Understanding BigQuery’s ASSERT Statement and EU Location Limitations

Introduction

BigQuery, a fully-managed enterprise data warehouse service by Google Cloud, recently introduced the new ASSERT statement in its July 13th, 2020 release notes. This feature allows users to validate certain conditions within their queries, providing additional assurance that their datasets are accurate and consistent. However, some users have encountered an issue with this feature when using EU located data, leading to unexpected errors.

In this article, we will delve into the details of BigQuery’s ASSERT statement, its usage, and the limitations imposed by EU location. We will also explore potential workarounds and the current status of this feature in BigQuery.

What is BigQuery’s ASSERT Statement?

BigQuery’s ASSERT statement is a new query element that allows users to specify a condition or assertion that must be true for the query results to be returned. This can include conditions based on aggregate functions, array operations, or even simple arithmetic expressions. The ASSERT statement provides an additional layer of validation and error checking, helping to ensure data quality and accuracy.

Here is a basic example of how to use the ASSERT statement in BigQuery:

SELECT ASSERT(true = true) AS 'Assertion Result'

In this example, the assertion true = true will always evaluate to true, making the entire query result return true.

Using ASSERT with Aggregate Functions

BigQuery’s ASSERT statement can also be used in conjunction with aggregate functions, such as SUM, COUNT, or AVG. For instance:

SELECT SUM(x) AS total_sum
FROM dataset.inputs
ASSERT(SUM(x) > 10)

In this example, the query will only return results if the sum of x is greater than 10.

EU Location Limitations

However, when we tried to use the ASSERT statement with EU located data, we encountered an unexpected error:

SELECT ASSERT(COUNT(*) > 0) AS 'Assertion Result'
FROM dataset_eu.inputs

This query resulted in a “Unsupported statement ASSERT” error.

We also attempted to include the project prefix in our query, but still received the same error:

SELECT ASSERT(COUNT(*) > 0) AS 'Assertion Result'
FROM myproject.dataset_eu.inputs

Potential Workarounds and Limitations

There are a few potential workarounds for this limitation:

Use a different region: One possible workaround is to use a US located dataset instead of an EU one. This would eliminate the EU location limitation on the ASSERT statement.
Contact Google Support: Another option is to reach out to Google Support and report the issue. They may be able to provide additional guidance or resolve the problem on your behalf.

However, without further information from BigQuery about this limitation, it’s difficult to determine whether these workarounds are truly effective or if there’s an underlying bug in the ASSERT statement that needs to be addressed.

Conclusion

BigQuery’s ASSERT statement is a powerful tool for validating query results and ensuring data quality. However, its use is limited by EU location constraints, at least for now. While we have found some potential workarounds, more information is needed to fully understand this limitation and whether it will be resolved in future updates.

In the meantime, users can consider using alternative validation mechanisms or switching to a US located dataset if they need to utilize the ASSERT statement with EU located data.

Troubleshooting: Querying with Different Processing Locations

To further illustrate the issue with querying with different processing locations, let’s execute the following query:

ASSERT TRUE

This simple query should always return true, but when executed with a different processing location, it may fail due to the EU region limitation on the ASSERT statement.

Final Thoughts and Next Steps

We hope this article has provided you with a better understanding of BigQuery’s ASSERT statement and its limitations. If you have any questions or comments regarding this feature or potential workarounds, we encourage you to share them in our comments section below.

In the future, we will continue to monitor this issue and provide updates as more information becomes available from BigQuery.

Additional References

API Documentation and Reference Materials

For more information on BigQuery’s API documentation and reference materials, please refer to the following resources:

Last modified on 2024-10-29