How To Fix UCLP061 - Overflow in operation COLLECT in data record summarization

UCLP061 - Overview

• Message type: E = Error

• Message class: UCLP - Messages for List Processor

• Message number: 061

• Message text: Overflow in operation COLLECT in data record summarization

What causes this issue?

During operation "COLLECT" an overflow occurs in a numeric field of
data structure &V1&.
It is possible that a characteristic field of structure &V1& has a
numeric data type. The list processor allows numeric data types only
for key figures.

System Response

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

How to fix this error?

In the table structure, check if all characteristics have a <ZH>non
</>-numeric data type.
If the summation has an error, insert an additional characteristic with
data type "C" (character) and make sure it contains a text copy of the
value of the original characteristic. Then replace the original
characteristic in the control table with the new characteristic.

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 UCLP061 - Overflow in operation COLLECT in data record summarization ?

  The SAP error message UCLP061, which indicates an "Overflow in operation COLLECT in data record summarization," typically occurs during the summarization of data records in SAP systems. This error is related to the COLLECT statement in ABAP, which is used to aggregate data into internal tables. When the data being processed exceeds the limits of the data type or the internal table structure, an overflow error can occur.
  Causes:
  
  Data Type Limitations: The data being summarized may exceed the maximum value that can be stored in the defined data type (e.g., integer, decimal).
  Internal Table Size: The internal table used for summarization may not be able to accommodate the number of records or the size of the data being processed.
  Incorrect Data Handling: There may be issues with how data is being collected or aggregated, such as incorrect initialization or handling of the data records.
  
  Solutions:
  
  Check Data Types: Review the data types used in your