DQX Test Failure Analysis: `test_installation_stores_install_state_keys` And Node Type Issues

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Understanding the Test Failure

This article delves into the recent test failure encountered during the nightly build of the Databricks Quality Explorer (DQX), specifically the test_installation_stores_install_state_keys test. This failure, categorized under databrickslabs and dqx, highlights an issue related to unsupported node types during the installation process. Understanding the root cause of this failure is crucial for maintaining the stability and reliability of DQX.

The Error Message: A Deep Dive into Node Type Incompatibility

The core of the problem lies within the error message:

databricks.sdk.errors.platform.InvalidParameterValue: Node type Standard_D4ads_v6 is not supported. Supported node types: Standard_DS3_v2, Standard_DS4_v2, Standard_DS5_v2, Standard_D4s_v3, Standard_D8s_v3, Standard_D16s_v3, Standard_D32s_v3, Standard_D64s_v3, Standard_D4a_v4, Standard_D8a_v4, Standard_D16a_v4, Standard_D32a_v4, Standard_D48a_v4, Standard_D64a_v4, Standard_D96a_v4, Standard_D8as_v4, Standard_D16as_v4, Standard_D32as_v4, Standard_D48as_v4, Standard_D64as_v4, Standard_D96as_v4, Standard_D4ds_v4, Standard_D8ds_v4, Standard_D16ds_v4, Standard_D32ds_v4, Standard_D48ds_v4, Standard_D64ds_v4, Standard_D3_v2, Standard_D4_v2, Standard_D5_v2, Standard_D8_v3, Standard_D16_v3, Standard_D32_v3, Standard_D64_v3, Standard_D4s_v5, Standard_D8s_v5, Standard_D16s_v5, Standard_D32s_v5, Standard_D48s_v5, Standard_D64s_v5, Standard_D96s_v5, Standard_D4ds_v5, Standard_D8ds_v5, Standard_D16ds_v5, Standard_D32ds_v5, Standard_D48ds_v5, Standard_D64ds_v5, Standard_D96ds_v5, Standard_D4as_v5, Standard_D8as_v5, Standard_D16as_v5, Standard_D32as_v5, Standard_D48as_v5, Standard_D64as_v5, Standard_D96as_v5, Standard_D4ads_v5, Standard_D8ads_v5, Standard_D16ads_v5, Standard_D32ads_v5, Standard_D48ads_v5, Standard_D64ads_v5, Standard_D96ads_v5, Standard_D4d_v4, Standard_D8d_v4, Standard_D16d_v4, Standard_D32d_v4, Standard_D48d_v4, Standard_D64d_v4, Standard_D12_v2, Standard_D13_v2, Standard_D14_v2, Standard_D15_v2, Standard_DS12_v2, Standard_DS13_v2, Standard_DS14_v2, Standard_DS15_v2, Standard_E8_v3, Standard_E16_v3, Standard_E32_v3, Standard_E64_v3, Standard_E8s_v3, Standard_E16s_v3, Standard_E32s_v3, Standard_E64s_v3, Standard_E4d_v4, Standard_E8d_v4, Standard_E16d_v4, Standard_E20d_v4, Standard_E32d_v4, Standard_E48d_v4, Standard_E64d_v4, Standard_E4ds_v4, Standard_E8ds_v4, Standard_E16ds_v4, Standard_E20ds_v4, Standard_E32ds_v4, Standard_E48ds_v4, Standard_E64ds_v4, Standard_E80ids_v4, Standard_E4a_v4, Standard_E8a_v4, Standard_E16a_v4, Standard_E20a_v4, Standard_E32a_v4, Standard_E48a_v4, Standard_E64a_v4, Standard_E96a_v4, Standard_E4as_v4, Standard_E8as_v4, Standard_E16as_v4, Standard_E20as_v4, Standard_E32as_v4, Standard_E48as_v4, Standard_E64as_v4, Standard_E96as_v4, Standard_E4s_v4, Standard_E8s_v4, Standard_E16s_v4, Standard_E20s_v4, Standard_E32s_v4, Standard_E48s_v