gcp.bigquery.Table

The dataset ID to create the table in. Changing this forces a new resource to be created.

A unique ID for the resource. Changing this forces a new resource to be created.

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

Whether or not to allow the provider to destroy the instance. Unless this field is set to false in state, a =destroy or =update that would delete the instance will fail.

The field description.

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.

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.

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.

A descriptive name for the table.

A mapping of labels to assign to the resource.

• schema - (Optional) A JSON schema for the table.

~>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.

~>NOTE: If you use external_data_configuration documented below and do not set external_data_configuration.connection_id, schemas must be specified with external_data_configuration.schema. Otherwise, schemas must be specified with this top-level field.

If specified, configures this table as a materialized view. Structure is documented below.

The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

If specified, configures range-based partitioning for this table. Structure is documented below.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

If specified, configures time-based partitioning for this table. Structure is documented below.

If specified, configures this table as a view. Structure is documented below.

The dataset ID to create the table in. Changing this forces a new resource to be created.

A unique ID for the resource. Changing this forces a new resource to be created.

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

Whether or not to allow the provider to destroy the instance. Unless this field is set to false in state, a =destroy or =update that would delete the instance will fail.

The field description.

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.

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.

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.

A descriptive name for the table.

A mapping of labels to assign to the resource.

• schema - (Optional) A JSON schema for the table.

~>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.

~>NOTE: If you use external_data_configuration documented below and do not set external_data_configuration.connection_id, schemas must be specified with external_data_configuration.schema. Otherwise, schemas must be specified with this top-level field.

If specified, configures this table as a materialized view. Structure is documented below.

The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

If specified, configures range-based partitioning for this table. Structure is documented below.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

If specified, configures time-based partitioning for this table. Structure is documented below.

If specified, configures this table as a view. Structure is documented below.

The dataset ID to create the table in. Changing this forces a new resource to be created.

A unique ID for the resource. Changing this forces a new resource to be created.

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

Whether or not to allow the provider to destroy the instance. Unless this field is set to false in state, a =destroy or =update that would delete the instance will fail.

The field description.

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.

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.

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.

A descriptive name for the table.

A mapping of labels to assign to the resource.

• schema - (Optional) A JSON schema for the table.

~>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.

~>NOTE: If you use external_data_configuration documented below and do not set external_data_configuration.connection_id, schemas must be specified with external_data_configuration.schema. Otherwise, schemas must be specified with this top-level field.

If specified, configures this table as a materialized view. Structure is documented below.

The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

If specified, configures range-based partitioning for this table. Structure is documented below.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

If specified, configures time-based partitioning for this table. Structure is documented below.

If specified, configures this table as a view. Structure is documented below.

The dataset ID to create the table in. Changing this forces a new resource to be created.

A unique ID for the resource. Changing this forces a new resource to be created.

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

Whether or not to allow the provider to destroy the instance. Unless this field is set to false in state, a =destroy or =update that would delete the instance will fail.

The field description.

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.

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.

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.

A descriptive name for the table.

A mapping of labels to assign to the resource.

• schema - (Optional) A JSON schema for the table.

~>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.

~>NOTE: If you use external_data_configuration documented below and do not set external_data_configuration.connection_id, schemas must be specified with external_data_configuration.schema. Otherwise, schemas must be specified with this top-level field.

If specified, configures this table as a materialized view. Structure is documented below.

The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

If specified, configures range-based partitioning for this table. Structure is documented below.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

If specified, configures time-based partitioning for this table. Structure is documented below.

If specified, configures this table as a view. Structure is documented below.

The dataset ID to create the table in. Changing this forces a new resource to be created.

A unique ID for the resource. Changing this forces a new resource to be created.

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

Whether or not to allow the provider to destroy the instance. Unless this field is set to false in state, a =destroy or =update that would delete the instance will fail.

The field description.

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.

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.

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.

A descriptive name for the table.

A mapping of labels to assign to the resource.

• schema - (Optional) A JSON schema for the table.

~>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.

~>NOTE: If you use external_data_configuration documented below and do not set external_data_configuration.connection_id, schemas must be specified with external_data_configuration.schema. Otherwise, schemas must be specified with this top-level field.

If specified, configures this table as a materialized view. Structure is documented below.

The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

If specified, configures range-based partitioning for this table. Structure is documented below.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

If specified, configures time-based partitioning for this table. Structure is documented below.

If specified, configures this table as a view. Structure is documented below.

The dataset ID to create the table in. Changing this forces a new resource to be created.

A unique ID for the resource. Changing this forces a new resource to be created.

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

Whether or not to allow the provider to destroy the instance. Unless this field is set to false in state, a =destroy or =update that would delete the instance will fail.

The field description.

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.

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.

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.

