Monitor usage with system tables

Preview

This feature is in Public Preview.

This article explains the concept of system tables in Databricks and highlights resources you can use to get the most out of your system tables data.

What are system tables?

System tables are a Databricks-hosted analytical store of your account’s operational data found in the system catalog. System tables can be used for historical observability across your account.

Note

For documentation on system.information_schema, see Information schema.

Which system tables are available?

Currently, Databricks hosts system tables for:

Table

Description

Location

Audit logs

Includes records for all audit events across your Databricks account. For a list of available audit events, see Audit log reference.

system.access.audit

Table lineage

Includes a record for each read or write event on a Unity Catalog table or path.

system.access.table_lineage

Column lineage

Includes a record for each read or write event on a Unity Catalog column (but does not include events that do not have a source).

system.access.column_lineage

Billable usage

Includes records for all billable usage across your account. Each usage record is an hourly aggregate of a resource’s billable usage.

system.billing.usage

Pricing

A historical log of SKU pricing. A record gets added each time there is a change to a SKU price.

system.billing.list_prices

Clusters

A slow-changing dimension table that contains the full history of cluster configurations over time for any cluster.

system.compute.clusters

Node types

Captures the currently available node types with their basic hardware information.

system.compute.node_types

Marketplace funnel events

Includes consumer impression and funnel data for your listings.

system.marketplace.listing_funnel_events

Marketplace listing access

Includes consumer info for completed request data or get data events on your listings.

system.marketplace.listing_access_events

SQL warehouse events

Captures events related to SQL warehouses. For example, starting, stopping, running, scaling up and down.

system.compute.warehouse_events

Predictive optimization

Tracks the operation history of the predictive optimization feature.

system.storage.predictive_optimization_operations_history

Note

You may see other system tables in your account besides the ones listed above. Those tables are in Private Preview currently and are empty by default. If you are interested in using any of these tables, please reach out to your Databricks account team.

Enable system table schemas

Since system tables are governed by Unity Catalog, you need to have at least one Unity Catalog-enabled workspace in your account to enable and access system tables. System tables include data from all workspaces in your account but they can only be accessed from a Unity Catalog-enabled workspace.

System tables are enabled at the schema level. If you enable a system schema, you enable all the tables within that schema. When new schemas are released, an account admin needs to manually enable the schema.

System tables must be enabled by an account admin. You can enable system tables using the Unity Catalog REST API.

List available system schemas

Use the following curl command to list available system schemas:

curl -v -X GET -H "Authorization: Bearer <PAT Token>" "https://<workspace>.cloud.databricks.com/api/2.0/unity-catalog/metastores/<metastore-id>/systemschemas"

The following is an example output of the GET command:

{"schemas":[{"schema":"access","state":"<AVAILABLE OR EnableCompleted>"},{"schema":"billing","state":"<AVAILABLE OR EnableCompleted>"},{"schema":"information_schema","state":"<AVAILABLE OR EnableCompleted>"}]}

state: AVAILABLE: The system schema is available but has not yet been enabled.

state: EnableCompleted: You have enabled the system schema and it is visible in Catalog Explorer.

Enable a system schema

Use the following curl command to enable a system schema:

curl -v -X PUT -H "Authorization: Bearer <PAT Token>" "https://<workspace.databricks.com/api/2.0/unity-catalog/metastores/<metastore-id>/systemschemas/<SCHEMA_NAME>"

If the system schema is enabled successfully, result code 200 is returned.

If you attempt to re-enable a system schema, the following is returned: "error_code":"SCHEMA_ALREADY_EXISTS","message":"Schema <schema-name> already exists".

Disable a system schema

Use the following curl command to disable a system schema:

curl -v -X DELETE -H "Authorization: Bearer <PAT Token>" "https://<workspace>.databricks.com/api/2.0/unity-catalog/metastores/<metastore-id>/systemschemas/<SCHEMA_NAME>"

Grant access to system tables

System table access is governed by Unity Catalog. By default, no users have access to system tables. To grant access, a metastore admin or other privileged user must grant USE and SELECT permissions on the system schemas. See Manage privileges in Unity Catalog.

System tables are read-only and cannot be modified.

Note

If your account was created after November 8, 2023, you might not have a metastore admin by default. For more information, see Set up and manage Unity Catalog.

Do system tables contain data for all workspaces in your account?

The audit log and lineage tables contain operational data for all workspaces in your account deployed within the same cloud region. The billing system table (system.billing.usage) contains data for all workspaces in your account, no matter what region they are deployed in.

Even though system tables can only be accessed through a Unity Catalog workspace, the tables also include operational data for non-Unity Catalog workspaces in your account.

Where are the system tables located?

The system tables in your account are located in a catalog called system, which is included in every Unity Catalog metastore. In the system catalog you’ll see schemas such as access and billing that contain the system tables.

Note

During the system tables Public Preview, Databricks will retain all your system tables data.

Considerations for streaming system tables

Access to system tables is supported by Delta Sharing. Be aware of the following considerations when streaming with Delta Sharing:

  • If you are using streaming with system tables, set the skipChangeCommit option to true. This ensures the streaming job is not disrupted from deletes in the system tables. See Ignore updates and deletes.

  • Trigger.AvailableNow is not supported with Delta Sharing streaming. It will be converted to Trigger.Once.

  • If you use a trigger in your streaming job and find the job isn’t catching up to the latest system table version, Databricks recommends increasing the scheduled frequency of the job.

Known issues

  • Currently no support for real-time monitoring. Data is updated throughout the day. If you don’t see a log for a recent event, check back later.

  • The system schemas system.operational_data and system.lineage are deprecated and will contain empty tables.

  • If your workspace uses a customer-managed VPC, you might be denied access to the S3 bucket where the logs are stored. If so, you need to update your VPC endpoint policy to allow access to the S3 bucket where your region’s system tables data is stored. For a list of regional bucket names, see the System tables bucket column in Storage bucket addresses table.