How To Fix FMFG029 - &1 duplicate lines updated on the FACTS II Extract File

FMFG029 - Overview

• Message type: E = Error

• Message class: FMFG - U.S. Federal Government Message Class

• Message number: 029

• Message text: &1 duplicate lines updated on the FACTS II Extract File

What causes this issue?

The FACTS II extract program extracts data from special ledger 97 in
table group FMUSFGFACTS2 and places it in table FMFGF2EXT to be used by
the other FACTS II programs.
Table FMFGF2EXT contains only a single record for each "Bulk Key". The
extract program updates any duplicate records on the database table.

System Response

The system tells you how many records are dropped. This is the number
of records updated on the FACTS II Bulk Extract File.

How to fix this error?

The system issues an error message and will not allow you to continue with this transaction until the error is resolved.

Procedure for System Administrators

Error message extract from SAP system. Copyright SAP SE.

Smart SAP Assistant

• What is the cause and solution for SAP error message FMFG029 - &1 duplicate lines updated on the FACTS II Extract File ?

  The SAP error message FMFG029 indicates that there are duplicate lines in the FACTS II Extract File. This error typically arises during the extraction or processing of data when the system detects that the same record or line is being processed more than once, which can lead to inconsistencies in the data being extracted.
  
  Cause:
  
  Duplicate Data Entries: The most common cause is that the source data contains duplicate entries. This could be due to data entry errors, system integration issues, or incorrect data processing logic.
  
  Configuration Issues: There may be issues with the configuration of the extraction process that allow duplicates to be generated.
  Data Processing Logic: The logic used to compile the extract file may not adequately handle unique records, leading to duplicates being included.
  
  
  Solution:
  
  Identify Duplicates: Review the source data to identify the duplicate entries. This can often be done using SQL queries or data analysis tools to find records with the