A descriptive name for the table.

A mapping of labels to assign to the resource.

• schema - (Optional) A JSON schema for the table.

~>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.

~>NOTE: If you use external_data_configuration documented below and do not set external_data_configuration.connection_id, schemas must be specified with external_data_configuration.schema. Otherwise, schemas must be specified with this top-level field.

If specified, configures this table as a materialized view. Structure is documented below.

The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

If specified, configures range-based partitioning for this table. Structure is documented below.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

If specified, configures time-based partitioning for this table. Structure is documented below.

If specified, configures this table as a view. Structure is documented below.

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

A hash of the resource.

The provider-assigned unique ID for this managed resource.

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

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

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

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

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

The URI of the created resource.

The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.

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

A hash of the resource.

The provider-assigned unique ID for this managed resource.

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

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

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

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

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

The URI of the created resource.

The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.

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

A hash of the resource.

The provider-assigned unique ID for this managed resource.

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

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

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

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

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

The URI of the created resource.

The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.

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

A hash of the resource.

The provider-assigned unique ID for this managed resource.

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

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

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

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

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

The URI of the created resource.

The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.

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

A hash of the resource.

The provider-assigned unique ID for this managed resource.

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

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

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

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

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

The URI of the created resource.

The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.

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

A hash of the resource.

The provider-assigned unique ID for this managed resource.

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

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

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

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

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

The URI of the created resource.

The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.

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 gcp.bigquery.getDefaultServiceAccount datasource and the gcp.kms.CryptoKeyIAMBinding resource.

The self link or full name of the kms key version used to encrypt this table.

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 gcp.bigquery.getDefaultServiceAccount datasource and the gcp.kms.CryptoKeyIAMBinding resource.

The self link or full name of the kms key version used to encrypt this table.

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 gcp.bigquery.getDefaultServiceAccount datasource and the gcp.kms.CryptoKeyIAMBinding resource.

The self link or full name of the kms key version used to encrypt this table.

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 gcp.bigquery.getDefaultServiceAccount datasource and the gcp.kms.CryptoKeyIAMBinding resource.

The self link or full name of the kms key version used to encrypt this table.

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 gcp.bigquery.getDefaultServiceAccount datasource and the gcp.kms.CryptoKeyIAMBinding resource.

The self link or full name of the kms key version used to encrypt this table.

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 gcp.bigquery.getDefaultServiceAccount datasource and the gcp.kms.CryptoKeyIAMBinding resource.

The self link or full name of the kms key version used to encrypt this table.

Let BigQuery try to autodetect the schema and format of the table.

A list of the fully-qualified URIs that point to your data in Google Cloud.

Additional options if source_format is set to "AVRO". Structure is documented below.

The compression type of the data source. Valid values are "NONE" or "GZIP".

The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form {{project}}.{{location}}.{{connection_id}} or projects/{{project}}/locations/{{location}}/connections/{{connection_id}}.

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

Additional properties to set if source_format is set to "CSV". Structure is documented below.

Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. Docs

Additional options if source_format is set to "GOOGLE_SHEETS". Structure is documented below.

When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. Structure is documented below.

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.

Additional properties to set if source_format is set to "JSON". Structure is documented below.

The maximum number of bad records that BigQuery can ignore when reading data.

Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. Valid values are AUTOMATIC and MANUAL.

Object Metadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the sourceUris. If object_metadata is set, source_format should be omitted.

Additional properties to set if source_format is set to "PARQUET". Structure is documented below.

When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

The data format. Please see sourceFormat under ExternalDataConfiguration in Bigquery's public API documentation for supported formats. To use "GOOGLE_SHEETS" the scopes must include "https://www.googleapis.com/auth/drive.readonly".

Let BigQuery try to autodetect the schema and format of the table.

A list of the fully-qualified URIs that point to your data in Google Cloud.

Additional options if source_format is set to "AVRO". Structure is documented below.

The compression type of the data source. Valid values are "NONE" or "GZIP".

The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form {{project}}.{{location}}.{{connection_id}} or projects/{{project}}/locations/{{location}}/connections/{{connection_id}}.

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

Additional properties to set if source_format is set to "CSV". Structure is documented below.

Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. Docs

Additional options if source_format is set to "GOOGLE_SHEETS". Structure is documented below.

When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. Structure is documented below.

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.

Additional properties to set if source_format is set to "JSON". Structure is documented below.

The maximum number of bad records that BigQuery can ignore when reading data.

Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. Valid values are AUTOMATIC and MANUAL.

Object Metadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the sourceUris. If object_metadata is set, source_format should be omitted.

Additional properties to set if source_format is set to "PARQUET". Structure is documented below.

