Connect Soda to GCP BigQuery
Last modified on 29-Nov-24
For Soda to run quality scans on your data, you must configure it to connect to your data source.
To learn how to set up Soda and configure it to connect to your data sources, see Get started.
Connection configuration
Authentication methods
Test the datasource connection
Supported data types
Use a file reference for a BigQuery data source connection
Troubleshoot
A note about BigQuery datasets: Google uses the term dataset slightly differently than Soda (and many others) do.
- In the context of Soda, a dataset is a representation of a tabular data structure with rows and columns. A dataset can take the form of a table in PostgreSQL or Snowflake, or a DataFrame in a Spark application.
- In the context of BigQuery, a dataset is “a top-level container that is used to organize and control access to your tables and views. A table or view must belong to a dataset…”
Instances of “dataset” in Soda documentation always reference the former.
Connection configuration reference
Install package: soda-bigquery
# Service Account Key authentication method
# See Authentication methods below for more config options
data_source my_datasource_name:
type: bigquery
account_info_json: '{
"type": "service_account",
"project_id": "gold-platform-67883",
"private_key_id": "d0121d000000870xxx",
"private_key": "-----BEGIN PRIVATE KEY-----\n...\n-----END PRIVATE KEY-----\n",
"client_email": "abc333@project.iam.gserviceaccount.com",
"client_id": "XXXXXXXXXXXXXXXXXXXX.apps.googleusercontent.com",
"auth_uri": "https://accounts.google.com/o/oauth2/auth",
"token_uri": "https://accounts.google.com/o/oauth2/token",
"auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
"client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/..."
}'
auth_scopes:
- https://www.googleapis.com/auth/bigquery
- https://www.googleapis.com/auth/cloud-platform
- https://www.googleapis.com/auth/drive
project_id: "platinum-platform-67883"
dataset: sodacore
Property | Required | Notes (See Google BigQuery Integration parameters) |
---|---|---|
type | required | Identify the type of data source for Soda. |
account_info_json | required | The integration parameters for account info are listed below. If you do not provide values for the properties, Soda uses the Google application default values. |
type | required | This the type of BigQuery account. Default: service_account |
project_id | required | This is the unique identifier for the project in your console. See Locate the project ID. |
private_key_id | required | A unique identifier that you generate in your console. See Create an API key. |
private_key | required | A unique identifier that you generate in your console. See Create an API key. |
client_email | required | Also known as the service account ID, find this value in the IAM & Admin > Service Accounts > Details tab in your Google Cloud Console. |
client_id | required | Your unique ID, find this value in the IAM & Admin > Service Accounts > Details tab in your Google Cloud Console. |
auth_uri | required | BigQuery’s authentication URI to which you send auth credentials. Default: https://accounts.google.com/o/oauth2/auth |
token_uri | required | BigQuery’s token URI to which you send access tokens. Default: https://oauth2.googleapis.com/ token |
auth_provider_x509_cert_url | required | BigQuery’s public x509 certificate URL that it uses to verify the JWT signed by the authentication provider. Default: https://www.googleapis.com/ oauth2/v1/certs |
client_x509_cert_url | required | BigQuery’s public x509 certificate URL that it uses to verify the JWT signed by the client. |
auth_scopes | optional | Soda applies three OAuth 2.0 scopes: • https://www.googleapis.com/auth/bigquery to view and manage your data in BigQuery• https://www.googleapis.com/auth/cloud-platform to view, configure, and delete your Google Cloud data• https://www.googleapis.com/auth/drive to view and add to the record of file activity in your Google Drive |
project_id | optional | Add an identifier to override the project_id from the account_info_json |
storage_project_id | optional | Add an identifier to use a separate BigQuery project for compute and storage. |
dataset | required | The identifier for your BigQuery dataset, the top-level container that is used to organize and control access to your tables and views. |
Authentication methods
Using GCP BigQuery, you have the option of using one of several methods to authenticate the connection.
- Application Default Credentials
- Application Default Credentials with Service Account impersonation
- Service Account Key (see connection configuration above)
- Service Account Key with Service Account Impersonation
Application Default Credentials
Add the use_context_auth
property to your connection configuration, as per the following example.
data_source my_datasource:
type: bigquery
...
use_context_auth: True
Application Default Credentials with Service Account impersonation
Add the use_context_auth
and impersonation_account
properties to your connection configuration, as per the following example.
data_source my_datasource:
type: bigquery
...
use_context_auth: True
impersonation_account: <SA_EMAIL>
Service Account Key with Service Account impersonation
Add the impersonation_account
property to your connection configuration, as per the following example.
data_source my_database_name:
type: bigquery
...
account_info_json: '{
"type": "service_account",
"project_id": "...",
"private_key_id": "...",
...}'
impersonation_account: <SA_EMAIL>
Test the data source connection
To confirm that you have correctly configured the connection details for the data source(s) in your configuration YAML file, use the test-connection
command. If you wish, add a -V
option to the command to returns results in verbose mode in the CLI.
soda test-connection -d my_datasource -c configuration.yml -V
Supported data types
Category | Data type |
---|---|
text | STRING |
number | INT64, DECIMAL, BINUMERIC, BIGDECIMAL, FLOAT64 |
time | DATE, DATETIME, TIME, TIMESTAMP |
Use a file reference for a BigQuery data source connection
If you already store information about your data source in a JSON file in a secure location, you can configure your BigQuery data source connection details in Soda Cloud to refer to the JSON file for service account information. To do so, you must add two elements:
volumes
andvolumeMounts
parameters in thevalues.yml
file that your Soda Agent helm chart uses- the
account_info_json_path
in your data source connection configuration
You, or an IT Admin in your organization, can add the following scanlauncher
parameters to the existing values.yml
that your Soda Agent uses for deployment and redployment in your Kubernetes cluster. Refer to Deploy using a values YAML file for details.
soda:
scanlauncher:
volumeMounts:
- name: gcloud-credentials
mountPath: /opt/soda/etc
volumes:
- name: gcloud-credentials
secret:
secretName: gcloud-credentials
items:
- key: serviceaccount.json
path: serviceaccount.json
Use the following command to add the service account information to a Kubernetes secret that the Soda Agent consumes according to the configuration above; replace the angle brackets and the values in them with your own values.
kubectl create secret generic -n <soda-agent-namespace> gcloud-credentials --from-file=serviceaccount.json=<local path to the serviceccount.json>
After you make both of these changes, you must redeploy the Soda Agent. Refer to Deploy using a values YAML file for details.
Adjust the data source connection configuration to include the account_info_json_path
configuration, as per the following example.
my_datasource_name:
type: bigquery
account_info_json_path: /opt/soda/etc/serviceaccount.json
auth_scopes:
- https://www.googleapis.com/auth/bigquery
- https://www.googleapis.com/auth/cloud-platform
- https://www.googleapis.com/auth/drive
project_id: ***
dataset: sodalibrary
Troubleshoot
Problem: When running a scan, you encounter an error that reads, 400 Cannot query over table 'event_logs' without a filter over column(s) 'serverTimestamp' that can be used for partition elimination
.
Workaround: The error occurs because the table in BigQuery is configured to require partitioning.
- If the error occurs when you are profiling your data with Soda, you must disable profiling.
- If the error occurs when the scan is executing regular SodaCL checks, be sure you always apply a filter on
serverTimestamp
. See Dataset filters
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Documentation always applies to the latest version of Soda products
Last modified on 29-Nov-24