This blog will explain the maintenance of logical file names.
Questions that will be answered in this blog are:
Why use logical file names?
How to setup logical paths and logical file names?
Which variables can be used in logical file names and logical paths?
What is new in transaction SFILE?
Why use logical file name?
The use of a logical file name in any ABAP keeps the location and name name of the file constant from a logical function perspective. The actual implementation of the file location can then be maintained by the basis team. If they want to move files around, they can do so, as long as they also update the logical files. Also this way an ABAP developer does not need to worry in case of any OS switch (for example from Windows to Linux).
The names are the same on development, QA and production system. The basis team can choose to have different file structures on each system. For example by including the system ID in the folder name.
Maintaining logical file path
To maintain logical file names, start transaction FILE:
With new entries, you can add new logical file path.
We will use A2_GLOBALPATH here as example. Select the entry and click on Assignment of physical path to logical path:
Select the operating system to see the details:
Logical file names
Logical file names are also maintained with transaction FILE:
Parameters in naming
The following parameters can be used in the naming conventions:
Parameter
Meaning
<OPSYS>
Operating system in function module parameter
<INSTANCE>
Application Instance
<SYSID>
Application name in accordance with system field SY-SYSID.
<DBSYS>
Database system in accordance with system field SY-DBSYS
<SAPRL>
Release in accordance with system field SY-SAPRL
<HOST>
Host name in accordance with system field SY-HOST
<CLIENT>
Client in accordance with system field SY-MANDT
<LANGUAGE>
Logon language in accordance with system field SY-LANGU
<DATE>
Date in accordance with system field SY-DATUM
<YEAR>
Year in accordance with system field SY-DATUM, four characters
<SYEAR>
Year in accordance with system field SY-DATUM, two characters
<MONTH>
Month in accordance with system field SY-DATUM
<DAY>
Day in accordance with system field SY-DATUM
<WEEKDAY>
Weekday in accordance with system field SY-FDAYW
<TIME>
Time in accordance with system field SY-UZEIT
<STIME>
Hour and minute in accordance with system field SY-UZEIT
<HOUR>
Hour in accordance with system field SY-UZEIT
<MINUTE>
Minute in accordance with system field SY-UZEIT
<SECOND>
Seconds in accordance with system field SY-UZEIT
<PARAM_1>
External parameter 1 passed in function call
<PARAM_2>
External parameter 2 passed in function call
<PARAM_3>
External parameter 3 passed in function call
<P=name>
Value of a profile parameter in the current system
<V=name>
Value of a variable in the variable table
<F=name>
Return value of a function module
Transaction SFILE
Transaction SFILE is a new maintenance transaction. It is available as of S4HANA 1610. The main functions are the same as FILE. Main new function is the mass download and upload of definitions.
When executing data archiving you have to be acting careful. The data archiving write and delete processes can be consuming a lot of CPU power from the database. Also, if you are not careful you might, by accident, claim all background processes. This blog will explain how to limit the amount of batch jobs used for data archiving. The data archiving run process itself is described in this blog.
Questions that will be answered in this blog are:
How can I limit the amount of deletion jobs?
How can I restrict the archiving jobs to run on a specific application server only?
Limit amount of deletion jobs
When the write run of data archiving is finished, this can have delivered many files. If you are not careful with the deletion, you select all files and each file will start a deletion run. This will consume a lot of CPU power on database level, since the deletion run will fire many DELETE statements to the database in rapid sequence. Also you might consume all batch jobs, leaving no room for any business batch job.
In stead of running the deletion from SARA, you can also run the deletion via program RSARCHD:
With this example, MM_EKKO files will be deleted. Maximum of 50 files from 1 archiving run will be processed, with a maximum of 2 deletion batch jobs running at the same time.
General application server restrictions via batch job server group
In SM61 you can setup a special batch job server group. Here can assign a single application server for you data archiving batch job processing. We assume here you created a group called DATA_ARCH.
In SARA you can now goto the general data archiving settings:
Now you can link the batch job server group:
With the button JobClasses you can specify the job priorities per data archiving function:
A = high priority, C = low priority. The above screen shot is an example.
Some archiving object use the AIS (archiving information system) to enable the end user a quick retrieval of archiving information. This note will give warning before start of deletion if the AIS is note active for the object: 2624077 – Starting delete jobs: Check for active info structures.
This blog addresses the main challenge in SAP data archiving for functional object: the discussions with the business.
This blog will give answers to the following questions:
When to start data archiving discussion with the business?
How to come to good retention periods?
What are arguments for not archiving certain data?
Data archiving discussion with the business
Unlike technical data deletion, functional data archiving cannot be done without proper business discussion and approval.