4, Standard_E64s_v4, Standard_E80is_v4, Standard_E4s_v5, Standard_E8s_v5, Standard_E16s_v5, Standard_E20s_v5, Standard_E32s_v5, Standard_E48s_v5, Standard_E64s_v5, Standard_E96s_v5, Standard_E4ds_v5, Standard_E8ds_v5, Standard_E16ds_v5, Standard_E20ds_v5, Standard_E32ds_v5, Standard_E48ds_v5, Standard_E64ds_v5, Standard_E96ds_v5, Standard_E4as_v5, Standard_E8as_v5, Standard_E16as_v5, Standard_E20as_v5, Standard_E32as_v5, Standard_E48as_v5, Standard_E64as_v5, Standard_E96as_v5, Standard_E4ads_v5, Standard_E8ads_v5, Standard_E16ads_v5, Standard_E20ads_v5, Standard_E32ads_v5, Standard_E48ads_v5, Standard_E64ads_v5, Standard_E96ads_v5, Standard_L4s, Standard_L8s, Standard_L16s, Standard_L32s, Standard_F4, Standard_F8, Standard_F16, Standard_F4s, Standard_F8s, Standard_F16s, Standard_H8, Standard_H16, Standard_F4s_v2, Standard_F8s_v2, Standard_F16s_v2, Standard_F32s_v2, Standard_F64s_v2, Standard_F72s_v2, Standard_NC12, Standard_NC24, Standard_NC6s_v3, Standard_NC12s_v3, Standard_NC24s_v3, Standard_NC4as_T4_v3, Standard_NC8as_T4_v3, Standard_NC16as_T4_v3, Standard_NC64as_T4_v3, Standard_ND96asr_v4, Standard_L8s_v2, Standard_L16s_v2, Standard_L32s_v2, Standard_L64s_v2, Standard_L80s_v2, Standard_L8s_v3, Standard_L16s_v3, Standard_L32s_v3, Standard_L48s_v3, Standard_L64s_v3, Standard_L80s_v3, Standard_L8as_v3, Standard_L16as_v3, Standard_L32as_v3, Standard_L48as_v3, Standard_L64as_v3, Standard_L80as_v3, Standard_DC4as_v5, Standard_DC8as_v5, Standard_DC16as_v5, Standard_DC32as_v5, Standard_EC8as_v5, Standard_EC16as_v5, Standard_EC32as_v5, Standard_EC8ads_v5, Standard_EC16ads_v5, Standard_EC32ads_v5, Standard_NV36ads_A10_v5, Standard_NV36adms_A10_v5, Standard_NV72ads_A10_v5, Standard_NC24ads_A100_v4, Standard_NC48ads_A100_v4, Standard_NC96ads_A100_v4, Standard_D4pds_v6, Standard_D8pds_v6, Standard_D16pds_v6, Standard_D32pds_v6, Standard_D48pds_v6, Standard_D64pds_v6, Standard_D96pds_v6, Standard_D4plds_v6, Standard_D8plds_v6, Standard_D16plds_v6, Standard_D32plds_v6, Standard_D48plds_v6, Standard_D64plds_v6, Standard_D96plds_v6, Standard_E4pds_v6, Standard_E8pds_v6, Standard_E16pds_v6, Standard_E32pds_v6, Standard_E48pds_v6, Standard_E64pds_v6, Standard_E96pds_v6, Standard_E4ps_v6, Standard_E8ps_v6, Standard_E16ps_v6, Standard_E32ps_v6, Standard_E48ps_v6, Standard_E64ps_v6, Standard_E96ps_v6, Standard_D4pls_v6, Standard_D8pls_v6, Standard_D16pls_v6, Standard_D32pls_v6, Standard_D48pls_v6, Standard_D64pls_v6, Standard_D96pls_v6, Standard_D4ps_v6, Standard_D8ps_v6, Standard_D16ps_v6, Standard_D32ps_v6, Standard_D48ps_v6, Standard_D64ps_v6, Standard_D96ps_v6, Standard_E20ads_v6, Standard_E48ads_v6, Standard_E96ads_v6, Standard_D48ads_v6, Standard_D96ads_v6, Standard_NC40ads_H100_v5, Standard_NC80adis_H100_v5, Standard_D48ds_v6, Standard_D96ds_v6, Standard_D128ds_v6, Standard_E20ds_v6, Standard_E48ds_v6, Standard_E96ds_v6, Standard_E128ds_v6, Standard_ND96isr_H100_v5, Standard_D4s_v4, Standard_D8s_v4, Standard_D16s_v4, Standard_D32s_v4, Standard_D48s_v4, Standard_D64s_v4, Standard_E2ps_v6, Standard_E2pds_v6

