gcloud alpha dlp datasources bigquery analyze

NAME: gcloud alpha dlp datasources bigquery analyze - schedule a risk analysis job for content in a BigQuery table
SYNOPSIS: gcloud alpha dlp datasources bigquery analyze INPUT_TABLE (--categorical-stat-field=CATEGORICAL_STAT_FIELD | --numerical-stat-field=NUMERICAL_STAT_FIELD | [--quasi-ids=[QUASI_IDS,…] : --sensitive-attribute=SENSITIVE_ATTRIBUTE]) (--output-table=[OUTPUT_TABLE,…] | --output-topics=[OUTPUT_TOPICS,…]) [--job-id=JOB_ID] [GCLOUD_WIDE_FLAG …]
DESCRIPTION: (ALPHA) Schedules a job to compute risk analysis metrics on content in a BigQuery table.
EXAMPLES: To create a job my-bq-analysis to analyze records in a BigQuery table myproject.myds.mytable, run:
gcloud alpha dlp datasources bigquery analyze `myproject.myds.mytable` --job-id my-ds-job --output-topics my-topic --numerical-stat-field col2
POSITIONAL ARGUMENTS: INPUT_TABLE

BigQuery table to scan. BigQuery tables are uniquely identified by their project_id, dataset_id, and table_id in the format <project_id>.<dataset_id>.<table_id>.
REQUIRED FLAGS: Privacy analysis metrics.
Exactly one of these must be specified:

--categorical-stat-field=CATEGORICAL_STAT_FIELD

An individual column to compute numerical stats on, including number of distinct values and value count distribution.

--numerical-stat-field=NUMERICAL_STAT_FIELD

Individual column to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time.

l-diversity analysis options.

--quasi-ids=[QUASI_IDS,…]

A set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key.
This flag argument must be specified if any of the other arguments in this group are specified.

--sensitive-attribute=SENSITIVE_ATTRIBUTE

Sensitive field for computing the l-diversity value.

Exactly one of these must be specified:

--output-table=[OUTPUT_TABLE,…]

Publishes results of a Cloud DLP job to a BigQuery table. BigQuery tables are uniquely identified by their project_id, dataset_id, and table_id in the format <project_id>.<dataset_id>.<table_id>. If no table_id is specified, DLP will create a new table.

--output-topics=[OUTPUT_TOPICS,…]

Publishes the results of a Cloud DLP job to one or more Cloud Pub/Sub topics.
Note: The topic must have given publishing access rights to the DLP API service account executing the Cloud DLP job.
OPTIONAL FLAGS: --job-id=JOB_ID

Optional job ID to use for the created job. If not provided, a job ID will automatically be generated. Must be unique within the project. The job ID can contain uppercase and lowercase letters, numbers, and hyphens; that is, it must match the regular expression: [a-zA-Z\\d-]+. The maximum length is 100 characters. Can be empty to allow the system to generate one.
GCLOUD WIDE FLAGS: These flags are available to all commands: --access-token-file, --account, --billing-project, --configuration, --flags-file, --flatten, --format, --help, --impersonate-service-account, --log-http, --project, --quiet, --trace-token, --user-output-enabled, --verbosity.
Run $ gcloud help for details.
API REFERENCE: This command uses the dlp/v2 API. The full documentation for this API can be found at: https://cloud.google.com/sensitive-data-protection/docs/
NOTES: This command is currently in alpha and might change without notice. If this command fails with API permission errors despite specifying the correct project, you might be trying to access an API with an invitation-only early access allowlist.