Create a Google BigQuery Connection
To access your data stored on a Google BigQuery database, you will need to know the server and database name that you want to connect to, and you must have access credentials. Once you have created a connection to a Google BigQuery database, you can select data from the available tables and then load that data into your app or document.
In Qlik Sense, you connect to a Google BigQuery database through the Add data dialog or the Data load editor.
In Qlik Cloud Data Integration, you connect to a Google BigQuery database when setting a target platform for a data project.
In QlikView you connect to a Google BigQuery database through the Edit Script dialog.
Creating a trusted storage certificate
If you do not have an appropriate storage certificate to use with the connector in your Windows environment, you will need to download one.
Do the following:
Go to Google Trust Services - Repository and navigate to the Download CA certificate section.
Select the GTS Root R2 certificate with fingerprint SHA1: 8d:25:cd:97:22:9d:bf:70:35:6b:da:4e:b3:cc:73:40:31:e2:4c:f0:0f:af:cf:d3:2d:c7:6e:b5:84:1c:7e:a8 .
Click Action and download the certificate as a PEM file.
Authenticating the Google account
The first step is to authenticate your Google account using the account properties below.
Select User Authentication or Service Authentication mechanisms.
For Service Authentication, the Google service account must be BigQuery Job User for connections to multiple catalogs, or BigQuery Data Viewer for connections to a single catalog. Read more about how to configure permissions for the Google service account in the Google documentation.
|Sign In||Redirects to a Google sign-in page where you can obtain a confirmation code.||Yes, when User Authentication is selected.|
|Confirmation Code||The code obtained from the Google sign-in page.||Yes, when User Authentication is selected.|
|The service account email.||Yes, when Service Authentication is selected.|
|Key File||The uploaded key file.||Yes, when Service Authentication is selected.|
|File||Click to upload a key file.||Yes, when Service Authentication is selected.|
|Validate||Validates the confirmation code or the key.||Yes|
|P12 Password||This option allows you to use a P12 private key file with a non-standard password. The specified value is the password your key file is encrypted with.||No|
|Catalog (Project)||The name of your BigQuery project. This project is the default project the Google BigQuery Connector queries against. The Google BigQuery Connector supports multiple catalogs, the equivalent of Google BigQuery projects.||Yes|
|Minimum TLS||The minimum version of TLS allowed for encrypting connections. For example, if TLS 1.1 is specified, TLS 1.0 cannot be used. Default value is TLS 1.2.||Yes|
Connecting through proxy properties
If you are connecting through a proxy server you must provide authentication information for the proxy server.
|Use Proxy Server||Selected when connecting through a proxy server.|
|Proxy Host||Sets the proxy server's host name or IP address.|
|Proxy Port||Sets the number of the TCP port that the proxy server uses.|
|Proxy Username||Sets the username for accessing the proxy server.|
|Proxy Password||Sets the password for the username used to access the proxy server.|
These options are only available on Qlik Sense Enterprise on Windows.
|Use System Trust Store||Use the SSL certificate located in the standard system location used for storing trusted certificates.||Yes, if certificate is stored in the standard system location.|
|Trusted certificate path||Sets the path to the Windows trusted storage certificate.||Yes|
Use this dropdown to select Standard SQL or Legacy SQL.
Standard SQL: is compliant with the SQL 2011 standard. It supports querying nested and repeated data. For more information, see SQL Reference.
Legacy SQL: Non-standard SQL dialect previously named BigQuery SQL. Legacy SQL was used prior to Google BigQuery 2.0. For more information, see Query Reference.
|Rows Per Block||Sets the maximum number of rows to fetch for each data request.|
|Default String Column Length||Sets the maximum number of characters that can be contained in string columns.|
Large Results Options
|Allow Large Result Sets||This option specifies the connector's response to query results larger than 128MB when using Legacy SQL.||No|
|Dataset Name For Large Result Sets||The ID of the existing BigQuery dataset that you want to use to store temporary tables for large result sets. Only specify a value for this option if you want to enable support for large result sets.||No|
|Query timeout||Amount of time before a data load query times out. Can be set from 30 seconds to 65535 seconds. Default is 30 seconds.|
|Retry timeout||The length of time, in seconds, for which the connector retries a failed API call before timing out. The specified value must be an integer. A value of 0 indicates no timeout. Default value is 300.|
Load optimization settings
|Max String Length|
Maximum length of string fields. This can be set from 256 to 16384 characters. The default value is 4096. Setting this value close to the maximum length may improve load times, as it limits the need to allocate unnecessary resources. If a string is longer than the set value, it will be truncated, and the exceeding characters will not be loaded.
Name of the custom property. You can add additional properties by clicking the .
Value of the property.