BigQueryCheckOperator

Google

Performs checks against BigQuery. The BigQueryCheckOperator expects a sql query that will return a single row. Each value on that first row is evaluated using python bool casting. If any of the values return False the check is failed and errors out.

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Last Updated: May. 7, 2021

Access Instructions

Install the Google provider package into your Airflow environment.

Import the module into your DAG file and instantiate it with your desired params.

Parameters

sqlstrthe sql to be executed
gcp_conn_idstr(Optional) The connection ID used to connect to Google Cloud.
bigquery_conn_idstr(Deprecated) The connection ID used to connect to Google Cloud. This parameter has been deprecated. You should pass the gcp_conn_id parameter instead.
use_legacy_sqlboolWhether to use legacy SQL (true) or standard SQL (false).
locationstrThe geographic location of the job. See details at: https://cloud.google.com/bigquery/docs/locations#specifying_your_location
impersonation_chainUnion[str, Sequence[str]]Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated).

Documentation

Performs checks against BigQuery. The BigQueryCheckOperator expects a sql query that will return a single row. Each value on that first row is evaluated using python bool casting. If any of the values return False the check is failed and errors out.

See also

For more information on how to use this operator, take a look at the guide: Check if query result has data

Note that Python bool casting evals the following as False:

  • False

  • 0

  • Empty string ("")

  • Empty list ([])

  • Empty dictionary or set ({})

Given a query like SELECT COUNT(*) FROM foo, it will fail only if the count == 0. You can craft much more complex query that could, for instance, check that the table has the same number of rows as the source table upstream, or that the count of today’s partition is greater than yesterday’s partition, or that a set of metrics are less than 3 standard deviation for the 7 day average.

This operator can be used as a data quality check in your pipeline, and depending on where you put it in your DAG, you have the choice to stop the critical path, preventing from publishing dubious data, or on the side and receive email alerts without stopping the progress of the DAG.

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