LINQ to SQL
SQL Server Compact Edition
Exception Handling
Row not found or changed
Database Errors

What can I do to resolve a Row not found or changed Exception in LINQ to SQL on a SQL Server Compact Edition Database?

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When working with LINQ to SQL on a SQL Server Compact Edition (SQL CE) database, you may occasionally encounter the "Row not found or changed" exception. This exception typically occurs under concurrency issues when the row you're trying to update or delete has been modified or doesn't exist at the expected time during the operation.

Understanding the root cause and implementing a solution is crucial for maintaining data consistency and application stability. Below is a comprehensive look at strategies and technical explanations to resolve this issue.

Understanding the Exception

Cause of the Exception

In SQL CE, a LINQ to SQL operation might fail if:

  • The row has been modified in the database since it was loaded into memory.
  • The row has been deleted from the database since it was loaded.
  • The underlying data structure in the table has changed, such as column types or constraints.

How LINQ to SQL Detects Changes

LINQ to SQL uses an Original and Current version of the entity to determine whether a row has been changed:

  • Original: Represents the state of the entity when it was first retrieved from the database.
  • Current: Represents the current state of the entity since it has been loaded.

When an update occurs, LINQ to SQL checks if the Original version still matches the data in the database. If not, it raises a "Row not found or changed" exception.

Strategies for Resolution

1. Handling Concurrency with a Timestamp Column

A typical resolution is to implement optimistic concurrency control using a timestamp column. Here's how you can achieve this:

  1. Add a Timestamp Column:
    Ensure that your table has a timestamp or rowversion column. This column automatically updates whenever a row is modified.
  • Transactional Updates: Use transactions for batch updates to maintain atomic operations.
  • User Notifications: Notify users when data updates were unsuccessful due to concurrency issues, allowing them to retry or make informed decisions.
  • Error Logging: Implement comprehensive error logging to capture details about conflicting operations for future diagnosis.

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