This page will walk through the setup of BigQuery in K using the direct connect method
Scope | Included | Comments |
---|---|---|
Metadata | YES |
|
Lineage | YES |
|
Usage | YES |
|
Sensitive Data Scanner | NO | Sensitive Scanner does not currently support Big Query. |
Step 1) Setup a Google Cloud Service Account
This step is performed by the Google Cloud Admin
Create a Service Account by going to the Google Cloud Admin or clicking on this link
Give the Service Account a name (e.g. KADA BQ Integration)
Select the Projects that include the BigQuery instance(s) that you want to catalog
Click Save
Create a Service Token
Click on the Service Account
Select the Keys tab. Click on Create new key
Select the JSON option. After clicking ‘CREATE’, the JSON file will automatically download to your device. Provide this to the user(s) that will complete the next steps
Add grants on the Service Account by going to IAM page or clicking on this link
Click on ADD
Add the Service Account to the ‘New principals’ field.
Grant the following roles this principal as shown in the following screenshot.
BigQuery Job User
BigQuery Metadata Viewer
BigQuery Read Session User
BigQuery Resource Viewer
Click SAVE
Step 2) Connecting K to BigQuery
Select Platform Settings in the side bar
In the pop-out side panel, under Integrations click on Sources
Click Add Source and select BigQuery
Select Direct Connect
Fill in the Source Settings and click Save & Next
Name: The name you wish to give your BigQuery Service in K
Host: Add your BigQuery Host Name (e.g. cloud.google.com)
Region: Select the region your Service is located in (check with your admin if you are unsure)
Add the Connection details and click Save & Next when connection is successful
Credentials: Copy the content of the Credentials.json created in Step 1
Test your connection and click Save
Select the Databases you wish to load into K and click Finish Setup
All databases will be listed. If you have a lot of databases this may take a few seconds to load
Return to the Sources page and locate the new BigQuery source that you loaded
Click on the clock icon to select Edit Schedule and set your preferred schedule for the BigQuery load
Note that scheduling a source can take up to 15 minutes to propagate the change.
Step 3) Manually run an ad hoc load to test BigQuery setup
Next to your new Source, click on the Run manual load icon
Confirm how your want the source to be loaded
After the source load is triggered, a pop up bar will appear taking you to the Monitor tab in the Batch Manager page. This is the usual page you visit to view the progress of source loads
A manual source load will also require a manual run of
DAILY
GATHER_METRICS_AND_STATS
To load all metrics and indexes with the manually loaded metadata. These can be found in the Batch Manager page
Troubleshooting failed loads
If the job failed at the extraction step
Check the error. Contact KADA Support if required.
Rerun the source job
If the job failed at the load step, the landing folder failed directory will contain the file with issues.
Find the bad record and fix the file
Rerun the source job