![]() ![]() To create a SQL warehouse using the web UI: The default warehouse settings create an efficient and high-performing SQL warehouse, but you can edit some of the settings to fit your workload needs. ![]() You can create warehouses using the SQL Warehouses page in the web UI, using the SQL Warehouse API, or Terraform. Contact your Azure account representative for more information.īefore you can create a serverless SQL warehouse in a region that supports the feature, there may be required steps. Your Azure account may have limitations on how much vCPU quota you can request. See Required Azure vCPU quota for classic and pro SQL warehouses. The default vCPU quota is usually adequate to create a serverless SQL warehouse but might not be enough to scale the SQL warehouse or to create additional warehouses. To manage a SQL warehouse you must be a workspace admin or have the Can Manage permission on the SQL warehouse.įor classic or pro SQL warehouses, your Azure account must have adequate vCPU quota. To create a SQL warehouse you must be a workspace admin or a user with unrestricted cluster creation permissions. SQL warehouses have the following requirements: You can edit or delete this SQL warehouse. To help you get started quickly, Azure Databricks creates a small SQL warehouse called Starter Warehouse automatically. By default, warehouses are sorted by state (running warehouses first), then in alphabetical order. To navigate to the SQL warehouse dashboard, click SQL Warehouses in the sidebar. Compute resources are infrastructure resources that provide processing capabilities in the cloud. What is a SQL warehouse?Ī SQL warehouse is a compute resource that lets you run SQL commands on data objects within Databricks SQL. You can also create SQL warehouses using the SQL warehouse API, or Terraform. You will also learn how to convert existing classic warehouses into serverless warehouses. This includes how to create, edit, and monitor existing SQL warehouses. This article explains how to configure and manage SQL warehouses using the Databricks SQL UI. ![]()
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