QuestDB: Double Quotes Bug In Calculated Columns Naming

Introduction

In this article, we will delve into a peculiar issue encountered in QuestDB concerning the inconsistent naming behavior of calculated columns when double quotes are involved. This issue was brought to light by a user, Super Richmann, who faced challenges while integrating QuestDB with .NET NpgSql 9.0.2 for ML.NET AutoML experiments. Understanding this behavior is crucial for users who rely on calculated columns and need consistent naming conventions for seamless integration with other tools and libraries. Let's explore the details of the problem, the steps to reproduce it, and the implications it has on real-world use cases.

The Problem: Inconsistent Naming with Double Quotes

The core of the issue lies in how QuestDB handles double quotes when naming calculated columns. Specifically, the naming convention appears inconsistent when performing calculations on columns, especially when decimals are involved. This inconsistency can lead to significant problems when integrating QuestDB with other tools that rely on precise column name matching, such as ML.NET's AutoML functionality. Let's break down the specific scenarios where this behavior manifests.

When working with calculated columns in QuestDB, users expect the output column name to mirror the input column text or the alias provided. However, this isn't always the case, particularly when double quotes are involved. The inconsistency arises in scenarios where mathematical operations are performed on columns, and the output column name should reflect the calculation. For instance, dividing a column by a simple integer might yield an expected output name, but dividing by a decimal number can produce a different result, often including double quotes in unexpected places. This discrepancy can be a major roadblock for developers who need predictable and consistent column naming for their applications.

Steps to Reproduce the Issue

To demonstrate this inconsistent behavior, Super Richmann provided a clear set of steps that can be replicated on the QuestDB demo instance. By following these steps, anyone can observe the issue firsthand and understand the nuances of the problem.

1. Access the QuestDB demo instance.
2. Execute the following query: SELECT indicator2 / 2 from core_price limit 0
   • Observe that the output column naming convention is exactly identical to the input column text indicator2 / 2. This is the expected behavior.
3. Next, execute this query: SELECT indicator2/0.1289543 from core_price limit 0
   • Notice that the output column naming convention is not identical to the input column text "indicator2 / 2.314". This demonstrates the inconsistency.
4. Finally, run the following query to see another variation of the issue: SELECT indicator2 / 2.314 as 'indicator2 / 2.314' from core_price limit 0
   • Observe the output and note the unexpected behavior in column naming.

These steps clearly illustrate that the presence of decimals in the calculation and the use of aliases with single quotes can lead to inconsistent and unexpected column naming conventions in QuestDB. This inconsistency can have significant implications for users integrating QuestDB with other tools and libraries.

Impact on Real-World Use Cases

The inconsistent naming behavior described above isn't just a minor annoyance; it can have significant repercussions for real-world applications, particularly those involving data science and machine learning workflows. Super Richmann highlighted a specific use case where this issue renders their current workflow impossible.

The primary challenge arises when using QuestDB with .NET NpgSql 9.0.2 in conjunction with ML.NET AutoML. ML.NET's AutoML functionality is designed to automate the process of building machine learning models. It includes a CreateDatabaseLoader function, which is crucial for loading data from databases. This function requires that the column names specified in the SQL query match the output column names exactly. This strict requirement ensures that the data is correctly mapped to the model's input features.

When calculated columns in QuestDB produce output names with unexpected double quotes, it becomes impossible to satisfy ML.NET's requirement for exact column name matching. The SQL query might specify a calculation like indicator2 / 2.314, but the output column name could be "indicator2 / 2.314" or some other variation. This mismatch prevents CreateDatabaseLoader from correctly mapping the data, effectively blocking the use of AutoML experiments. In essence, the inconsistent naming behavior in QuestDB makes it impossible to leverage ML.NET AutoML for datasets that require calculated columns.

This issue underscores the importance of consistent and predictable naming conventions in database systems, especially when those systems are integrated into complex data pipelines and machine learning workflows. The ability to rely on exact column names is crucial for ensuring that data is processed correctly and that automated tools like AutoML can function as intended. Addressing this inconsistency in QuestDB is essential for enabling seamless integration with tools like ML.NET and for supporting a wide range of data-driven applications.

Technical Details and Context

To fully understand the issue, it's essential to consider the technical context in which it occurs. Super Richmann reported this behavior on QuestDB version 9.2.1, running on the Cloud Demo instance. This context is important because it helps narrow down the potential causes of the bug and provides a specific environment for testing and verification.

The fact that the issue was observed on the Cloud Demo instance suggests that it is not specific to a particular operating system or file system configuration. The Cloud Demo provides a standardized environment, which means the bug is likely related to the core logic of QuestDB's query processing and column naming mechanisms. This makes it more likely that the issue is a software bug rather than a configuration problem.

Super Richmann also confirmed that they had followed the necessary Linux and macOS kernel configuration steps to increase the maximum open files and maximum virtual memory areas limits. This detail is important because it rules out the possibility that the issue is caused by resource constraints or misconfiguration of the operating system. By ensuring that the system is properly configured, Super Richmann has effectively eliminated a common source of problems and focused attention on the core issue within QuestDB.

The specific QuestDB version (9.2.1) is also relevant. Knowing the version helps developers and other users determine whether the bug has been addressed in later releases or if it is still present. It also allows for targeted testing and debugging efforts, as the version number provides a specific codebase to examine.

Suggested Solutions and Workarounds

While a definitive solution to this issue requires a fix within QuestDB itself, there are a few potential workarounds that users can employ in the meantime. These workarounds may not be ideal for all situations, but they can help mitigate the problem and allow users to continue working with calculated columns in QuestDB.

One possible workaround is to avoid using decimals in calculations within the SQL query. If the calculations can be performed using integers or other data types that do not trigger the inconsistent naming behavior, the issue can be circumvented. However, this approach may not be feasible for all use cases, particularly those that require precise decimal calculations.

Another potential workaround is to perform the calculations outside of QuestDB, either in the application code or in a separate data processing step. By fetching the raw data from QuestDB and performing the calculations elsewhere, users can control the naming of the resulting columns and ensure consistency. This approach adds complexity to the data processing pipeline but can provide a reliable way to avoid the naming issue.

A more direct workaround involves post-processing the column names after the query is executed. This can be done programmatically, by iterating through the column names and removing any unwanted double quotes or other characters. This approach requires additional code but can be effective in ensuring that the column names match the expectations of other tools and libraries.

It's important to note that these workarounds are temporary measures and should not be considered permanent solutions. The ideal resolution is for QuestDB to address the underlying issue and provide a consistent naming convention for calculated columns. In the meantime, these workarounds can help users continue their work and minimize the impact of the bug.

Conclusion

The inconsistent naming behavior of calculated columns in QuestDB, particularly when double quotes are involved, presents a significant challenge for users integrating QuestDB with other tools and libraries. The issue, as highlighted by Super Richmann, can prevent the seamless use of ML.NET AutoML, hindering the development of machine learning models. Understanding the steps to reproduce the issue, its impact on real-world use cases, and the technical context in which it occurs is crucial for both users and developers.

While workarounds can help mitigate the problem in the short term, a permanent solution requires a fix within QuestDB itself. Addressing this inconsistency will ensure that QuestDB remains a reliable and versatile tool for a wide range of data-driven applications. Consistent naming conventions are essential for smooth data processing and integration, and resolving this issue will greatly enhance the user experience.

For further information on QuestDB and its features, you can visit the official QuestDB website. This resource provides comprehensive documentation, tutorials, and community support to help you make the most of QuestDB's capabilities.