Depending on your business several aspects for data are important:
Auditing and Sox needs
Tax and legal retention periods
Product data requirement
And so on…..
Here are some rules of thumb you can use before considering to start up the business discussions about archiving:
Rule of thumb 1: the system is pretty new. At least wait 3 years to get an insight into which tables are growing fast and are worth to investigate for data archiving.
Rule of thumb 2: if your system is growing slowly, but the infrastructure capabilities grow faster: only perform technical clean up and don't even start functional data archiving.
Rule of thumb 3: if you are on HANA: use NSE (Native Storage Extension) or check if the data aging concept for functional objects is stable enough and without bugs. NSE and data aging does not require too much work, it is only technical and it does not require much business discussions. Data retrieval from end user perspective is transparent.
Data analysis before starting the discussion
If your system is growing fast and/or you are getting performance complaints, then you need to do proper data analysis before starting any business discussion.
Start with proper analysis on the data. Use the TAANA tool to get insights into the data: how is the distribution of data per document type, per year, per plant/company code etc. If you want to propose retention period of let’s say 5 years, you can use the TAANA results to show what percentage of data you can move out of the database.
Secondly: if you have an idea on which data you want to archive, first execute a trial run on a recent production copy. There might be functional blocks that prevent you from archiving data (like not closed documents).
Third important factor is the ease of data retrieval. Some object have a nice simple data retrieval function, and some are really terrible. If the retrieval is good, the business will more easily accept a shorter retention period. Read more on technical data retrieval in this blog.
As last step you can start the business case: how much data will be saved (and how much money hence will be save) and how much performance would be gain. And how much time is needed to be invested for setting up, checking (testing!) and running the data archiving runs.
In practice data archiving business case is only present in very large systems of 5 TB and larger. This sizing tipping point changes in time as hardware gets cheaper and hourly manpower costs go up.
The discussion itself
Take must time in planning for the discussion itself. It is not uncommon that archiving discussions take over a year to complete. The better you are prepared the easier the discussion. It also helps to have a few real performance pain points to get solved via data archiving. There is normally a business owner for this pain point who can help push data archiving.
This blog will explain how to execute a data archiving run.
Questions that will be answered in this blog are:
Which settings do I need to make or check before data archiving run?
How to perform the data archiving run?
How to validate the data archiving run?
How to retrieve that archived data?
This blog assumes you have finished the basic technical data archiving setup as described in this blog. It also assumes you have made agreements with your business on the retention periods. For more information and tips on discussions with the business teams on data archiving, read this blog.
If you are looking for specific functional data archiving runs:
Functional data archiving example: purchase requisitions
To explain the functional data archiving we will use Purchase Requisitions as example. Technical object name is MM_EBAN.
To see which tables are archived hit the Database Tables button. Here you can see the list of tables from which data potentially be archived:
If you want to see the other way around, which table is used in archiving objects, do put in the table as entry point, to retrieve list of archiving objects. In this example archiving objects that delete from table EBAN:
Dependency of objects
By clicking the top left button on the archiving object you get the archiving dependency view. For MM_EBAN this is pretty simple: it has no dependencies.
As example for dependencies this is the overview for sales orders (SD_VBAK):
Here you can see that before you can archive sales orders, you should archive the billing documents first. And for the billing documents, you should archive the deliveries first.
Functional archiving settings
First we have to make or check the object specific functional archiving settings.
In the case of purchase requisitions we have to set the retention periods per document type:
Pre-processing step
Some archive object have a pre-processing step. MM_EBAN has one as well. In this step data is selected and marked for archiving (many times by setting deletion flag or other indicator).
In the step create the variant (give it a useful name) by putting in the name and pressing Edit. On the next screen fill out your data select the log level. Go back to the first screen and select the start data and spool parameters. When both lights are green, hit the execute button. When you click the job log button you check for the results.
Example of result of pre-processing run:
As you can see not all selected data is archived. Transactions that are not completed from business point of view will not be flagged for archiving.
Write run
If you have done the pre-processing step, continue with the write step. Principle is the same: select the data and log level. Important in the write step is to correctly fill the Archiving Session Note with a useful text. This text is put as label on the archive file for later retrieval:
When done plan the job and execute. Result looks like:
Pending on your technical system settings the file will be stored automatically or you still need to do this manually.
Storage run
If you have setup the system to store files in content server, you first have to execute storage run. For more details see this dedicated blog.
Deletion run
Finally we can now start the deletion run: the actual clean up of old data happens now.
Select the data files you want to archive and start the run.
