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  1. Preface
  2. Part 1: Introduction to Google BigQuery connectors
  3. Part 2: Data Integration with Google BigQuery V2 Connector
  4. Part 3: Data Integration with Google BigQuery Connector

Google BigQuery Connectors

Google BigQuery Connectors

Google BigQuery connection properties

Google BigQuery connection properties

When you create a Google BigQuery connection, you must configure the connection properties.
The following table describes the Google BigQuery connection properties:
Property
Description
Connection Name
The name of the connection. The name is not case sensitive and must be unique within the domain. You can change this property after you create the connection. The name cannot exceed 128 characters, contain spaces, or contain the following special characters:~ ` ! $ % ^ & * ( ) - + = { [ } ] | \ : ; " ' < , > . ? /
Description
Optional. The description of the connection. The description cannot exceed 4,000 characters.
Type
The Google BigQuery connection type.
Runtime Environment
Name of the runtime environment where you want to run the tasks.
Service Account ID
Specifies the client_email value present in the JSON file that you download after you create a service account.
Service Account Key
Specifies the private_key value present in the JSON file that you download after you create a service account.
Connection mode
The mode that you want to use to read data from or write data to Google BigQuery.
Select one of the following connection modes:
  • Simple. Flattens each field within the Record data type field as a separate field in the mapping.
  • Hybrid. Displays all the top-level fields in the Google BigQuery table including Record data type fields. Google BigQuery Connector displays the top-level Record data type field as a single field of the String data type in the mapping.
  • Complex. Displays all the columns in the Google BigQuery table as a single field of the String data type in the mapping.
Default is Simple.
Schema Definition File Path
Specifies a directory on the Secure Agent machine where the Secure Agent must create a JSON file with the sample schema of the Google BigQuery table. The JSON file name is the same as the Google BigQuery table name.
Alternatively, you can specify a storage path in Google Cloud Storage where the Secure Agent must create a JSON file with the sample schema of the Google BigQuery table. You can download the JSON file from the specified storage path in Google Cloud Storage to a local machine.
The schema definition file is required if you configure complex connection mode in the following scenarios:
  • You add a Hierarchy Builder transformation in a mapping to read data from relational sources and write data to a Google BigQuery target.
  • You add a Hierarchy Parser transformation in a mapping to read data from a Google BigQuery source and write data to relational targets.
Project ID
Specifies the project_id value present in the JSON file that you download after you create a service account.
If you have created multiple projects with the same service account, enter the ID of the project that contains the dataset that you want to connect to.
Dataset ID
Name of the dataset that contains the source table and target table that you want to connect to.
Google BigQuery supports the datasets that reside only in the US region.
Storage Path
This property applies when you read or write large volumes of data. Required if you read data in staging mode or write data in bulk mode.
Path in Google Cloud Storage where the Secure Agent creates a local stage file to store the data temporarily.
You can either enter the bucket name or the bucket name and folder name.
For example, enter
gs://<bucket_name>
or
gs://<bucket_name>/<folder_name>
Ensure that you specify valid credentials in the connection properties. The test connection is successful even if you specify incorrect credentials in the connection properties.

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