Connecting to Google BigQuery

This section contains details for Google BigQuery connections.

Select an option from the dropdown menu to display information for a particular driver class.

General information

Field Description
Data source Google BigQuery
Supported versions 1.5.2.1005 21.0.8160.0
Connection string jdbc:bigquery://jdbc:googlebigquery:
Packaged?

No Yes

Certified?

Yes

Supported features
Estimate job

Yes

Analyze data

Yes

Schedule

Yes No

Processing capabilities
Pushdown

Yes

Spark agent

Yes

Yarn agent

Yes No

Parallel JDBC

Yes

Java Platform version compatibility
JDK 8

Yes

JDK 11

Yes

Minimum user permissions

To bring your BigQuery data into Collibra Data Quality & Observability, you need the following permissions:

  • Read access on your BigQuery dataset tables.
  • BigQuery job editor access.
  • Write access on the materialized view datasets.
  • ROLE_ADMIN assigned to your user in Collibra DQ.

Networking and firewalls

Account for the following URLs from networking and firewall perspectives:

  • logging.googleapis.com
  • oauth2.googleapis.com
  • googleapis.com
  • bigquerystorage.googleapis.com
  • bigquery.googleapis.com

Recommended and required connection properties

Required Connection Property Type Value

Yes

Name Text The unique name of your connection. Ensure that there are no spaces in your connection name.

Yes

Connection URL String

The connection string path of your BigQuery connection.

When referring to the example below, replace the value between the { } in the ${value} sections of the connection URL with your actual value.

Example jdbc:bigquery://https://www.googleapis.com/bigquery/v2:443;OAuthType=0;ProjectId=${projectId};OAuthServiceAcctEmail=${service-account};OAuthPvtKeyPath=${/path/to/key};TimeOut=3600jdbc:googlebigquery:AuthScheme="OAuthJWT";OAuthSettingsLocation=memory://;ProjectId=${projectId};InitiateOAuth="GETANDREFRESH";OAuthJWTCert="/tmp/keytab/bigquery.json";OAuthJWTCertType="GOOGLEJSON";OAuthJWTIssuer="iam.service.account";

Yes

Driver Name String

The driver class name of your BigQuery connection.

com.simba.googlebigquery.jdbc42.Drivercdata.jdbc.googlebigquery.GoogleBigQueryDriver

Yes

Port Integer

The port number to establish a connection to the datasource.

The default port is 443

No

Source Name String N/A

No

Target Agent Option The Agent that submits your Spark job for processing.

Yes

Auth Type Option

The method to authenticate your connection.

Note The configuration requirements differ depending on the Auth Type you select. See Authentication for more details on available authentication types.

No

Driver Properties String

The configurable driver properties for your connection. Multiple properties must be comma delimited. For example, abc=123,test=true

Authentication

Select an authentication type from the dropdown menu. The options available in the dropdown menu are the currently supported authentication types for this data source.

Required Field Description

Yes

Username

The username of your BigQuery service account.

Set Username to any value.

Yes

Password

The password of your BigQuery service account.

Enter the base64 encoded string of your OAuth key.

To encode your credential JSON file as a base64 encoded string, use one of the following commands:

base64 your_json.json -w 0 or cat your_json.json | base64 -w 0

Tip Your JSON file is typically available to download in GCP when you create a service account in your IAM profile.

Yes

JSON Credential File

The JSON file containing service account access credentials from your local file storage. Click anywhere in the Service Account Credential field, then upload the JSON credential file containing your Google IAM service account key.

The JSON file contains the following service account information:

Copy 
{
  "type": "service_account",
  "project_id": "owl-hadoop-cdh",
  "private_key_id": "<your-private-key-id-string>",
  "private_key": "-----BEGIN PRIVATE KEY-----\<encoded-string>\n-----END PRIVATE KEY-----\n",
  "client_email": "<your-service-account>@developer.gserviceaccount.com",
  "client_id": "your-service-account-id-string",
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": "https://oauth2.googleapis.com/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/<your-service-account>@developer.gserviceaccount.com"
}

Tip Your JSON file is typically available to download in GCP when you create a service account in your IAM profile.

Note The cdata.jdbc.googlebigquery.GoogleBigQueryDriver driver does not support JSON Credential File authentication.

Yes

Workload Identity

Refer to Configuring Workload Identity for Google BigQuery for information on how to set it up.

Because the Connection URL contains the Project ID associated with the GCP cluster that was set up with the access grant, you only need to select Workload Identity from the Authentication Type dropdown menu, specify an agent, and fill out the other required fields in the connection template once you configure Workload Identity.

Views

When creating views from different datasets (collections), you can add the viewsEnabled=true parameter to the connection property when defining the connection.

Note 
For read/write access to BigQuery, you can use the Spark BigQuery connector. To use this connector, ensure that you have the following configurations:

  • Set viewsEnabled=true.
  • Set materializationDataset to a dataset where the GCP user has table creation permission.
  • Optionally set materializationProject.