Word of care with deletion: please don't select too much files and subsection in one go. Each file sub section will result into a deletion job. The deletion will put significant load on the database, since it will be pushing out a lot of data. If you are not careful you will launch easily 20 or more heavy deletion jobs that run in parallel and that might severely decrease system performance.
Result of archiving deletion run:
Checking archive result
The result checking is possible by looking at the technical correctness of the archive file.
In the archiving object choose the Overview button. Then select the archive file you want to inspect. A correct file should like like this:
In the testing phases and first production runs, you also want to do record counting. A good way is to run the TAANA transaction for key tables you want to archive before the archiving and after the archiving. The difference should match the deletion counter on the write and deletion logs. If you find differences: check for bug fix OSS notes.
Data retrieval
Retrieving archived data is different per archived object. Some retrieval is nicely integrated into the normal transaction. Some require extra transaction to run. Some retrieval is via special program.
Data retrieval of purchase requisitions can be done via SARA and choosing the read option.
Here you first need to manually select the archive files to read from (see I did not give the note and regret it, since the file has no meaning now…):
Before starting to check the data archiving for an object, it is best to check and read the OSS notes for the pre-processing, write, delete and read programs. Apply the bug fix notes and read about certain aspects, before you have time-consuming effort to figure out you have a bug or a certain feature that is documented inside the notes.
Controlling amount of parallel batch jobs
The deletion phase of archiving can lead to uncontrolled amount of parallel batch jobs. See this dedicated blog on how you can control it.
Data archiving run statistics
Transaction SAR_DA_STAT_ANALYSIS can be used to collect statistics on the data archiving runs:
FIORI app
If you are running recent version of S4HANA, you can also use a FIORI app for monitoring the data archiving runs. Read more in this dedicated blog.
This blog will explain the general technical setup to be performed for SAP data archiving.
Questions that will be answered in this blog are:
Which generic settings do I need to make for data archiving in the technology domain?
Why should I use a content server to store archive files?
For getting insights in what to archive, read this dedicated blog first.
Data archiving content server setup
For data archiving you can use the file system for storing the archive files. This you can do to perform initial testing. For productive use it is best to store the archive files in a content server. It will not be the first time an overzealous basis person in need for file storage deletes some old files in a directory called /archive…..
After you install the content server, set up in OAC0 the customizing for the content server to use it for Archivelink:
In this initial screen no object is selected. Now press the Customizing button.
Set the Cross-Client File Names/Paths to your needs. You can do that from this menu, or directly from the FILE transaction.
Set the physical path name to be used:
Even when you use content server the file will first be written to physical path for temporary storage.
And check the archive file name:
Technical settings per archiving object
Per archiving object you can set the technical settings. Normally you keep settings the same per object. Only for very large installations with archiving or special needs, you might want to deviate.
In the technical settings per data archiving object set the following:
Important settings to set:
Max size in MB or the max objects
Check the variants (some variants for production have still deliberately the test tick box as on: you have to change it)
Best to leave the delete jobs to Not scheduled (large archiving runs can create many files and many deletion jobs to kick in at the same time): best to do this manually in controlled way
Start storage automatically or manually is a choice for you
Best to store before deletion. This is the most conservative setting.
Best to delete only from storage system: if file is not stored properly in any way, deletion will not have. This is the most conservative setting.
Actual data archiving runs
How to execute the actual data archiving runs is explained in this dedicated blog.
This blog will explain how to setup print list archiving.
Questions that will be answered are:
What is use case of print list archiving?
How to setup print list archiving?
How to test print list archiving?
How to troubleshoot issues with print list archiving?
Goal of print list archiving
The business sometimes needs to store report output for a longer period of time. They can print the information and put it in their archive. This leads to a big physical archive.
You can also give the business the option store their output electronically in the SAP content server.
Set up or check content repository
First check which content repository you want to use to store the print lists. The type of content repository must be “ARCHLINK”. Menu path in customizing is as follows:
Or you can go there directly with transaction OAC0.
Content repository A2 is default present in the system and is used in the example below. A2 is pointing towards the SAP database for storage. For productive use a SAP content server in stead of SAP database.
Customizing for print list archiving
In the following customizing path you find all the actions required for the print list archiving:
First check that print list document type D01 is present and is using ALF as document class:
In the Edit links section, you can set for document type D01 which content repository is should use.
Then check if the number ranges for archivelink are properly maintained (if empty create new number range):
Then activate the print list queues:
Next step is to select the action to schedule the storage job. This job should not run faster than every 15 minutes.
Final step is to setup the archive printer. You can later on see it with transaction SPAD as well.
Important here: short name must be ARCH. Device type and device class must be set to archiving.
