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Databricks

How to connect Databricks to Count.

Click "Connect a database"

Enter your connection details

You'll need:
  • Hostname and path of your Databricks cluster
  • an Access token that has permissions to run queries there
You may also need to ensure that your firewall accepts requests from the following IP addresses:
34.107.75.117
35.198.189.90
35.234.110.177
Use this guide to obtain your hostname and path Use this guide to obtain an access token

Connect

Once you hit Connect you will see your connection details including a full list of tables accessible with this connection.
Use Projects to manage which users have access to which tables.

Troubleshooting

The most common issue common issue when connecting to a Databricks cluster is that the warehouse is unresponsive if it has stopped due to inactivity. Count's connecting and querying logic will retry every 10 seconds for 3 minutes. If Count is still unable to connect to your cluster after this time, a 503 error will return. Ensure that your warehouse is running and available to accept connections from the Count IP addresses (see above) and retry the connection in Count.
If you are having trouble connecting, reach out to us to schedule a support session

Limitations

BigInt

The BigInt data type in Databricks can accommodate integers in the range -2^63 -> 2^63 -1 . Due to a limitation in the Databricks client, Count can accommodate a reduced range of -2^53 -> 2^53 -1 for this data type. Values outside of this reduced range will be displayed as null values.

VALUES clause

Count uses a reduced parse to determine which cells are referenced in your SQL statements. Databrick's SELECT statement and querying syntax is more flexible than those of other databases. As a result, there is an unresolvable ambiguity in Count's reduced parse for statements of the form
SELECT * FROM VALUES 1, 2, 3
Running a SQL statement similar to this will result in an error similar to "Unexpected number", "Unexpected literal", etc. The workaround for this issue is to parenthetise the row values in the VALUES clause, e.g.
SELECT * FROM VALUES (1), (2), (3)
Last modified 5mo ago