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Since the second half of 2014 a new dedicated SAP HANA Quick Sizer tool has been available which covers SAP Suite on HANA including the CO-PA Accelerator option.

Also see SAP Note 1793345 Sizing for SAP Suite on HANA.

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THE INFORMATION BELOW IS NOW OUT OF DATE

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The SAP Quick Sizer tool is available now for SAP HANA and even includes content for the CO-PA Accelerator.

The mechanics of using the QuickSizer for CO-PA Accelerator are very easy.

1) Start the QuickSizer

2) Input the Customer No.

3) Provide a Project Name

4) Select SAP In-Memory Computing

5) Select HANA Rapid Deployment Solutions

6) Locate the row element for CO-PA-ACC

7) Input the Number of CO-PA Users, the Source Data Footprint in GB, and the estimated Compression factor (7 is the default)

8) Click on the Calculate Results button

Screen print from Step 7…

QuickSizerInputs.png

What is meant by number of users?  It is not the number of concurrent users or the number of named users,

rather the user concept is explained in SAP Note 1514966 which is extracted here.

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To estimate the maximum number of active users (i.e. users which

cause any kind of activity on the server within the time period

of one hour) that can be handled by a HANA server, we have chosen

the following approach.

we assume that HANA queries can be divided into three categories

(“easy”, “medium”, “heavy”), which differ in the amount of CPU

resources that they require. Typically, “medium” queries use twice

as much resources as “easy” ones, while “heavy” queries require ten

times as much resourses.

Furthermore, we assume that HANA users can be devided into three

categories (“sporadic”, “normal”, “expert”). The user categories

are defined by the frequency of query execution and the mix of

queries from different categories. “Sporadic” users typically

execute one query per hour, and run 80% “easy” queries and 20%

“medium” queries; “normal” users execute 11 queries per hour,

and run 50% “easy” queries and 50% “medium” queries; and “expert”

users execute 33 queries per hour, and run 100% “heavy” queries.

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What is the source data footprint and how is it captured?

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Memory sizing of HANA is determined by the amount of data that

is to be stored in memory, i.e. the amount of disk space

covered by the corresponding database tables, excluding their

associated indexes. Note that if the database supports

compression, the space of the uncompressed data is needed.

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The SAP note above further provides instruction on how to obtain the uncompressed table sizes

using a script or stored procedure.  The method required will differ by source database but one of

the inputs to the script is to identify which ERP tables should be selected.

So how do you go about determining which CO-PA tables go into the input for the source data footprint?

A short cut method for determining the source data footprint is to use transaction KECM or

report RKE_ANALYSE_COPA.

Click on the item “Transaction Data” from the menu.

KECM Transaction Data.png

Tick the bottom item “Data Volume of Specific Tables” and then select the radio button

“Rebuild in Foreground”.  Execute the report.  After you build the analysis, you can return to this

transaction and select the radio button “Display Analysis Data” before clicking Execute.

KECM Data Volume.png

Upon execution, the report output will display record counts and memory consumption in MB

for each CO-PA table.  For the CO-PA Accelerator we are only interested in the CE1, CE2, and CE4

tables being replicated into SAP HANA.  However if BusinessObjects reporting is to be utilized other

tables may be required to be replicated into SAP HANA depending on the specific reporting requirements.

KECM Output.png

The memory consumption figures are calculated as a theoretical size by multiplying the number

of actual records in the table by the ABAP table length and converting to MB.  However actual table

size in the database will be less because many CO-PA fields will be blank.  Nevertheless this is an easy

and quick way to get a worst case uncompressed sizing for CO-PA.  Just divide the Memory Consumption

numbers shown above by 1024 to input into the QuickSizer in GB.

To understand further the Memory Consumption figures shown above, use transaction SE11 to display

a CO-PA table.

SE11 Display DB table.png

Then select from the menu Extras –> Table Width…

SE11 Extras Table Width.png

The Width of Table popup screen is displayed.

SE11 Width of Table CE1IDEA.png

As proof to the Memory Consumption figure above, multiply the number of records in the

table x the ABAP Length:

69,019 x 2,274 = 156,949,206 bytes which divided by (1024)^2 coverts to 150 MB rounded

as shown in KECM.

If your CO-PA Accelerator scenario will involve BusinessObject reporting then you will use SLT

to replicate not only the CO-PA transaction data but also the related master data and text tables

into SAP HANA.  You might want to expand the source data footprint to include these additional

table sizes in the QuickSizer tool.  (However our early customer feedback indicates the master

data and text tables have little influence on HANA sizing.)

