Delete a table

Deleting or dropping a table only removes the table registration and metadata from the Lakehouse runtime catalog. The underlying data files stored in Cloud Storage aren't purged or deleted.

You can delete a table by using the Google Cloud console, SQL drop commands in Spark and Trino, or the REST API.

Before you begin

  1. Verify that billing is enabled for your Google Cloud project.

  2. Enable the BigLake API.

    Roles required to enable APIs

    To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

    Enable the API

  3. Set up the Lakehouse runtime catalog with the Apache Iceberg REST catalog endpoint.

Required roles

To get the permissions that you need to delete a table, ask your administrator to grant you the following IAM roles on your project:

  • All: BigLake Admin (roles/biglake.admin) - your project

For more information about granting roles, see Manage access to projects, folders, and organizations.

You might also be able to get the required permissions through custom roles or other predefined roles.

Table capabilities and support

When using tables in the Lakehouse runtime catalog, it's helpful to understand the different table types and their opt-in capabilities. To learn more about using Apache Iceberg tables specifically, see Overview of Apache Iceberg tables.

Supported Iceberg tables

Only Apache Iceberg V2 (GA) and V3 (Preview) tables are supported. Iceberg V1 tables aren't supported. To upgrade existing V1 tables, see Upgrade Iceberg V1 tables to V2.

Use table options (Preview)

You can opt in to use BigQuery managed capabilities, such as BigQuery Data Manipulation Language (DML) and automatic table management, by configuring specific table properties. These features are enabled in different ways depending on where the table is created:

  • From BigQuery: BigQuery DML and automatic table management are enabled by default.
  • From open source engines: To opt-in, you must explicitly configure table properties. See Configure table options for more information.

Deleting a table registration from the catalog removes the table regardless of whether it's a standard Iceberg table or a table enabled for BigQuery managed capabilities. See Configure table options to understand how table deletion interacts with background table management jobs.

Delete a table

Delete a table.

Console

  1. In the Google Cloud console, go to Lakehouse.

    Go to Lakehouse

  2. Select an existing catalog or create one if you don't have one.

  3. In the Namespace details table, select a table and expand the menu options.

  4. Click Delete.

  5. Confirm the deletion by entering the table name in the dialog.

  6. Click Delete.

Spark 

spark.sql("DROP TABLE TABLE_NAME;")

DROP TABLE TABLE_NAME;

gcloud

To delete a table using gcloud, run the gcloud biglake iceberg tables delete command.

gcloud biglake iceberg tables delete TABLE_NAME \
    --project="PROJECT_ID" \
    --catalog="CATALOG_ID" \
    --namespace="NAMESPACE_NAME"

Replace the following:

  • TABLE_NAME: the name of your Iceberg table.
  • PROJECT_ID: your Google Cloud project ID.
  • CATALOG_ID: the ID of your catalog.
  • NAMESPACE_NAME: the name of your catalog namespace.

BigQuery

To delete an Apache Iceberg table registration in the Lakehouse runtime catalog from BigQuery, use the following GoogleSQL DROP TABLE statement:

DROP TABLE `PROJECT_ID.CATALOG_ID.NAMESPACE.TABLE_NAME`;

Replace the following:

  • PROJECT_ID: your Google Cloud project ID.
  • CATALOG_ID: your Lakehouse runtime catalog ID.
  • NAMESPACE: your Iceberg namespace name.
  • TABLE_NAME: the name of your Iceberg table.

REST

To delete an Iceberg table registration by using the REST API, make a DELETE request to the DeleteIcebergTable endpoint:

DELETE /iceberg/v1/restcatalog/v1/projects/PROJECT_ID/catalogs/CATALOG_ID/namespaces/NAMESPACE_NAME/tables/TABLE_NAME

Replace the following:

  • PROJECT_ID: your Google Cloud project ID.
  • CATALOG_ID: the ID of your catalog.
  • NAMESPACE_NAME: the name of your catalog namespace.
  • TABLE_NAME: the name of your Iceberg table.

What's next