Enterprise Resource Planning Blogs by Members
Gain new perspectives and knowledge about enterprise resource planning in blog posts from community members. Share your own comments and ERP insights today!
cancel
Showing results for 
Search instead for 
Did you mean: 
wojciech_lukowski
Discoverer
0 Kudos

With SAP HANA we received a revolutionary improvement in database performance. Complex analytical queries can now be executed in seconds on line item data. Therefore storing pre-calculated materialized aggregates can now be avoided. The analytics are now more flexible and fully line item based.

In the past historical items used to be archived. Removing them from the system made them practically unusable for any bulk operations. With SAP HANA this could no longer be the case. Without all sorts of totals tables we need the item data available in the system much longer. So instead of archiving we now use multi-temperature data strategy i.e. data aging.

In case you were wondering how data aging is implemented in S/4HANA, check out the new SAP Press book Data Aging for SAP Business Suite on SAP HANA (https://www.sap-press.com/data-aging-for-sap-business-suite-on-sap-hana_4041/).

You will get a chance to learn the concept of data temperature – what is still hot and what is not. All the steps that are happening behind the scenes when aging is triggered are explained based on the example scenario of accounting documents in SAP S/4HANA Finance. You will see what the extensibility options are, how to develop you own aging objects as well as step by step instructions on how to configure, execute and monitor data aging. If basic troubleshooting doesn’t work, you will see where and how to set breakpoints for debugging.

The hot way of dealing with cold data!

Contents:

  1. Introduction to Data Aging
    1. In-Memory Databases versus Traditional Databases
    2. What Is Data Temperature?
    3. Introduction to Data Aging in SAP S/4HANA Finance
  2. Data Aging Building Blocks for Accounting Documents in SAP S/4HANA Finance
    1. Object Definition
    2. Object Methods
      1. CONSTRUCTOR
      2. INIT
      3. PROCESS
    3. Enhancement Spots
      1. Check
      2. Update
    4. Analysis Program
  3. Configuring Data Aging
    1. Setting up the Basis Layer
      1. Activating DAAG_DATA_AGING
      2. Setting up Data Aging Authorizations
    2. Setting up Partitions
      1. Customizing for Partitioning
      2. Creating Partitions
      3. Executing Partitioning
      4. Deleting the Others Partition
      5. Controlling Partitions Programmatically
    3. Activating the Data Aging Object
    4. Applying Application-Specific Customizing
      1. Defining Life for Document Types
      2. Defining Life for Account Types
      3. Customizing Data Aging Job Parameters
  4. Managing Data Aging
    1. Executing Data Aging Runs
      1. Analysis Run
      2. Update Run
    2. Monitoring Data Aging and Analyzing Logs
      1. Data Aging Job Log
      2. Data Aging Run Log
    3. Accessing Cold Data
      1. Accounting Document Temperature: Clearing versus Posting Date
      2. Account Balance Calculation in SAP S/4HANA Finance
  5. Debugging Data Aging

The e-bite is based on SAP_FIN 720 SPS01. Below are some updates to the aging process of FI documents released most recently:

  • as of SPS03 the FI_DOCUMENT object does not just age the FI document, but also the entire journal entry (ACDOCA). For lower SPS level implement the note 2178388 (latest version available since September this year). For this reason, three new AMDPs are called when determining the list of keys of the accounting documents to be moved to cold storage (FI_DOCUMENT_ML_CHECK, FI_DOCUMENT_AA_CHECK, FI_DOCUMENT_CO_CHECK). As a result, additional un-aging reason codes can be raised:
    • 600 for ML relevant postings with existing and not archived ML header,
    • 601 for AA relevant postings with asset under construction,
    • 602 for CO relevant postings which are not archived (excluding CO-PA and KS/KL postings).

For more information, see SAP Note 2190848 - FAQ - Aging for Journal Entry in SAP Simple Finance.

  • FAGLFLEXA is replaced with ACDOCA also for data aging. The old data remaining in obsolete tables can be removed from memory by report FINS_MIG_OBSOLETE_DB_DEL (see note 2190137). Data from obsolete tables is copied to shadow tables and deleted in original tables. When copying data to shadow tables the report sets the "_DATAAGING" column with a fixed date of 2000-01-01 causing all records end up in cold partitions.
  • The runtime class of the data aging object implements now the interface IF_DAAG_RUNTIME_PARALLEL.
Labels in this area