Google Cloud Asset V1 Client - Class BigQueryDestination (1.11.3)

Reference documentation and code samples for the Google Cloud Asset V1 Client class BigQueryDestination.

A BigQuery destination for exporting assets to.

Generated from protobuf message google.cloud.asset.v1.BigQueryDestination

Constructor.

Required. The BigQuery dataset in format "projects/projectId/datasets/datasetId", to which the snapshot result should be exported. If this dataset does not exist, the export call returns an INVALID_ARGUMENT error. Setting the contentType for exportAssets determines the schema of the BigQuery table. Setting separateTablesPerAssetType to TRUE also influences the schema.

Required. The BigQuery dataset in format "projects/projectId/datasets/datasetId", to which the snapshot result should be exported. If this dataset does not exist, the export call returns an INVALID_ARGUMENT error. Setting the contentType for exportAssets determines the schema of the BigQuery table. Setting separateTablesPerAssetType to TRUE also influences the schema.

Required. The BigQuery table to which the snapshot result should be written. If this table does not exist, a new table with the given name will be created.

Required. The BigQuery table to which the snapshot result should be written. If this table does not exist, a new table with the given name will be created.

If the destination table already exists and this flag is TRUE, the table will be overwritten by the contents of assets snapshot. If the flag is FALSE or unset and the destination table already exists, the export call returns an INVALID_ARGUMEMT error.

If the destination table already exists and this flag is TRUE, the table will be overwritten by the contents of assets snapshot. If the flag is FALSE or unset and the destination table already exists, the export call returns an INVALID_ARGUMEMT error.

[partition_spec] determines whether to export to partitioned table(s) and how to partition the data.

If [partition_spec] is unset or [partition_spec.partition_key] is unset or PARTITION_KEY_UNSPECIFIED, the snapshot results will be exported to non-partitioned table(s). [force] will decide whether to overwrite existing table(s). If [partition_spec] is specified. First, the snapshot results will be written to partitioned table(s) with two additional timestamp columns, readTime and requestTime, one of which will be the partition key. Secondly, in the case when any destination table already exists, it will first try to update existing table's schema as necessary by appending additional columns. Then, if [force] is TRUE, the corresponding partition will be overwritten by the snapshot results (data in different partitions will remain intact); if [force] is unset or FALSE, it will append the data. An error will be returned if the schema update or data appension fails.

[partition_spec] determines whether to export to partitioned table(s) and how to partition the data.

If [partition_spec] is unset or [partition_spec.partition_key] is unset or PARTITION_KEY_UNSPECIFIED, the snapshot results will be exported to non-partitioned table(s). [force] will decide whether to overwrite existing table(s). If [partition_spec] is specified. First, the snapshot results will be written to partitioned table(s) with two additional timestamp columns, readTime and requestTime, one of which will be the partition key. Secondly, in the case when any destination table already exists, it will first try to update existing table's schema as necessary by appending additional columns. Then, if [force] is TRUE, the corresponding partition will be overwritten by the snapshot results (data in different partitions will remain intact); if [force] is unset or FALSE, it will append the data. An error will be returned if the schema update or data appension fails.

If this flag is TRUE, the snapshot results will be written to one or multiple tables, each of which contains results of one asset type. The [force] and [partition_spec] fields will apply to each of them.

Field [table] will be concatenated with "" and the asset type names (see https://cloud.google.com/asset-inventory/docs/supported-asset-types for supported asset types) to construct per-asset-type table names, in which all non-alphanumeric characters like "." and "/" will be substituted by "". Example: if field [table] is "mytable" and snapshot results contain "storage.googleapis.com/Bucket" assets, the corresponding table name will be "mytable_storage_googleapis_com_Bucket". If any of these tables does not exist, a new table with the concatenated name will be created. When [content_type] in the ExportAssetsRequest is RESOURCE, the schema of each table will include RECORD-type columns mapped to the nested fields in the Asset.resource.data field of that asset type (up to the 15 nested level BigQuery supports (https://cloud.google.com/bigquery/docs/nested-repeated#limitations)). The fields in >15 nested levels will be stored in JSON format string as a child column of its parent RECORD column. If error occurs when exporting to any table, the whole export call will return an error but the export results that already succeed will persist. Example: if exporting to table_type_A succeeds when exporting to table_type_B fails during one export call, the results in table_type_A will persist and there will not be partial results persisting in a table.

If this flag is TRUE, the snapshot results will be written to one or multiple tables, each of which contains results of one asset type. The [force] and [partition_spec] fields will apply to each of them.

Field [table] will be concatenated with "" and the asset type names (see https://cloud.google.com/asset-inventory/docs/supported-asset-types for supported asset types) to construct per-asset-type table names, in which all non-alphanumeric characters like "." and "/" will be substituted by "". Example: if field [table] is "mytable" and snapshot results contain "storage.googleapis.com/Bucket" assets, the corresponding table name will be "mytable_storage_googleapis_com_Bucket". If any of these tables does not exist, a new table with the concatenated name will be created. When [content_type] in the ExportAssetsRequest is RESOURCE, the schema of each table will include RECORD-type columns mapped to the nested fields in the Asset.resource.data field of that asset type (up to the 15 nested level BigQuery supports (https://cloud.google.com/bigquery/docs/nested-repeated#limitations)). The fields in >15 nested levels will be stored in JSON format string as a child column of its parent RECORD column. If error occurs when exporting to any table, the whole export call will return an error but the export results that already succeed will persist. Example: if exporting to table_type_A succeeds when exporting to table_type_B fails during one export call, the results in table_type_A will persist and there will not be partial results persisting in a table.