# Google BigQuery properties

Properties to configure to establish a connection to Google BigQuery.

## Google BigQuery connection

Select Google BigQuery in the list and configure the connection.

## Configuration

Select your engine from the list and set the main and advanced settings.

Connection settingsConnection settings

| Property | Configuration |
| --- | --- |
| Project name | Enter the unique identifier of your Google Cloud Platform project. This<br>information is available on the Dashboard page of your Google Cloud console.<br>To know more about Google Cloud projects, read [the Google Cloud documentation](https://cloud.google.com/resource-manager/docs/creating-managing-projects). |
| Google credentials | Paste the content of the JSON file that contains your service account<br>key. To know more about the Google Cloud authentication process, read [the Google Cloud documentation](https://cloud.google.com/docs/authentication/getting-started). |

## Google BigQuery dataset

Dataset configurationDataset configuration

| Property | Configuration |
| --- | --- |
| Dataset name | Enter a<br>display name for the dataset. This name will be used as a unique identifier of<br>the dataset in all Talend Cloud apps. |
| Connection | Select<br>your connection in the list. If you are creating a dataset based on an existing<br>connection, this field is read-only. |
| Type | Select the type of dataset you want to create:<br><br><ul> <li> <span>Table</span>: to access the dataset and dataset table                              located in your BigQuery bucket using their unique names.</li> <li> <span>Query</span>: to query the data in your existing                              tables.</li> </ul> |

Table settingsTable settings

| Property | Configuration |
| --- | --- |
| Dataset | Select or enter the unique name of your BigQuery dataset that contains<br>your table. For more information, see the [Google BigQuery documentation about<br>datasets](https://cloud.google.com/bigquery/docs/datasets-intro). |
| Table name | Select or enter the unique name of your Amazon Aurora table. |
| Storage bucket | Enter the name of the bucket, the Google BigQuery container, which holds<br>the data. |

Query settingsQuery settings

| Property | Configuration |
| --- | --- |
| Query | Enter the query to access the data of your choice located in your<br>BigQuery table. |
| Use legacy SQL | If the query to be used is the legacy SQL of BigQuery, enable this<br>option. For further information about this legacy SQL, see [the Legacy SQL query reference](https://cloud.google.com/bigquery/docs/reference/legacy-sql) from the Google<br>BigQuery documentation. |

## Google BigQuery destination configuration

When Google BigQuery is used as a destination dataset in your pipeline, you can select the type of operation you want to do while inserting data in your BigQuery table:

| Property | Configuration |
| --- | --- |
| Table operation | Select how the processed data will be inserted in your BigQuery table:<br><br><ul> <li> <span>Append</span>: select this option to append the                              processed data to the existing BigQuery table at execution time.</li> <li> <span>Create if not exists</span>: select this option to                              create a BigQuery table and insert the processed data in this table at                              execution time.</li> <li> <span>Truncate</span>: select this option to remove all the                              existing rows and thus overwrite the content of your BigQuery table at                              execution time.</li> </ul> |
| Max batch size | Set the maximum number of lines allowed in each batch. Changing the<br>default value may impact the pipeline performances. |

Additional JDBC parameters might be displayed depending on whether the connector is used as a source or destination dataset, read [the JDBC parameters section](https://help.qlik.com/talend/r/en-US/Cloud/connectors-guide/jdbc) to know more about these parameters.