Snowflake data output
This article provides an introduction to Snowflake along with a guide on how to create a Snowflake data output using Upsolver.
Last updated
This article provides an introduction to Snowflake along with a guide on how to create a Snowflake data output using Upsolver.
Last updated
1. Go to the Outputs page and click New.
2. Select Snowflake as your output type.
3. Name your output and select your Data Sources.
4. Select New to create a new table or Existing to output to an existing table. Then click Next.
If outputting to an existing table, complete the database options as prompted before clicking Next again. If necessary, create a new Snowflake connection.
Click Properties to review this output's properties. See: Output properties
5. Click the information iconin the fields tree to view information about a field. The following will be displayed:
How many of the events in this data source include this field, expressed as a percentage (e.g. 20.81%).
The percentage distribution of the field values. These distribution values can be exported by clicking Export.
6. Click the information iconnext to a hierarchy element (such as the overall data) to review the following metrics:
The number of fields in the selected hierarchy.
7. Click the plus iconin the fields tree to add a field from the data source to your output. This will be reflected under the Data Source Field in the Schema tab.
If required, modify the column name under Schema Column.
Additionally, click the gear iconto modify other details such as Column Type and Size.
To remove a field, click the unlink iconto clear the column mapping then the garbage iconto drop the column.
Alternatively, add columns by clicking Add New Column.
Provide a Column Name as well as select a Column Type.
If desired, give the column a Default Value then click Save.
This column will now be added under the Data Source Field in the Schema tab.
Toggle from UI to SQL at any point to view the corresponding SQL code for your selected output.
You can also edit your output directly in SQL. See: Transform with SQL
8. Add any required calculated fields and review them in the Calculated Fields tab. See: Adding calculated fields
9. Add any required lookups and review them under the Calculated Fields tab.
10. Through the Filters tab, add a filter like WHERE in SQL to the data source.
See: Adding filters
11. Click Make Aggregated to turn the output into an aggregated output. Read the warning before clicking OK and then add the required aggregation. This aggregation field will then be added to the Schema tab. See: Aggregation functions
12. In the Aggregation Calculated Fields area under the Calculated Fields tab, add any required calculated fields on aggregations. See: Functions, Aggregation functions
13. To keep only the latest event per upsert key, click More > Manage Upserts then select the following:
Keys: A unique key identifying a row in the table.
Deletions: The delete key (events with the value true in their deletion key field will be deleted).
See: Data types and features, How do upserts work?
Click Preview at any time to view a preview of your current output.
14. Click Run and fill out the following fields:
Snowflake Connection: How to create a new Snowflake connection
Schema
Table Name
Intermediate Storage Location: Where Upsolver will store the intermediate bulk files which it will then load into Snowflake using the copy into command
See: Running an output, Database output options
14. Click Next and complete the following:
Select the compute cluster to run the calculation on. Alternatively, click the drop-down and create a new compute cluster.
15. Finally, click Deploy to run the output. It will show as Running in the output panel and is now live in production and consumes compute resources.
You have now successfully outputted your table to your Snowflake database.
