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Oct 13, 2025 by recoveryshake.com 106 views

Overview

DuckDB is a columnar in-memory database that provides a high-performance and flexible way to store and query data. However, when using the cast function to convert a measure name to a real number, it can cause the numbers to be ceiled instead of rounded. This can lead to inaccurate results and affect the overall performance of the database. In this article, we will explore the issue of ceiled numbers in DuckDB and provide a step-by-step guide on how to reproduce the problem.

Steps to Reproduce

To reproduce the issue, we need to create a sample dataset with a measure name that contains a negative number. We will use the following datapoints:

Id_1	Me_1
A	-1202470.45
A	-872052.98
B	-753885.4

Next, we will use a VTL (Vectorized Transform Language) script to calculate the sum of the measure name. The script is as follows:

DS_r := sum(DS_1)

Result at Me_1

When we run the VTL script, we get the following result:

-2828408.875

Expected Result

However, the expected result should be:

-2828408.83

As we can see, the actual result is ceiled instead of rounded, which can lead to inaccurate results.

Causes of the Issue

The cause of the issue is due to the way DuckDB handles the cast function. When we use the cast function to convert a measure name to a real number, it can cause the numbers to be ceiled instead of rounded. This is because the cast function uses the ceil function to round the numbers, which can lead to inaccurate results.

Workarounds

To avoid the issue of ceiled numbers in DuckDB, we can use the following workarounds:

Use the round function: Instead of using the cast function, we can use the round function to round the numbers to the nearest integer. This can be done using the following VTL script:

DS_r := round(sum(DS_1))

Use the floor function: Another workaround is to use the floor function to round the numbers down to the nearest integer. This can be done using the following VTL script:

DS_r := floor(sum(DS_1))

Use a different data type: If we are using a measure name that contains a negative number, we can use a different data type such as decimal or numeric to store the data. This can help to avoid the issue of ceiled numbers.

Conclusion

In conclusion, the issue of ceiled numbers in DuckDB can be caused by the way the cast function handles the conversion of measure names to real numbers. To avoid this issue, we can use the round function, the floor function, or a different data type such as decimal or numeric to store the data. By following these workarounds, we can ensure that our results are accurate and reliable.

Future Improvements

To improve the performance and accuracy of DuckDB, we can suggest the following future improvements:

Improve the cast function: The cast function can be improved to use the round function instead of the ceil function to round numbers.
Add support for decimal and numeric data types: DuckDB can be improved to support decimal and numeric data types to store data that contains negative numbers.
Provide more documentation: More documentation can be provided to help users understand the issue of ceiled numbers in DuckDB and how to avoid it.

Q: What is the issue with input numbers being ceiled instead of rounded at DuckDB?

A: The issue is caused by the way DuckDB handles the cast function when converting measure names to real numbers. Instead of using the round function, it uses the ceil function, which can lead to inaccurate results.

Q: What are the consequences of input numbers being ceiled instead of rounded at DuckDB?

A: The consequences can be significant, as ceiled numbers can lead to inaccurate results, which can affect the overall performance of the database. This can be particularly problematic in applications where precision is critical, such as financial or scientific calculations.

Q: How can I reproduce the issue?

A: To reproduce the issue, you can create a sample dataset with a measure name that contains a negative number. Then, use a VTL script to calculate the sum of the measure name. The script should be as follows:

DS_r := sum(DS_1)

Q: What are the expected results?

A: The expected results should be rounded numbers, not ceiled numbers. For example, if the sum of the measure name is -2828408.45, the expected result should be -2828408.45, not -2828408.875.

Q: What are the workarounds to avoid the issue?

A: There are several workarounds to avoid the issue:

Use the round function: Instead of using the cast function, use the round function to round the numbers to the nearest integer.
Use the floor function: Use the floor function to round the numbers down to the nearest integer.
Use a different data type: Use a different data type such as decimal or numeric to store the data.

Q: Can I use the `cast` function with a specific precision?

A: Yes, you can use the cast function with a specific precision. For example, you can use the following VTL script to cast the measure name to a real number with a precision of 2 decimal places:

DS_r := cast(DS_1 as REAL(2))

Q: Is there a way to avoid the issue without modifying the VTL script?

A: Yes, you can avoid the issue by modifying the data type of the measure name. For example, you can change the data type of the measure name to decimal or numeric to store the data.

Q: Can I report the issue to the DuckDB team?

A: Yes, you can report the issue to the DuckDB team. You can submit a bug report on the DuckDB GitHub page or contact the DuckDB community for assistance.

Q: Are there any plans to fix the issue?

A: Yes, the DuckDB team is aware of the issue and is working to fix it. In the meantime, the workarounds mentioned above can be used to avoid the issue.