Resetting A Pipeline Resource Should Also Drop Staging Table

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Problem Description

When using the dlt pipeline drop <resource> command to selectively reset a resource, it currently only drops the final table but not the staging table of the resource. This can cause load failure if the schema is changed in an incompatible way. Manually dropping the staging table will trigger a different error when dlt attempts to truncate the staging table.

Current Behavior

When a resource is reset using dlt pipeline drop <resource>, the final table is dropped, but the staging table remains intact. This can lead to issues when loading data into the staging table, especially if the schema has been changed in an incompatible way.

Expected Behavior

The expected behavior is that the staging table should be dropped and recreated when a pipeline's resource is reset. Additionally, DLT should not run the truncate command if the staging table does not exist.

Steps to Reproduce the Issue

To reproduce the issue, follow these steps:

  1. Create a DLT Pipeline: Create a new DLT pipeline using the dlt pipeline create <pipeline_name> command.
  2. Drop a Resource: Drop a resource using the dlt pipeline drop <resource> command.
  3. Change the Type of a Column: Change the type of a column in the resource and reload the data.
  4. An Error is Raised: An error is raised because of incompatible data when loading the staging table.

Environment Details

  • Operating System: Linux
  • Runtime Environment: Local
  • Python Version: 3.13
  • DLT Data Source: No response
  • DLT Destination: Google BigQuery
  • Other Deployment Details: No response

Additional Information

  • DLT Version: 1.9.0

Solution

To resolve this issue, the dlt pipeline drop <resource> command should be modified to also drop the staging table when resetting a resource. This will ensure that the staging table is recreated with the updated schema, preventing load failure due to incompatible data.

Proposed Changes

  • Modify the dlt pipeline drop <resource> command to drop the staging table when resetting a resource.
  • Add a check to prevent the truncate command from running if the staging table does not exist.

Benefits of the Proposed Changes

  • Ensures that the staging table is recreated with the updated schema, preventing load failure due to incompatible data.
  • Simplifies the process of resetting a resource, reducing the risk of errors and data inconsistencies.

Conclusion

Q: What is the current behavior of the dlt pipeline drop <resource> command?

A: The current behavior of the dlt pipeline drop <resource> command is to only drop the final table of the resource, but not the staging table. This can cause load failure if the schema is changed in an incompatible way.

Q: Why is it necessary to drop the staging table when resetting a resource?

A: It is necessary to drop the staging table when resetting a resource because the staging table may have been updated with new data or schema changes, which can cause load failure if the final table is not updated accordingly.

Q: What are the expected benefits of dropping the staging table when resetting a resource?

A: The expected benefits of dropping the staging table when resetting a resource include:

  • Ensuring that the staging table is recreated with the updated schema, preventing load failure due to incompatible data.
  • Simplifying the process of resetting a resource, reducing the risk of errors and data inconsistencies.

Q: How can I reproduce the issue of not dropping the staging table when resetting a resource?

A: To reproduce the issue, follow these steps:

  1. Create a DLT pipeline using the dlt pipeline create <pipeline_name> command.
  2. Drop a resource using the dlt pipeline drop <resource> command.
  3. Change the type of a column in the resource and reload the data.
  4. An error is raised because of incompatible data when loading the staging table.

Q: What are the environment details required to reproduce the issue?

A: The environment details required to reproduce the issue include:

  • Operating System: Linux
  • Runtime Environment: Local
  • Python Version: 3.13
  • DLT Data Source: No response
  • DLT Destination: Google BigQuery
  • Other Deployment Details: No response

Q: What is the proposed solution to resolve the issue of not dropping the staging table when resetting a resource?

A: The proposed solution is to modify the dlt pipeline drop <resource> command to also drop the staging table when resetting a resource. This will ensure that the staging table is recreated with the updated schema, preventing load failure due to incompatible data.

Q: What are the benefits of the proposed solution?

A: The benefits of the proposed solution include:

  • Ensuring that the staging table is recreated with the updated schema, preventing load failure due to incompatible data.
  • Simplifying the process of resetting a resource, reducing the risk of errors and data inconsistencies.

Q: How can I implement the proposed solution?

A: To implement the proposed solution, you can modify the dlt pipeline drop <resource> command to include the following code:

import dlt

def drop_resource(resource_name):
    # Drop the final table
    dlt.drop_table(resource_name)
    
    # Drop the staging table
    dlt.drop_table(resource_name + '_staging')

This code will drop both the table and the staging table when resetting a resource.

Q: What are the next steps to resolve the issue?

A: The next steps to resolve the issue include:

  • Implementing the proposed solution in the dlt pipeline drop <resource> command.
  • Testing the solution to ensure that it resolves the issue of not dropping the staging table when resetting a resource.
  • Deploying the solution to production to ensure that it is available to all users.