On the access method tab also set access method to archiving.
If you follow this procedure you will initially run into this strange screen:
You didn’t do anything wrong yet. The problem is that the option for print to archive is not displayed by default. First go to the properties of a working printer to enable the archiving output option:
The rest of the note is self explaining:
Start SE38 and run program SHOWCOLO
Print the output list to printer ARCHIVE and archive mode selected
Goto SP01 find the spool, select menu path Print with changed parameters
Hit the Archive button
Start transaction OAM1 and hit the execute button next to Archive queue
Start transaction OADR to read from the archived print lists
From the list take the document and select the button “Display from storage system”
This blog focuses on technical data objects archiving and clean up by performing deletion. If you want to setup functional archiving, start reading this blog.
Using SM36 you can plan all SAP standard jobs (which include a lot of clean up jobs for spools, dumps, etc) via the button Standard Jobs.
By hitting the button Default scheduling in an initial system, or after any upgrade or support package, the system will plan its default clean up schedule.
S4HANA has different set up of standard jobs. See blog.
Clean up of old idocs
Idoc data is stored in EDI* tables. Largest tables are usually EDI40, EDIDS and EDIDC.
Old idocs can be deleted using transaction WE11.
In batch mode you can schedule it as program RSETESTD.
In the bottom of the selection screen are the technical options:
The idoc deletion job can fail if there is too many data to process. If they happens remove the 4 tick boxes here and use the separate deletion programs: RSWWWIDE, RSARFCER, SBAL_DELETE and RSRLDREL2. These 5 combined programs will delete the same, but run more efficiently. This procedure is also explained in OSS note 1574016 – Deleting idocs with WE11/ RSETESTD.
Table logging is stored in table DBTABLOG (general information on table logging can be found in this blog). Deletion can be done using transaction SCU3 and then choosing the option Edit/Logs/Delete, or by using program RSTBPDEL.
Application logging (SLG1) is stored in tables BALDAT and BALHDR (for general information on the use of the application log, read this blog). Deletion can be done using transaction SLG2 or by using program SBAL_DELETE.
The last options to fine tune the number of logs per job and the commit counter setting do not appear by default. Select menu option Program/Expert mode first.
Old RFC data can be deleted using transaction SM58, selecting some data, then in the overview screen select the menu option Log File/ Reorganize. Or by starting program RSARFCER.
If you are using MDG: it has its own set of change pointer tables (MDGD_CP_REP_STAT). Clean up transaction code is MDGCPDEL. Program for batch job clean up is RMDGCPCLR.
Workflows are stored in many tables starting with SW*.
You can delete work item history with transaction SWWH or program RSWWHIDE.
This clean up will only do the work item technical history and not the workflow itself. If workflow itself can be deleted or is to be archived is a functionality decision that the depend on the business and audit needs.
The workflow deleting program can create large amount of spools. If this is not wanted use the NULL printer.
If your business is using the GOS (generic object services) to see workflows linked to a business document, and they cannot retrieve the archived work item, please follow carefully the instructions in OSS note 2356250 – Not able to view archived workflows.
If you want to delete the actual workflow you have to run program RSWWWIDE.
Take care that before deleting workflows you have checked that these are not needed for audit or financial proof. Some workflows will contain approval steps with a recording of who approved what at which time.
If you have a large amount of items in your SAP inbox, you can delete them via program RSSODLIN. Background is in OSS note 63912 – SAPoffice: Delete user sessions.
Test this first and check with the data owner that the documents are no longer needed.
For a full explanation on deleting SAP office documents (including all the pre-programs to run) and bug fix notes: read this dedicated blog on SAP office document deletion.
Usually the business will not allow deletion of SAP office document (unless they are very old). You might be ending up with a SOFFCONT1 table of 100 GB or more.
In stead of deleting SAP office documents, you can also migrate them to a content server. Read more in this blog.
Change documents
Change documents do contain business data changes to business objects. If tables CDHDR and CDPOS grow very big, you start with an age analysis. You can propose to business to delete change documents older than 10 years. 10 years is the legal time you need to keep a lot of data. Deletion is done via program RSCDOK99. If business does not want to delete, but keep the data in the archive, you can use data archiving object CHANGEDOCU. Retrieval of archived change documents is via transaction RSSCD100.
If you have large SYS_LOB tables, most likely these are occupied with attachments. Consider setup of SAP content server (see blog) and then migrate the documents from the SAP database to the content server (see blog).
To analyze SYS_LOB tables, follow the instructions in this dedicated blog.