Important 
The connector is implemented by running the query on BigQuery and the results are saved into a temporary table. Spark will then read the results, which could result in additional costs on your BigQuery account.

Command line example for basic spark-submit job

Copy 
-lib "/opt/owl/drivers/bigquery/bigquery/core/" \
-h <IP_ADDRESS>:5432/postgres \
-master spark://<SPARK_MASTER>:7077 \
-ds samples.loan_customer \
-deploymode client \
-q "select * from samples.loan_customer" \
-rd "2021-08-02" \
-driver "com.simba.googlebigquery.jdbc42.Driver" \
-cxn BigQuery

Troubleshooting a connection

  1. Password for the BigQuery Connector form in Collibra DQ must be a base64 encoded string created from the JSON file and input as password. For example: base64 your_json.json -w 0 or cat your_json.json | base64 -w 0
  2. Check that this JAR exists and is on the path of the Collibra DQ Web UI server. For example, <INSTALL_PATH>/owl/drivers/bigquery/core). Look at your driver directory location which contains this BigQuery JAR: spark-bigquery_2.12-0.18.1.jar
  3. Ensure these JARs present in <INSTALL_PATH>/owl/drivers/bigquery/:
    ****animal-sniffer-annotations-1.19.jargoogle-api-services-bigquery-v2-rev20201030-1.30.10.jargrpc-google-cloud-bigquerystorage-v1beta1-0.106.4.jarlistenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jarannotations-4.1.1.4.jargoogle-auth-library-credentials-0.22.0.jargrpc-google-cloud-bigquerystorage-v1beta2-0.106.4.jaropencensus-api-0.24.0.jarapi-common-1.10.1.jargoogle-auth-library-oauth2-http-0.22.0.jargrpc-grpclb-1.33.1.jaropencensus-contrib-http-util-0.24.0.jarauto-value-annotations-1.7.4.jarGoogleBigQueryJDBC42.jargrpc-netty-shaded-1.33.1.jarperfmark-api-0.19.0.jaravro-1.10.0.jargoogle-cloud-bigquery-1.125.0.jargrpc-protobuf-1.33.1.jarprotobuf-java-3.13.0.jarchecker-compat-qual-2.5.5.jargoogle-cloud-bigquerystorage-1.6.4.jargrpc-protobuf-lite-1.33.1.jarprotobuf-java-util-3.13.0.jarcommons-codec-1.11.jargoogle-cloud-core-1.93.10.jargrpc-stub-1.33.1.jarproto-google-cloud-bigquerystorage-v1-1.6.4.jarcommons-compress-1.20.jargoogle-cloud-core-http-1.93.10.jargson-2.8.6.jarproto-google-cloud-bigquerystorage-v1alpha2-0.106.4.jarcommons-lang3-3.5.jargoogle-http-client-1.38.0.jarguava-23.0.jarproto-google-cloud-bigquerystorage-v1beta1-0.106.4.jarcommons-logging-1.2.jargoogle-http-client-apache-v2-1.38.0.jarhttpclient-4.5.13.jarproto-google-cloud-bigquerystorage-v1beta2-0.106.4.jarconscrypt-openjdk-uber-2.5.1.jargoogle-http-client-appengine-1.38.0.jarhttpcore-4.4.13.jarproto-google-common-protos-2.0.1.jarcoregoogle-http-client-jackson2-1.38.0.jarj2objc-annotations-1.3.jarproto-google-iam-v1-1.0.3.jarerror_prone_annotations-2.4.0.jargoogle-oauth-client-1.31.1.jarjackson-annotations-2.11.0.jargrpc-alts-1.33.1.jarjackson-core-2.11.3.jarslf4j-api-1.7.30.jarfailureaccess-1.0.1.jargrpc-api-1.33.1.jarjackson-databind-2.11.0.jargax-1.60.0.jargrpc-auth-1.33.1.jarjavax.annotation-api-1.3.2.jarthreetenbp-1.5.0.jargax-grpc-1.60.0.jargrpc-context-1.33.1.jarjoda-time-2.10.1.jargax-httpjson-0.77.0.jargrpc-core-1.33.1.jarjson-20200518.jargoogle-api-client-1.31.1.jargrpc-google-cloud-bigquerystorage-v1-1.6.4.jarjsr305-3.0.2.jar
  4. You may get a CLASSPATH conflict regarding the JAR files.
  5. Ensure the BigQuery connector Scala version matches your Spark Scala version.

Limitations

  • A limitation exists where Spark is unable to process columns of DateTime data types from BigQuery, which causes it to incorrectly parse DateTime columns as string columns.
    • A possible workaround is to cast the DateTime column to timestamp so it processes as a timestamp column instead of a string.
  • A limitation exists where Spark does not support decimal values with fixed precision greater than 38. For more information, see the official Spark documentation.
    • A possible workaround is to cast the data type as a string.
  • The GEOGRAPHY column data type is not supported on Pushdown for BigQuery.
  • When referencing quoted identifiers with backticks ` in the query connection, add -corefetchmode to the DQ Job command line to prevent the removal of the backticks ` at runtime.