Nevertheless, in order to identify the CO-PA relate tables you can execute function module

RKE_FILL_FIELD_TABLE from transaction SE37.

SE37 FM RKE_FILL_FIELD_TABLE.png

After pressing F8 or clicking on the Test/Execute icon you will input the Operating Concern

for field ERKRS and input ‘1’ in the PA_TYPE field for costing-based CO-PA.

SE37 Initial Screen.png

Press F8 or click Execute again and you will see the Table results.

SE37 Results.png

Click on the Details View/Edit icon View Icon.png next to the 228 Entries under FIELDTAB.

SE37 FIELDTAB CHECKTABLE.png

You will need to take note of all of the master data tables listed under CHECKTABLE.

Scroll to the right and also take note of all of the text tables listed under TXTAB.

SE37 FIELDTAB TXTAB.png

To get the source data footprint for these tables you can use the script mentioned in SAP Note 151496.

Alternatively uou could calculate the Memory Consumption manually for each table using the method

shown above, where you would obtain record counts using transaction SE16 for each table.

SE16 Record Count.png

One final option, you can also view table sizes from transaction DB02 to obtain the source data footprint.

But there are a few things to watch out for if using DB02.  First, only include the Data size and not the

ndex size in the QuickSizer tool.  Also be sure to convert from KB to GB for the QuickSizer.

DB02 Table CE1IDEA.png

You do not want to use DB02 however if database compression is active on the table, because this will not give

you the correct (uncompressed) value to input into the SAP HANA QuickSizer.

DB02 Oracle Table CE1R110.png

Coming back to the QuickSizer tool, here is an example of the output it generates based on 100 users and

250 GB of source data.

CPU category – S (Small)

SAPS (total) – 46,200

Memory category – XS (eXtra Small)

Memory (MB) – 73,728

HANA disk GB – 358

SCU Class – A

QuickSizerResults.png

The above information should be sufficient data for you to have discussions with a hardware provider
on what size HANA appliance may be required for implementing the CO-PA Accelerator.

Finally, you may need to adjust the source data footprint input value if your organization expects growth in the

CO-PA tables due additional periods of data retention, or due to to ERP roll outs to new business units or if

you seek to move archived CO-PA data into SAP HANA.

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5 Comments

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  1. Eric Poellinger

    We are trying to know if we would need CO-PA on HANA for a new installation. 

    How would we calculate the ‘data footprint’ since the above shortcut (very helpful!) would not be available in our system?

    (0) 
    1. Jeffrey Holdeman Post author

      For a new installation of SAP ERP you would not have a source data footprint to start with, so you would have to estimate your record count and record width and convert to GB.   The number of sales documents (actually the number of line
      items) is typically a good indicator of CO-PA data volumes.  However this
      rule applies mainly for companies that manufacture and sell products.
      If your organization is more similar to a financial services company, in which case you
      could have to estimate line items that arise from General Ledger
      postings.  Keep in mind that CO-PA is intended for reporting revenues and
      costs only, thus no balance sheet items.  Also do not double count with
      postings that will flow into Cost Center Accounting, or other objects like
      Internal Orders or Project Systems, unless you foresee that those objects will
      allocate or settle their costs into CO-PA.  Sorry this is not an easy
      estimation process and depends on the customer situation.

      If you want to try for some precision in the estimate then you
      have to multiply the number of expected CO-PA line items times the table
      width.  A basic CO-PA line item table without any customization is 762
      bytes wide.  Every custom field which is added to the operating concern
      increases that size.    The absolute limitations are stated in
      SAP Note 1029391 which mentions 4,030 bytes as the maximum allowable table width as of basis 6.20 package 25.

        

      With HANA we typically see 6-10x compression of the CO-PA data
      over anyDB.  For comparison, a couple of our large CPG companies that have
      many years of CO-PA data (hundreds of millions of records)  run their CO-PA Accelerator on a 250GB HANA appliance.

      (0) 
  2. Jeffrey Holdeman Post author

    Hi Roland

    I agree with you.  The CO-PA-ACC line appears to have been removed from the QuickSizer tool.  I don’t know the background on this change, but I’ll try to look into it and post an update.  In the meantime, perhaps you can see if SAP Note 1872170 could be useful to help prepare your estimate.  The report which is mentioned there can be limited to only the CO-PA line item and profitability segment tables.  Further info on sizing for Suite on HANA can be found on SAP Note 1793345.

    Best regards,

    Jeff Holdeman

    (0) 

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