When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

The data format. Please see sourceFormat under ExternalDataConfiguration in Bigquery's public API documentation for supported formats. To use "GOOGLE_SHEETS" the scopes must include "https://www.googleapis.com/auth/drive.readonly".

Let BigQuery try to autodetect the schema and format of the table.

A list of the fully-qualified URIs that point to your data in Google Cloud.

Additional options if source_format is set to "AVRO". Structure is documented below.

The compression type of the data source. Valid values are "NONE" or "GZIP".

The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form {{project}}.{{location}}.{{connection_id}} or projects/{{project}}/locations/{{location}}/connections/{{connection_id}}.

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

Additional properties to set if source_format is set to "CSV". Structure is documented below.

Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. Docs

Additional options if source_format is set to "GOOGLE_SHEETS". Structure is documented below.

When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. Structure is documented below.

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.

Additional properties to set if source_format is set to "JSON". Structure is documented below.

The maximum number of bad records that BigQuery can ignore when reading data.

Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. Valid values are AUTOMATIC and MANUAL.

Object Metadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the sourceUris. If object_metadata is set, source_format should be omitted.

Additional properties to set if source_format is set to "PARQUET". Structure is documented below.

When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

The data format. Please see sourceFormat under ExternalDataConfiguration in Bigquery's public API documentation for supported formats. To use "GOOGLE_SHEETS" the scopes must include "https://www.googleapis.com/auth/drive.readonly".

Let BigQuery try to autodetect the schema and format of the table.

A list of the fully-qualified URIs that point to your data in Google Cloud.

Additional options if source_format is set to "AVRO". Structure is documented below.

The compression type of the data source. Valid values are "NONE" or "GZIP".

The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form {{project}}.{{location}}.{{connection_id}} or projects/{{project}}/locations/{{location}}/connections/{{connection_id}}.

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

Additional properties to set if source_format is set to "CSV". Structure is documented below.

Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. Docs

Additional options if source_format is set to "GOOGLE_SHEETS". Structure is documented below.

When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. Structure is documented below.

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.

Additional properties to set if source_format is set to "JSON". Structure is documented below.

The maximum number of bad records that BigQuery can ignore when reading data.

Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. Valid values are AUTOMATIC and MANUAL.

Object Metadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the sourceUris. If object_metadata is set, source_format should be omitted.

Additional properties to set if source_format is set to "PARQUET". Structure is documented below.

When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

The data format. Please see sourceFormat under ExternalDataConfiguration in Bigquery's public API documentation for supported formats. To use "GOOGLE_SHEETS" the scopes must include "https://www.googleapis.com/auth/drive.readonly".

Let BigQuery try to autodetect the schema and format of the table.

A list of the fully-qualified URIs that point to your data in Google Cloud.

Additional options if source_format is set to "AVRO". Structure is documented below.

The compression type of the data source. Valid values are "NONE" or "GZIP".

The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form {{project}}.{{location}}.{{connection_id}} or projects/{{project}}/locations/{{location}}/connections/{{connection_id}}.

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

Additional properties to set if source_format is set to "CSV". Structure is documented below.

Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. Docs

Additional options if source_format is set to "GOOGLE_SHEETS". Structure is documented below.

When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. Structure is documented below.

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.

Additional properties to set if source_format is set to "JSON". Structure is documented below.

The maximum number of bad records that BigQuery can ignore when reading data.

Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. Valid values are AUTOMATIC and MANUAL.

Object Metadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the sourceUris. If object_metadata is set, source_format should be omitted.

Additional properties to set if source_format is set to "PARQUET". Structure is documented below.

When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

The data format. Please see sourceFormat under ExternalDataConfiguration in Bigquery's public API documentation for supported formats. To use "GOOGLE_SHEETS" the scopes must include "https://www.googleapis.com/auth/drive.readonly".

Let BigQuery try to autodetect the schema and format of the table.

A list of the fully-qualified URIs that point to your data in Google Cloud.

Additional options if source_format is set to "AVRO". Structure is documented below.

The compression type of the data source. Valid values are "NONE" or "GZIP".

The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form {{project}}.{{location}}.{{connection_id}} or projects/{{project}}/locations/{{location}}/connections/{{connection_id}}.

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

Additional properties to set if source_format is set to "CSV". Structure is documented below.

Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. Docs

Additional options if source_format is set to "GOOGLE_SHEETS". Structure is documented below.

When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. Structure is documented below.

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.

Additional properties to set if source_format is set to "JSON". Structure is documented below.

The maximum number of bad records that BigQuery can ignore when reading data.

Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. Valid values are AUTOMATIC and MANUAL.

Object Metadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the sourceUris. If object_metadata is set, source_format should be omitted.

Additional properties to set if source_format is set to "PARQUET". Structure is documented below.

When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.

