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Workspace

databricks_notebook Resource

This resource allows you to manage Databricks notebooks. You can also work with databricks_notebook and databricks_notebook_paths data sources.

Example Usage

You can declare Terraform-managed notebook by specifying source attribute of corresponding local file. Only .scala, .py, .sql and .r extensions are supported, if you would like to omit language attribute.

data "databricks_current_user" "me" {
}

resource "databricks_notebook" "ddl" {
  source = "${path.module}/DDLgen.py"
  path = "${data.databricks_current_user.me.home}/AA/BB/CC"
}

You can also create managed notebook with inline sources through content_base64 and language attributes.

resource "databricks_notebook" "notebook" {
  content_base64 = base64encode(<<-EOT
    # created from ${abspath(path.module)}
    display(spark.range(10))
    EOT
  )
  path = "/Shared/Demo"
  language = "PYTHON"
}

Argument Reference

-> Note Notebook on Databricks workspace would only be changed, if Terraform stage did change. This means that any manual changes to managed notebook won't be overwritten by Terraform, if there's no local change to notebook sources. Notebooks are identified by their path, so changing notebook's name manually on the workspace and then applying Terraform state would result in creation of notebook from Terraform state.

The size of a notebook source code must not exceed few megabytes. The following arguments are supported:

  • path - (Required) The absolute path of the notebook or directory, beginning with "/", e.g. "/Demo".
  • source - Path to notebook in source code format on local filesystem. Conflicts with content_base64.
  • content_base64 - The base64-encoded notebook source code. Conflicts with source. Use of content_base64 is discouraged, as it's increasing memory footprint of Terraform state and should only be used in exceptional circumstances, like creating a notebook with configuration properties for a data pipeline.
  • language - (required with content_base64) One of SCALA, PYTHON, SQL, R.

Attribute Reference

In addition to all arguments above, the following attributes are exported:

  • id - Path of notebook on workspace
  • url - Routable URL of the notebook
  • object_id - Unique identifier for a NOTEBOOK

Access Control

Import

The resource notebook can be imported using notebook path

$ terraform import databricks_notebook.this /path/to/notebook