Scalability

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