As a SQL Server user, one of the most frustrating issues you may encounter is the “String or Binary Data Would be Truncated” error message. This error occurs when you try to insert a large amount of data into a table, and one or more of the values exceed the maximum length allowed for the column. In previous versions of SQL Server, this error message provided little information about which specific row or value caused the issue, making it difficult to troubleshoot and fix the problem.

Fortunately, SQL Server 2019 introduced improvements to this error message, providing more detailed information about the exact row and value that caused the truncation. This enhancement can save you a significant amount of time and frustration when dealing with large data imports.

Let’s take a look at an example to understand how this improvement works. In SQL Server 2016, if you try to insert a string that exceeds the maximum length of a column, you would receive the generic “String or Binary Data Would be Truncated” error message without any further details. However, in SQL Server 2019, the error message now includes the table name, column name, and the truncated value, allowing you to easily identify the problematic row.

For instance, if you attempt to insert a long string into a column with a maximum length of 10 characters, the error message in SQL Server 2019 would look like this:

Msg 2628, Level 16, State 6, Procedure ProcedureName, Line Linenumber
String or binary data would be truncated in table 'TableName', column 'ColumnName'.
Truncated value: 'TruncatedValue'.

This enhanced error message provides valuable information that can help you quickly identify and resolve the issue. By knowing the specific row and value that caused the truncation, you can easily locate and fix the problematic data.

It’s important to note that this improvement is not limited to SQL Server 2019. If you are using SQL Server 2016 SP2 CU 6 or SQL Server 2017 CU 12, you can enable a trace flag (460) to receive the enhanced error message.

Dealing with the “String or Binary Data Would be Truncated” error becomes even more critical when you are performing bulk data loads. In such cases, finding the problematic data manually can be a time-consuming and error-prone task.

Let’s consider an example where you need to load Oscar data from movies into a table. Assume you have a database with a table called “OscarScores” that captures the Oscar scores for various movies over the years. If you receive a large dataset to process, you may create a staging table to insert the data before merging it with the existing data.

Previously, if you encountered the truncation error during the bulk data load, you would have to search through the entire dataset to find the problematic row and value. However, with the enhanced error message in SQL Server 2019, you can easily identify the specific row and value that caused the truncation.

For example, if the “film” column in the “OscarScores” table has a maximum length of 30 characters, and you try to insert a movie title that exceeds this limit, the error message would provide the necessary details:

Msg 2628, Level 16, State 1, Line 23
String or binary data would be truncated in table 'sandbox.dbo.OscarScores', column 'film'.
Truncated value: 'TruncatedValue'.

With this information, you can quickly locate the offending row and correct the data to ensure a successful data import.

In summary, the “String or Binary Data Would be Truncated” error message can be a frustrating obstacle when importing data into SQL Server. However, the enhanced error message introduced in SQL Server 2019 (and available in SQL Server 2016 SP2 CU 6 and SQL Server 2017 CU 12 with a trace flag) provides valuable information that simplifies troubleshooting and resolution. By knowing the specific row and value that caused the truncation, you can quickly identify and fix the problematic data, saving time and effort in the process.

Remember, keeping your SQL Server up to date with the latest patches is essential to take advantage of these improvements and ensure a smooth data import experience.