SAP ABAP Data Element CNV_10020_FILL_METHOD (Filling method)
Hierarchy
☛ DMIS (Software Component) DMIS 2011_1
   ⤷ CA-GTF-BS (Application Component) Business Application Support
     ⤷ CNV_10020 (Package) CNV package 10020
Basic Data
Data Element CNV_10020_FILL_METHOD
Short Description Filling method  
Data Type
Category of Dictionary Type D   Domain
Type of Object Referenced     No Information
Domain / Name of Reference Type CNV_10020_FILL_METHOD    
Data Type CHAR   Character String 
Length 1    
Decimal Places 0    
Output Length 1    
Value Table      
Further Characteristics
Search Help: Name    
Search Help: Parameters    
Parameter ID   
Default Component name    
Change document    
No Input History    
Basic direction is set to LTR    
No BIDI Filtering    
Field Label
  Length  Field Label  
Short 10 FillM 
Medium 15 Filling method 
Long 20 Filling method 
Heading 6 FillM 
Documentation

Definition

There are the following ways of filling the object tables using a determination path. These options apply for determination using an automatically defined determination routine.

  1. Read data completely, process and store at the end
    All relationships between the determination values are read and made available to package 10020 in an internal table.
    Package 10020 sorts the data if necessary, deletes duplicate entries and does a relevance check if necessary. Finally, it stores the data in the database.


    Use case: Paths for which you do not expect large amounts of data. The more data you have, the more main memory is needed, which also means that sorting operations are more expensive.

  2. Read and process data completely, store at the end
    All relationships between the determination values are read, and each record is stored in an internal table in sorted form. This internal table is then made available to package 10020.
    Package 10020 does a relevance check if required and stores the data in the database.


    Use case: If you need to read large volumes of data and expect a large number of duplicate entries, 'Sort by insert' is the best strategy: For one thing, the program does not keep all the data in the main memory, but only the subset containing the non-duplicate entries. For another, the program does not have to write data with 'accept duplicate records'.
    Because of the implicit sorting, this approach is particularly useful for writing to the cluster. On the other hand, you do not always have to sort the data before writing it to transparent object tables, which results in performance losses.

  3. Read, process and store data package-by-package
    The program stores only a limited number of relationships between determination values in an internal table, makes a relevance check if necessary and then stores the data in the database. Then the internal table is emptied, and the next data package is read, until all data has been processed completely.
    Note: Because not all of the data is available at the time when the writing takes place, duplicate entries can only be deleted in the context of the current data package. You need to eliminate identical records that occur in different data packages by setting the indicator for duplicate entries when the data is written to transparent object tables. However this can lead to performance issues. When writing to the cluster, you do not have to eliminate duplicate data across packages, but you get larger volumes of data.

    Use case: If you need to read large volumes of data and do not expect any duplicate entries, you can use processing by packages to minimize the main memory requirements of the internal table. However the data cannot be stored in sorted form, which is a substantial drawback when you work with the cluster.

Notes

If you use specific function modules and/or routines for determination, keep in mind that your corresponding programs should support all approaches outlined above.
If you want to support only one of the approaches, make sure that it is stored as a path parameter, because otherwise package 10020 may do some unnecessary subsequent processing.

History
Last changed by/on SAP  20141030 
SAP Release Created in