A JSON schema for the external table. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, Iceberg, ORC and Parquet formats. ~>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. Furthermore drift for this field cannot not be detected because BigQuery only uses this schema to compute the effective schema for the table, therefore any changes on the configured value will force the table to be recreated. This schema is effectively only applied when creating a table from an external datasource, after creation the computed schema will be stored in google_bigquery_table.schema

~>NOTE: If you set external_data_configuration.connection_id, the table schema must be specified using the top-level schema field documented above.

The data format. Please see sourceFormat under ExternalDataConfiguration in Bigquery's public API documentation for supported formats. To use "GOOGLE_SHEETS" the scopes must include "https://www.googleapis.com/auth/drive.readonly".

If is set to true, indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).

If is set to true, indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).

If is set to true, indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).

If is set to true, indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).

If is set to true, indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).

If is set to true, indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).

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 the provider escaped as \". Due to limitations with default values, this value is required to be explicitly set.

Indicates if BigQuery should accept rows that are missing trailing optional columns.

Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.

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

The separator for fields in a CSV file.

The number of rows at the top of a CSV file that BigQuery will skip when reading the data.

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 the provider escaped as \". Due to limitations with default values, this value is required to be explicitly set.

Indicates if BigQuery should accept rows that are missing trailing optional columns.

Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.

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

The separator for fields in a CSV file.

The number of rows at the top of a CSV file that BigQuery will skip when reading the data.

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 the provider escaped as \". Due to limitations with default values, this value is required to be explicitly set.

Indicates if BigQuery should accept rows that are missing trailing optional columns.

Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.

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

The separator for fields in a CSV file.

The number of rows at the top of a CSV file that BigQuery will skip when reading the data.

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 the provider escaped as \". Due to limitations with default values, this value is required to be explicitly set.

Indicates if BigQuery should accept rows that are missing trailing optional columns.

Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.

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

The separator for fields in a CSV file.

The number of rows at the top of a CSV file that BigQuery will skip when reading the data.

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 the provider escaped as \". Due to limitations with default values, this value is required to be explicitly set.

Indicates if BigQuery should accept rows that are missing trailing optional columns.

Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.

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

The separator for fields in a CSV file.

The number of rows at the top of a CSV file that BigQuery will skip when reading the data.

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 the provider escaped as \". Due to limitations with default values, this value is required to be explicitly set.

Indicates if BigQuery should accept rows that are missing trailing optional columns.

Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.

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

The separator for fields in a CSV file.

The number of rows at the top of a CSV file that BigQuery will skip when reading the data.

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"

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.

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"

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.

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"

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.

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"

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.

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"

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.

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"

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.

When set, what mode of hive partitioning to use when reading data. The following modes are supported.

• AUTO: automatically infer partition key name(s) and type(s).
• STRINGS: automatically infer partition key name(s). All types are Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
• CUSTOM: when set to CUSTOM, you must encode the partition key schema within the source_uri_prefix by setting source_uri_prefix to gs://bucket/path_to_table/{key1:TYPE1}/{key2:TYPE2}/{key3:TYPE3}.

If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.

When hive partition detection is requested, a common for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. Note that when mode is set to CUSTOM, you must encode the partition key schema within the source_uri_prefix by setting source_uri_prefix to gs://bucket/path_to_table/{key1:TYPE1}/{key2:TYPE2}/{key3:TYPE3}.

When set, what mode of hive partitioning to use when reading data. The following modes are supported.

• AUTO: automatically infer partition key name(s) and type(s).
• STRINGS: automatically infer partition key name(s). All types are Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
• CUSTOM: when set to CUSTOM, you must encode the partition key schema within the source_uri_prefix by setting source_uri_prefix to gs://bucket/path_to_table/{key1:TYPE1}/{key2:TYPE2}/{key3:TYPE3}.

If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.

When hive partition detection is requested, a common for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. Note that when mode is set to CUSTOM, you must encode the partition key schema within the source_uri_prefix by setting source_uri_prefix to gs://bucket/path_to_table/{key1:TYPE1}/{key2:TYPE2}/{key3:TYPE3}.

When set, what mode of hive partitioning to use when reading data. The following modes are supported.

• AUTO: automatically infer partition key name(s) and type(s).
• STRINGS: automatically infer partition key name(s). All types are Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
• CUSTOM: when set to CUSTOM, you must encode the partition key schema within the source_uri_prefix by setting source_uri_prefix to gs://bucket/path_to_table/{key1:TYPE1}/{key2:TYPE2}/{key3:TYPE3}.

If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.

When hive partition detection is requested, a common for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. Note that when mode is set to CUSTOM, you must encode the partition key schema within the source_uri_prefix by setting source_uri_prefix to gs://bucket/path_to_table/{key1:TYPE1}/{key2:TYPE2}/{key3:TYPE3}.