DSS can connect to Google BigQuery through a JDBC driver developed by Simba.
- Java 8 is required
- Creating external datasets targeting BigQuery projects
- Reading data across all datasets and tables.
- Reading all BigQuery data types
- SQL notebook for interactive querying
- SQL query datasets
- SQL query recipes, with inputs and outputs in BigQuery
- Sync query recipes, with output in BigQuery and input in either Google Cloud Storage or BigQuery.
- All visual recipes (Group, Join, VStack, Window, Filter executed in BigQuery), with inputs and outputs in BigQuery
- Charts with DSS and In-Database engine modes.
- INSERT / CREATE statements in SQL notebook
- SQL script recipes
- BigQuery time partitioning experimental feature
- BigQuery wildcard tables
- BigQuery BYTES, DATETIME, DATE, TIME, ARRAY, STRUCT data types
Installing the JDBC driver¶
- The JDBC Driver can be downloaded from https://cloud.google.com/bigquery/partners/simba-drivers/
- Choose the “JDBC 4.2-compatible” download (beware: do not choose ODBC but JDBC)
- Unzip the downloaded file
The JDBC driver is made of many JAR files, all of which are contained in the Zip file.
- Copy all of the JAR files to the
- Restart DSS
Connecting to BigQuery¶
DSS connects to BigQuery using Service Account-based authentication.
- You first need to create a Google Service Account
- Create a private key for this account, and download the corresponding JSON file.
- Upload the JSON file somewhere on the DSS server.
In the connection settings, in the Secret key field, enter the absolute path (on the DSS server) to the credentials JSON file.
Alternatively, you can directly enter the content of the JSON file in the Secret key field to avoid storing the file on the server. Keep in mind that in this latter case, any DSS administrator will be able to see the content of this private file.
Finally we recommend that you add an Advanced JDBC property:
- Value: 180