This error message clearly indicates that the Node type Standard_D4ads_v6 is not supported. The extensive list that follows enumerates all the currently supported node types. This InvalidParameterValue exception arises from the databricks.sdk.errors.platform module, suggesting that the Databricks platform itself is rejecting the specified node type. This issue is critical because it prevents the successful installation of DQX when an unsupported node type is selected or defaulted to.

Tracing the Installation Process

The logs provide a step-by-step view of the installation attempt, revealing where the failure occurs:

  1. DQX Installation Initiated: The process begins with the initiation of the DQX installation, specifically version v0.6.1+520250708041552.
  2. Dashboard Creation: The installer proceeds to create dashboards, reading assets from a predefined directory (/home/runner/work/dqx/dqx/src/databricks/labs/dqx/queries/quality/dashboard).
  3. Dashboard Configuration: The installer configures the dashboard, using 'main.dqx_test.output_table' as the source table. Warnings related to parsing expressions and unsupported fields in the dashboard.yml file are also logged, which might warrant further investigation but are not the immediate cause of the failure.
  4. Workflow Installation: The installation process moves to create a new job configuration for the profiler step. This is where the critical error occurs.
  5. Parallel Component Installation Failure: The databricks.labs.blueprint.parallel module reports a failure in the 'installing components' task. The detailed traceback reveals that the attempt to create a Databricks job (self._ws.jobs.create(**settings)) failed due to the InvalidParameterValue exception.

The traceback pinpoints the issue to the workflows_installer.py script, specifically the _deploy_workflow function. This function attempts to create a new Databricks job with the specified settings, including the node type. The error occurs during the jobs.create call, indicating that the Databricks Jobs API rejected the request due to the unsupported node type.

Impact and Implications

This test failure has significant implications for the usability of DQX. If the installation process cannot handle unsupported node types gracefully, users may encounter roadblocks when trying to deploy DQX in their Databricks environments. This issue could lead to:

  • Installation Failures: Users might be unable to install DQX if their Databricks cluster defaults to or requires the use of the Standard_D4ads_v6 node type.
  • Increased Support Burden: The development team may face increased support requests from users struggling with installation issues.
  • Delayed Adoption: Potential users might be discouraged from adopting DQX if the installation process is perceived as complex or unreliable.

Diagnosing the Root Cause

To effectively address this test failure, a thorough diagnosis of the root cause is essential. Several factors could be contributing to the problem:

1. Incorrect Default Node Type Configuration

The most likely cause is an incorrect default node type configuration within the DQX installation process. The installer might be hardcoded to use the Standard_D4ads_v6 node type, or it might be selecting this node type based on a flawed logic. Identifying where the node type is being specified in the installation code is a crucial first step.

2. Environment Incompatibility

It's possible that the test environment used for nightly builds is configured in a way that makes the Standard_D4ads_v6 node type unavailable. This could be due to regional restrictions, account limitations, or other environmental factors. Verifying the test environment's configuration and ensuring it aligns with the supported node types is important.

3. Databricks Platform Changes

Databricks occasionally deprecates or introduces new node types. If the Standard_D4ads_v6 node type was recently deprecated, DQX might not have been updated to reflect this change. Reviewing the Databricks release notes and identifying any recent changes to node type availability is necessary.

