Common Content for Data Engineering 
			
			- Common Content for Data Engineering 10.5.9
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      Separate multiple options with a space. To enter a value that contains a space or other non-alphanumeric character, enclose the value in quotation marks.... -o option_name=value option_name=value ...
./infacmd.sh createconnection -dn Domain_Adapters_1041_Uni -un Administrator -pd Administrator -cn GBQ_BDM -ct BIGQUERY -o "CLIENTEMAIL='ics-test@api-project-80697026669.iam.gserviceaccount.com' PRIVATEKEY='-----BEGIN PRIVATE KEY-----\nMIIgfdzhgy74587igu787tio9QEFAASCBKgwggSkAgEAAoIBAQCy+2Dbh\n-----END PRIVATE KEY-----\n' PROJECTID=api-project-86699686669 CONNECTORTYPE=Simple SCHEMALOCATION='gs://0_europe-west6_region' STORAGEPATH='gs://0_europe-west6_region' DATASETNAMEFORCUSTOMQUERY='europe_west6' REGIONID='europe-west6'" ;
| Property 
				   | Description 
				   | 
|---|---|
|  CLIENTEMAIL 
				   | Required. Specifies the client_email value present in the JSON file that you download after you create a service account in Google BigQuery. 
				   | 
|  PRIVATEKEY 
				   |  Required. Specifies the private_key value present in the JSON file that you download after you create a service account in Google BigQuery. 
				   | 
| Connection Mode 
					  CONNECTORTYPE 
					  | Required. The connection mode that you want to use to read data from or write data to Google BigQuery. 
					  Enter one of the following connection modes: 
					  
 Default is Simple. 
					  | 
| Schema Definition File Path 
					  SCHEMALOCATION 
					  | Required. Specifies a directory on the client machine where the PowerExchange for Google BigQuery 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 PowerExchange for Google BigQuery 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. 
					  | 
| PROJECTID 
				   | Required. Specifies the project_id value present in the JSON file that you download after you create a service account in Google BigQuery. 
					   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. 
					  | 
| STORAGEPATH 
				   |  Required when you read or write large volumes of data. 
					  Path in Google Cloud Storage where PowerExchange for Google BigQuery 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> | 
| REGIONID
				   | The region name where the Google BigQuery dataset resides. 
					  For example, if you want to connect to a Google BigQuery dataset that resides in Las Vegas region, specify 
						 us-west4as the Region ID. In the 
						 Storage Pathconnection property, ensure that you specify a bucket name or the bucket name and folder name that resides in the same region as the dataset in Google BigQuery. For more information about the regions supported by Google BigQuery, see the following Google BigQuery documentation:https://cloud.google.com/bigquery/docs/locations 
					  |