» google_bigquery_table

Creates a table resource in a dataset for Google BigQuery. For more information see the official documentation and API.

» Example Usage

resource "google_bigquery_dataset" "default" {
  dataset_id                  = "foo"
  friendly_name               = "test"
  description                 = "This is a test description"
  location                    = "EU"
  default_table_expiration_ms = 3600000

  labels = {
    env = "default"

resource "google_bigquery_table" "default" {
  dataset_id = google_bigquery_dataset.default.dataset_id
  table_id   = "bar"

  time_partitioning {
    type = "DAY"

  labels = {
    env = "default"

  schema = <<EOF
    "name": "permalink",
    "type": "STRING",
    "mode": "NULLABLE",
    "description": "The Permalink"
    "name": "state",
    "type": "STRING",
    "mode": "NULLABLE",
    "description": "State where the head office is located"


resource "google_bigquery_table" "sheet" {
  dataset_id = google_bigquery_dataset.default.dataset_id
  table_id   = "sheet"

  external_data_configuration {
    autodetect    = true
    source_format = "GOOGLE_SHEETS"

    google_sheets_options {
      skip_leading_rows = 1

    source_uris = [

» Argument Reference

The following arguments are supported:

  • dataset_id - (Required) The dataset ID to create the table in. Changing this forces a new resource to be created.

  • table_id - (Required) A unique ID for the resource. Changing this forces a new resource to be created.

  • project - (Optional) The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

  • description - (Optional) The field description.

  • expiration_time - (Optional) The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed.

  • external_data_configuration - (Optional) Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table. Structure is documented below.

  • friendly_name - (Optional) A descriptive name for the table.

  • encryption_configuration - (Optional) Specifies how the table should be encrypted. If left blank, the table will be encrypted with a Google-managed key; that process is transparent to the user. Structure is documented below.

  • labels - (Optional) A mapping of labels to assign to the resource.

  • schema - (Optional) A JSON schema for the table. Schema is required for CSV and JSON formats and is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats when using external tables. For more information see the BigQuery API documentation. ~>NOTE: Because this field expects a JSON string, any changes to the string will create a diff, even if the JSON itself hasn't changed. If the API returns a different value for the same schema, e.g. it switched the order of values or replaced STRUCT field type with RECORD field type, we currently cannot suppress the recurring diff this causes. As a workaround, we recommend using the schema as returned by the API.

  • time_partitioning - (Optional) If specified, configures time-based partitioning for this table. Structure is documented below.

  • clustering - (Optional) Specifies column names to use for data clustering. Up to four top-level columns are allowed, and should be specified in descending priority order.

  • view - (Optional) If specified, configures this table as a view. Structure is documented below.

The external_data_configuration block supports:

  • autodetect - (Required) - Let BigQuery try to autodetect the schema and format of the table.

  • compression (Optional) - The compression type of the data source. Valid values are "NONE" or "GZIP".

  • csv_options (Optional) - Additional properties to set if source_format is set to "CSV". Structure is documented below.

  • google_sheets_options (Optional) - Additional options if source_format is set to "GOOGLE_SHEETS". Structure is documented below.

  • ignore_unknown_values (Optional) - Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.

  • max_bad_records (Optional) - The maximum number of bad records that BigQuery can ignore when reading data.

  • source_format (Required) - The data format. Supported values are: "CSV", "GOOGLE_SHEETS", "NEWLINE_DELIMITED_JSON", "AVRO", and "DATSTORE_BACKUP". To use "GOOGLE_SHEETS" the scopes must include "https://www.googleapis.com/auth/drive.readonly".

  • source_uris - (Required) A list of the fully-qualified URIs that point to your data in Google Cloud.

The csv_options block supports:

  • quote (Required) - The value that is used to quote data sections in a CSV file. If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allow_quoted_newlines property to true. The API-side default is ", specified in Terraform escaped as \". Due to limitations with Terraform default values, this value is required to be explicitly set.

  • allow_jagged_rows (Optional) - Indicates if BigQuery should accept rows that are missing trailing optional columns.

  • allow_quoted_newlines (Optional) - Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.

  • encoding (Optional) - The character encoding of the data. The supported values are UTF-8 or ISO-8859-1.

  • field_delimiter (Optional) - The separator for fields in a CSV file.

  • skip_leading_rows (Optional) - The number of rows at the top of a CSV file that BigQuery will skip when reading the data.

The google_sheets_options block supports:

  • range (Optional) - Range of a sheet to query from. Only used when non-empty. At least one of range or skip_leading_rows must be set. Typical format: "sheet_name!top_left_cell_id:bottom_right_cell_id" For example: "sheet1!A1:B20"

  • skip_leading_rows (Optional) - The number of rows at the top of the sheet that BigQuery will skip when reading the data. At least one of range or skip_leading_rows must be set.

The time_partitioning block supports:

  • expiration_ms - (Optional) Number of milliseconds for which to keep the storage for a partition.

  • field - (Optional) The field used to determine how to create a time-based partition. If time-based partitioning is enabled without this value, the table is partitioned based on the load time.

  • type - (Required) The only type supported is DAY, which will generate one partition per day based on data loading time.

  • require_partition_filter - (Optional) If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.

The view block supports:

  • query - (Required) A query that BigQuery executes when the view is referenced.

  • use_legacy_sql - (Optional) Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL.

The encryption_configuration block supports the following arguments:

  • kms_key_name - (Required) The self link or full name of a key which should be used to encrypt this table. Note that the default bigquery service account will need to have encrypt/decrypt permissions on this key - you may want to see the google_bigquery_default_service_account datasource and the google_kms_crypto_key_iam_binding resource.

» Attributes Reference

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

  • creation_time - The time when this table was created, in milliseconds since the epoch.

  • etag - A hash of the resource.

  • last_modified_time - The time when this table was last modified, in milliseconds since the epoch.

  • location - The geographic location where the table resides. This value is inherited from the dataset.

  • num_bytes - The size of this table in bytes, excluding any data in the streaming buffer.

  • num_long_term_bytes - The number of bytes in the table that are considered "long-term storage".

  • num_rows - The number of rows of data in this table, excluding any data in the streaming buffer.

  • self_link - The URI of the created resource.

  • type - Describes the table type.

» Import

BigQuery tables can be imported using the project, dataset_id, and table_id, e.g.

$ terraform import google_bigquery_table.default gcp-project/foo/bar