Preface
Introduction to PowerExchange for Google BigQuery
PowerExchange for Google BigQuery Configuration
- PowerExchange for Google BigQuery Configuration Overview
- Registering the PowerExchange for Google BigQuery Plug-in
  - Registering the PowerExchange for Google BigQuery Plug-in from the Administrator Tool
  - Registering the PowerExchange for Google BigQuery Plug-in from the Command Line Program
Google BigQuery Sources and Targets
Google BigQuery Mappings
- Google BigQuery Mappings Overview
- Source Filter
  - Configuring a Source Filter
Google BigQuery Sessions
Google BigQuery as CDC Target
Google BigQuery Pushdown Optimization
Appendix A: Google BigQuery Data Type Reference
- Data Type Reference Overview
- Google BigQuery and Transformation Data Types

PowerExchange for Google BigQuery User Guide for PowerCenter

10.5.6
- 10.5.9
- 10.5.8
- 10.5.7

Back Next

Import Google BigQuery Source and Target Definitions

Use the

Create PowerExchange for BigQuery Source

Create PowerExchange for BigQuery Target

wizard to import Google BigQuery source and target definitions into the PowerCenter repository.

You must import Google BigQuery source and target objects before you create a mapping.

Start PowerCenter Designer, and connect to a PowerCenter repository configured with a Google BigQuery instance.

Open a source or target folder.

Select

Source Analyzer

Target Designer

In the Source Analyzer, click

Sources

Create PowerExchange for BigQuery Source

as shown in the following image:

The image shows the location of the Create PowerExchange For Google BigQuery Source option.

The

Google BigQuery Connection

wizard appears.

In the Target Analyzer, click

Targets

Create PowerExchange for BigQuery Target

as shown in the following image:

The image shows the location of the Create PowerExchange For Google BigQuery Target option.

The

Google BigQuery Connection

dialog box appears.

Configure the following connection parameters:

Connection Parameter	Description
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. PowerExchange for Google BigQuery 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 client machine where the PowerCenter Integration Service 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 PowerCenter Integration Service 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.
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.
Storage Path	This property applies when you read or write large volumes of data. Path in Google Cloud Storage where the PowerCenter Integration Service 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>
Use Legacy SQL For Custom Query	Uses Legacy SQL to define a custom query. You can clear this option, you must use Standard SQL to define a custom query.
Dataset Name for Custom Query	When you define a custom query, you must specify a Google BigQuery dataset.
Region id	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-west4 as the Region ID . In the Storage Path connection 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
Optional Properties	Specifies whether you can configure certain source and target functionalities through custom properties. You can select one of the following options: None. If you do not want to configure any custom properties, select None. Required. If you want to specify custom properties to configure the source and target functionalities. Default is None.
Provide Optional Properties	Comma-separated key-value pairs of custom properties in the Google BigQuery connection to configure certain source and target functionalities. Appears only when you select Required in the Optional Properties.