4. Logic Errors in Node Type Selection

The DQX installer might have logic to select a node type based on certain criteria (e.g., cluster size, workload type). If this logic contains errors, it could lead to the selection of an unsupported node type. Examining the node type selection logic and identifying any potential flaws is crucial.

Steps to Resolve the Issue

Addressing the test_installation_stores_install_state_keys failure requires a systematic approach. The following steps outline a recommended course of action:

1. Identify the Source of Node Type Specification

The primary task is to pinpoint where the Standard_D4ads_v6 node type is being specified within the DQX installation code. This might involve:

  • Code Review: Examining the workflows_installer.py script, particularly the _deploy_workflow function and any related configuration files.
  • Configuration Analysis: Inspecting any configuration files or settings that might define the default node type.
  • Debugging: Using debugging tools to trace the execution flow and identify where the node type is being set.

2. Update Node Type Selection Logic

Once the source of the node type specification is identified, the logic needs to be updated to ensure a supported node type is selected. This could involve:

  • Hardcoding a Supported Node Type: Replacing the Standard_D4ads_v6 node type with a known supported node type (e.g., Standard_D32s_v3). This is a quick fix but might not be the most flexible solution.
  • Implementing Dynamic Node Type Selection: Developing logic to select a node type based on the available resources and Databricks environment. This approach would provide greater flexibility and resilience.
  • Allowing User Configuration: Providing users with the option to specify the desired node type during installation. This would give users more control over the deployment process.

3. Validate the Fix

After implementing the fix, it's crucial to validate that the issue has been resolved. This can be done by:

  • Running the Test Suite: Executing the test_installation_stores_install_state_keys test to ensure it passes.
  • Performing Manual Installation Tests: Attempting to install DQX in different Databricks environments with various node type configurations.
  • Monitoring Nightly Builds: Tracking the nightly builds to ensure the test failure does not reappear.

4. Enhance Error Handling

To prevent similar issues in the future, it's beneficial to enhance the error handling within the DQX installation process. This could involve:

  • Adding Node Type Validation: Implementing checks to verify that the selected node type is supported before attempting to create Databricks jobs.
  • Providing Informative Error Messages: Generating clear and actionable error messages when an unsupported node type is encountered.
  • Implementing Fallback Mechanisms: Developing mechanisms to fall back to a supported node type if the initially selected node type is unavailable.

Lessons Learned and Future Considerations

The test_installation_stores_install_state_keys failure provides valuable lessons for the DQX development team. It highlights the importance of:

1. Robust Node Type Management

Node type compatibility is a critical aspect of deploying applications on Databricks. DQX needs to have a robust mechanism for managing node types, including:

  • Staying Up-to-Date: Keeping track of Databricks' supported node types and updating DQX accordingly.
  • Flexible Node Type Selection: Implementing flexible logic for selecting node types based on environment and user preferences.
  • Proactive Validation: Validating node types before attempting to create Databricks jobs.

2. Comprehensive Testing

Thorough testing is essential for identifying and preventing issues like this. The DQX test suite should include tests that cover various node type configurations and Databricks environments.

3. Clear Error Messaging

Providing users with clear and informative error messages is crucial for troubleshooting installation issues. Error messages should clearly indicate the cause of the problem and suggest potential solutions.

4. Continuous Monitoring

Monitoring nightly builds and other test runs is essential for identifying regressions and ensuring the stability of DQX. Promptly addressing test failures helps maintain the quality and reliability of the software.

Conclusion

The test_installation_stores_install_state_keys failure serves as a reminder of the complexities involved in deploying applications in cloud environments. By thoroughly diagnosing the root cause, implementing appropriate fixes, and enhancing error handling, the DQX development team can ensure a smoother installation experience for users and maintain the high quality of the product. This incident also underscores the importance of robust node type management, comprehensive testing, clear error messaging, and continuous monitoring in software development.

By addressing these points, the Databricks Quality Explorer (DQX) can become even more user-friendly and reliable, fostering greater adoption and trust within the data science community.