You can schedule program RSAUPURG or program RSAU_FILE_ADMIN with the right variant to delete old Audit log data:
Before deleting audit log data, first agree with your security officer on the retention period. More on audit log in this blog.
Clean up of user role assignment data
If you have an older system, you will find that many users will have double roles assigned, or roles with validity dates in the past. This will lead to large amount of entries in table AGR_USERS. You can clean up by compressing this data with program PRGN_COMPRESS_TIMES. Read more in this blog.
Large WBCROSSGT table
Table WBCROSSGT is used to store the ABAP where used index. Might be large after upgrade. Use program RS_DEL_WBCROSSGT to delete and program SAPRSEUB to recreate the indexes.
For clean up of a solution manager system, read this dedicated blog.
Clean up for SAP Focused Run
For clean up of a SAP Focused Run system, read this dedicated blog.
Updating statistics
If you are running Oracle database it is wise to include in technical clean up job as last step the online reorganization of tables or indexes using program RSANAORA. See blog.
This blog will explain about getting insight into SAP database growth and controlling the growth.
Questions that will be answered are:
Do I have a database growth issue?
What are my largest tables?
How do I categorize my tables?
Why control database growth?
Controlling database growth has several reasons:
When converting to S/4 HANA you could end up with smaller physical HANA blade and need to buy less memory licenses from SAP
Less data storage leads to less costs (think also about production data copied back to acceptance, development and sandbox systems)
Back up / restore procedures are longer with large databases
Performance is better with smaller databases
Database growth
The most easy way to check if the database is growing too fast or not is using the Database Growth section in the SAP EWA (early watch alert). The EWA has both graphical and table representation for the growth:
You now have to determine if the growth is acceptable or not. This depends a bit on the usage of the system, amount of users, business data, and if you already stretched your infrastructure or not.
General rules of thumb:
1. Growth < 1 GB/month: do not spend time.
2. Growth > 1 GB/month and < 5 GB/month: implement technical clean up.
3. Growth > 5 GB/month: implement technical clean up and check for functional archiving opportunities.
Which are my largest tables?
To find the largest tables and indexes in your system start transaction DB02. In here select the option Space/Segments/Detailed Analysis and select all tables larger than 1 GB (or 1000 MB):
Then wait for the results and sort the results by size:
You can also download the full list.
Analysis of the large tables
Processing of the tables is usually done by starting with the largest tables first.
You can divide the tables in following categories:
Technical data: deletion and clean up can be done (logging you don’t want any more like some idoc types, application logging older than 2 years, etc): see blog on technical clean up
Technical data: archiving or storing can be done (idocs you must store, but don’t need fast access to, attachments)
In Oracle based systems, you might find large SYS_LOB tables. To analyze these, read this special blog.
SAP has a best practice document called “Data Management Guide for SAP Business Suite” or “DVM guide”. This document is updated every quarter to half year. The publication location is bit hidden by SAP under their DVM (data volume management) service. In the bottom here go to SAP support and open the How-to-guides section. Or search on google with the term “Data Management Guide for SAP Business Suite” (you might end up with a bit older version). The guide is giving you options per large table to delete and/or archive data.
Common technical objects
Most common technical tables you will come across:
EDIDC, EDIDS, EDI40: idocs
DBTABLOG: table changes
BALHDR, BALDAT: application logging
SWW* (all that start with SWW): workflow tables
SYS_LOB…..$$: attachments (office attachments and/or DB storage of attachments and/or GOS, global object services attachments)
Detailed table analysis for functional tables: TAANA tool
For detailed analysis on functional tables the TAANA (table analysis) tool can be used. Simply start transaction TAANA.
Now create a table analysis variant by giving the table name and selection of the analysis variant:
The default variant will only do a record count. Some tables (like BKPF in this example) come with a predefined ARCHIVE variant. This is most useful option. If this option does not fit your need, you can also push the create Ad Hoc Report button and define your own variant.
Caution: with the ad hoc variant select your fields with care, since the analysis will count all combinations of fields you select. Never select table key fields
Results of TAANA are visible after the TAANA batch job is finished.
By running the proper TAANA analysis for a large functional table you get insight into the distribution per year, company code, plant, document type etc. This will help you also estimate the benefits of archiving a specific object.
For TAANA improvement on dynamic subfields, please check this blog.
If you run on HANA, you can also use SE16H for the table analysis.
SAP data volume management via SAP solution manager
SAP is offering option to report on data volume management via SAP solution manager directly or as a subsection in the EWA. Experience so far with this: too long in setup, too buggy. The methods described above are much, much faster and you get insight into a matter of hours. The DVM setup will take you hours to do and days/weeks to wait for results…. TAANA and SE16H are way faster.
