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 |
|
Connection string | jdbc:bigquery:// jdbc:googlebigquery:
|
Packaged? |
|
Certified? |
Yes |
Supported features | |
Estimate job
|
Yes |
Analyze data
|
Yes |
Schedule
|
|
Processing capabilities | |
Pushdown
|
Yes |
Spark agent
|
Yes |
Yarn agent
|
|
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 Example |
Yes |
Driver Name | String |
The driver class name of your BigQuery connection.
|
Yes |
Port | Integer |
The port number to establish a connection to the datasource. The default port is |
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 |
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. base64 encoded commands
To encode your credential JSON file as a base64 encoded string, use one of the following commands:
Tip Your JSON file is typically available to download in GCP when you create a service account in your IAM profile. |
Yes |
Script |
The file path that contains the script file that the password manager uses to interact with and authenticate a user account. Example /tmp/keytab/bigquery_pwd_mgr.sh |
No |
Param $1 | Optional. An additional parameters to authenticate your BigQuery connection. |
No |
Param $2 | Optional. An additional parameter to authenticate your BigQuery connection. |
No |
Param $3 | Optional. An additional parameter to authenticate your BigQuery connection. |
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. Plain text JSON example
The JSON file contains the following service account information: Copy
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.
Miscellaneous
Connection property | Description |
---|---|
AllowLargeResults
|
When set to true , this option allows results larger than the maximum response size when reading large tables. |
QueryPassthrough
|
When set to true , this option passes the query to the Google BigQuery server as is, which can help overcome some SQL syntax errors for valid SQL queries. |
Command line example for basic spark-submit job
-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
- 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
orcat your_json.json | base64 -w 0
- 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_2.12-0.35.1.jar
- Ensure these JARs present in <INSTALL_PATH>/owl/drivers/bigquery/:****animal-sniffer-annotations-1.23.jar,annotations-4.1.1.4.jar,api-common-2.20.0.jar,auto-value-1.10.4.jar,auto-value-annotations-1.10.4.jar,avro-1.11.3.jar,cdata.jdbc.googlebigquery.jar,commons-codec-1.16.0.jar,commons-compress-1.26.0.jar,commons-logging-1.2.jar,conscrypt-openjdk-uber-2.5.2.jar,core,error_prone_annotations-2.22.0.jar,failureaccess-1.0.1.jar,gax-2.37.0.jar,gax-grpc-2.37.0.jar,google-api-client-2.2.0.jar,google-api-services-bigquery-v2-rev20231008-2.0.0.jar,google-auth-library-credentials-1.20.0.jar,google-auth-library-oauth2-http-1.20.0.jar,google-cloud-bigquerystorage-2.46.0.jar,google-cloud-core-2.27.0.jar,google-http-client-1.43.3.jar,google-http-client-apache-v2-1.42.3.jar,google-http-client-gson-1.43.3.jar,google-oauth-client-1.34.1.jar,GoogleBigQueryJDBC42.jar,grpc-alts-1.59.0.jar,grpc-api-1.59.0.jar,grpc-auth-1.59.0.jar,grpc-context-1.59.0.jar,grpc-core-1.59.0.jar,grpc-google-cloud-bigquerystorage-v1-2.46.0.jar,grpc-google-cloud-bigquerystorage-v1beta1-0.170.0.jar,grpc-google-cloud-bigquerystorage-v1beta2-0.170.0.jar,grpc-googleapis-1.59.0.jar,grpc-grpclb-1.59.0.jar,grpc-inprocess-1.59.0.jar,grpc-netty-shaded-1.59.0.jar,grpc-protobuf-1.59.0.jar,grpc-protobuf-lite-1.59.0.jar,grpc-stub-1.59.0.jar,grpc-util-1.59.0.jar,gson-2.10.1.jar,guava-32.1.2-jre.jar,httpclient-4.5.14.jar,httpcore-4.4.16.jar,j2objc-annotations-2.8.jar,jackson-annotations-2.14.2.jar,jackson-core-2.14.2.jar,jackson-databind-2.14.2.jar,javax.annotation-api-1.3.2.jar,joda-time-2.10.10.jar,json-20231013.jar,jsr305-3.0.2.jar,listenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jar,opencensus-api-0.31.1.jar,opencensus-contrib-http-util-0.31.1.jar,perfmark-api-0.26.0.jar,proto-google-cloud-bigquerystorage-v1-2.46.0.jar,proto-google-cloud-bigquerystorage-v1beta1-0.170.0.jar,proto-google-cloud-bigquerystorage-v1beta2-0.170.0.jar,proto-google-common-protos-2.28.0.jar,proto-google-iam-v1-1.23.0.jar,protobuf-java-3.24.4.jar,protobuf-java-util-3.24.4.jar,slf4j-api-1.7.36.jar,threetenbp-1.6.8.jar
- You may get a CLASSPATH conflict regarding the JAR files.
- 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.