Error
Error Code:
359
SAP S/4HANA Error 359: SQL String Length Exceeded
Description
This error indicates that an operation attempted to process or store a string of characters that exceeded the maximum allowed length in the underlying SAP S/4HANA database. It typically occurs during data entry, system integrations, or custom report execution.
Error Message
ERR_SQL_STR_LENGTH_TOO_LARGE
Known Causes
4 known causesExceeding Input Field Limits
A user attempts to enter data into an SAP S/4HANA field that has a defined maximum character limit, which the input exceeds.
Data Migration/Integration Discrepancy
During data import or integration, source system strings are longer than the corresponding target field lengths in SAP S/4HANA.
Custom Code or Query Generation
Custom reports, interfaces, or extensions generate SQL statements or parameters exceeding the database's maximum string length.
Database Configuration Constraints
The underlying database or application server has configured string length limits that are too restrictive for certain SAP S/4HANA operations.
Solutions
3 solutions available1. Optimize ABAP Code Generating Long SQL Statements advanced
Analyze and refactor ABAP programs that construct excessively long SQL queries.
1
Identify the ABAP program and statement causing the error. This often requires debugging the ABAP code and examining the generated SQL string.
2
Use transaction ST05 (SQL Trace) to capture SQL statements executed by the problematic program. Filter the trace by the program name and look for the long SQL string.
3
Examine the ABAP code to understand how the SQL string is being built. Look for patterns like concatenating many literals, large internal tables, or complex dynamic SQL generation.
4
Refactor the ABAP code to simplify the SQL query. This might involve:
5
Breaking down a large query into smaller, more manageable ones.
6
Using joins more effectively instead of multiple subqueries.
7
Reducing the number of selected fields or WHERE clause conditions if they are not strictly necessary.
8
Re-evaluating the use of dynamic SQL. If possible, use static SQL.
9
Consider using newer ABAP features like CDS views or Open SQL enhancements that might offer more efficient ways to express complex logic.
10
Thoroughly test the refactored ABAP code to ensure it produces the correct results and no longer triggers the error.
2. Review and Adjust Database Parameters (Less Common for S/4HANA) medium
While less common in S/4HANA due to its optimized architecture, review relevant database parameters if extensive custom development is suspected.
1
Identify the underlying database system (e.g., SAP HANA).
2
Consult SAP Notes and database documentation for parameters related to SQL statement length limits or buffer sizes. For SAP HANA, parameters like `max_sql_statement_length` are generally not configurable in a way that would cause this specific error for typical S/4HANA operations. This error is more indicative of an application-level issue.
3
If a specific parameter is identified (highly unlikely for this error in S/4HANA), follow the recommended procedure for adjusting it. This usually involves modifying the database configuration file and restarting the database instance. **Caution:** Modifying database parameters without a clear understanding of their impact can lead to system instability.
4
The primary focus for ERR_SQL_STR_LENGTH_TOO_LARGE in S/4HANA should always be on optimizing the ABAP code that generates the SQL.
3. Analyze and Optimize Data Loading/Migration Scripts medium
Address long SQL statements generated by custom data loading or migration tools.
1
If the error occurs during a data load or migration process, examine the scripts or tools being used. These often involve generating large `INSERT` or `UPDATE` statements.
2
Look for methods that generate single, very large SQL statements for inserting or updating many records. For example, a script might be constructing one giant `INSERT INTO table (col1, col2) VALUES (val1a, val2a), (val1b, val2b), ...` statement.
3
Modify the script to process data in smaller batches. Instead of one massive statement, generate multiple statements, each handling a reasonable number of records.
Example (Conceptual Python for batching):4
For example, if inserting data, instead of one giant INSERT statement, use a loop to create smaller INSERT statements for chunks of data.
import pyodbc
db_connection = pyodbc.connect('DRIVER={ODBC Driver 17 for SQL Server};SERVER=your_server;DATABASE=your_db;UID=your_user;PWD=your_password')
cursor = db_connection.cursor()
data_to_insert = [...] # your list of data rows
batch_size = 1000 # Adjust as needed
for i in range(0, len(data_to_insert), batch_size):
batch = data_to_insert[i:i + batch_size]
# Construct and execute INSERT statement for the 'batch'
# This will involve building the SQL string for the current batch
# Example: sql = "INSERT INTO your_table (col1, col2) VALUES (?, ?)"
# cursor.executemany(sql, batch)
# db_connection.commit()
print(f"Processing batch {i // batch_size + 1}")
db_connection.close()5
For SAP Data Services or other ETL tools, review the transformation jobs and ensure they are configured to handle data in appropriate chunks or use efficient bulk loading mechanisms.
6
Test the modified scripts thoroughly to confirm data integrity and performance.