Why are certain BigQuery jobs not allocated to the reservation?

[graceho27291]

I've established a reservation specifically for query jobs. However, why are certain BigQuery jobs not being assigned to this reservation? (With the reservation ID appearing as null)

Capacity Management:

[ms4446 · Accepted solution]

In BigQuery, reservations are used to manage and allocate dedicated query processing resources to specific jobs or projects. If you've noticed that certain BigQuery jobs are not being allocated to a specific reservation, even though you've set one up, there could be several reasons for this. Here are some common scenarios and troubleshooting steps to consider:

Here's a breakdown of the reasons why some BigQuery jobs might not be allocated to your reservation, even if you've set one up specifically for query jobs:

1. Job Type Mismatch:

   • Reservation Type: Ensure your reservation is specifically set for "QUERY" operations. Reservations for "PIPELINE" are intended for different types of data processing jobs, not for standard SQL queries.
   • Job Priority: While job priority (INTERACTIVE vs. BATCH) affects the execution priority of jobs, it does not inherently override reservation assignments unless explicitly configured in job settings.

2. Project and Folder Assignments:

   • Direct Assignment: Verify that the project running the query is directly assigned to the reservation. This is crucial for the reservation resources to be utilized.
   • Inheritance: If using folder-level assignments, ensure that inheritance is correctly set up and that there are no conflicting assignments at lower levels that might prevent the reservation from being applied.

3. Idle Slots and Capacity:

   • Idle Slot Sharing: If your reservation has idle slot sharing enabled, other projects within the same organization might use its idle slots. This can make it appear as though your job isn't using the reservation.
   • Reservation Capacity: If your reservation runs out of slots due to high demand, new jobs will revert to using on-demand resources, even if they are within the assigned project.

4. Special Cases and Limitations:

   • BigQuery ML: Some BigQuery ML jobs might not utilize reservations depending on the specific model and operation being executed.
   • Legacy SQL: Ensure that Legacy SQL queries are configured to respect reservation assignments. While generally supported, specific configurations or unusual scenarios might lead to unexpected behavior.

Troubleshooting Tips:

• Information Schema: Use the INFORMATION_SCHEMA.JOBS view to check the actual reservation used by a job. This can provide insights into whether jobs are correctly using the assigned reservation.
• Reservation Details: Review your reservation's configuration in the Google Cloud Console or using the bq show command to ensure it is set up correctly.
• Job Audit Logs: Audit logs can be a valuable resource for detailed information about job execution and resource usage, helping to identify why a job did not use a reservation.

Additional Resources:

• For more detailed guidance on managing and troubleshooting reservations, refer to the official Google Cloud documentation on BigQuery reservations: Work with slot reservations | BigQuery.

If you've gone through these points and are still facing issues, consider reaching out to Google Cloud Support for further assistance. They can provide more targeted help based on your specific configuration and usage patterns.

[ms4446 · Accepted solution]

In BigQuery, reservations are used to manage and allocate dedicated query processing resources to specific jobs or projects. If you've noticed that certain BigQuery jobs are not being allocated to a specific reservation, even though you've set one up, there could be several reasons for this. Here are some common scenarios and troubleshooting steps to consider:

Here's a breakdown of the reasons why some BigQuery jobs might not be allocated to your reservation, even if you've set one up specifically for query jobs:

1. Job Type Mismatch:

   • Reservation Type: Ensure your reservation is specifically set for "QUERY" operations. Reservations for "PIPELINE" are intended for different types of data processing jobs, not for standard SQL queries.
   • Job Priority: While job priority (INTERACTIVE vs. BATCH) affects the execution priority of jobs, it does not inherently override reservation assignments unless explicitly configured in job settings.

2. Project and Folder Assignments:

   • Direct Assignment: Verify that the project running the query is directly assigned to the reservation. This is crucial for the reservation resources to be utilized.
   • Inheritance: If using folder-level assignments, ensure that inheritance is correctly set up and that there are no conflicting assignments at lower levels that might prevent the reservation from being applied.

3. Idle Slots and Capacity:

   • Idle Slot Sharing: If your reservation has idle slot sharing enabled, other projects within the same organization might use its idle slots. This can make it appear as though your job isn't using the reservation.
   • Reservation Capacity: If your reservation runs out of slots due to high demand, new jobs will revert to using on-demand resources, even if they are within the assigned project.

4. Special Cases and Limitations:

   • BigQuery ML: Some BigQuery ML jobs might not utilize reservations depending on the specific model and operation being executed.
   • Legacy SQL: Ensure that Legacy SQL queries are configured to respect reservation assignments. While generally supported, specific configurations or unusual scenarios might lead to unexpected behavior.

Troubleshooting Tips:

• Information Schema: Use the INFORMATION_SCHEMA.JOBS view to check the actual reservation used by a job. This can provide insights into whether jobs are correctly using the assigned reservation.
• Reservation Details: Review your reservation's configuration in the Google Cloud Console or using the bq show command to ensure it is set up correctly.
• Job Audit Logs: Audit logs can be a valuable resource for detailed information about job execution and resource usage, helping to identify why a job did not use a reservation.

Additional Resources:

• For more detailed guidance on managing and troubleshooting reservations, refer to the official Google Cloud documentation on BigQuery reservations: Work with slot reservations | BigQuery.

If you've gone through these points and are still facing issues, consider reaching out to Google Cloud Support for further assistance. They can provide more targeted help based on your specific configuration and usage patterns.

[graceho27291]

Hi @ms4446,

Thanks for your reply. I've checked the query.

It seems that all query jobs that don't use reservations are querying

INFORMATION_SCHEMA.JOBS_BY_PROJECT table.
Why doesn't it use reservations?

[ms4446 · Accepted solution]

The reason behind this is related to the specific nature of INFORMATION_SCHEMA queries. These are considered metadata operations rather than typical data-processing queries. Metadata queries, such as those querying INFORMATION_SCHEMA tables, are designed to retrieve information about various aspects of your BigQuery usage, like job, table, or dataset details. Due to their lightweight nature and different execution method, they are handled separately from the more intensive data-processing tasks that benefit from reservations.

INFORMATION_SCHEMA queries are a special case:

• Metadata operations: These queries are designed to quickly fetch metadata (information about your BigQuery usage), not to process large datasets.
• System-managed resources: Google handles these queries using dedicated resources, separate from your standard BigQuery slots and quotas. This ensures they don't impact your main data processing jobs.
• Non-billable: You aren't charged for these queries, so using reserved slots would be an inefficient use of paid resources.
• Performance optimization: Google manages these queries for fast access, and they typically don't need the heavy-duty resources that reservations provide.

[graceho27291]

Thank you for your prompt reply! I have no more questions