You can start your feed import by navigating to the import recommendations overview page and selecting the appropriate import type.
You can import data from a data warehouse using one of the following methods:
- Databricks – Connect to Databricks and import data from a specified database and table.
- Snowflake – Import data from Snowflake by providing account credentials, database, and schema.
- Google BigQuery – Fetch data from BigQuery using service account credentials and specifying the dataset and table.
Choose the appropriate method based on your data source and access preferences.
Left-side panel overview
- Source: Displays the data source for the import. Example: Google BigQuery.
- Destination: Specifies where the imported data will be directed, i.e., recommendation feeds in this case.
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Select recommendation type: (mandatory field)
- User-to-product: Imports recommendations based on user identifiers and related product IDs, ideal for personalized promotions.
- Product-to-product: Suggests related products based on user interactions, such as viewed or purchased items.
- Recommendation feed name: (mandatory field) Enter a name for the feed (minimum of 3 characters).
- Description: Add details to describe the recommendation feed.
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Notification preferences:
- To: Specify email IDs to receive notifications about the import task.
- CC: Add additional recipients to be copied on notifications.
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Settings:
- Notify - any status: Sends notifications for all import task statuses.
- Notify - If more than [X]% of records fail: Sends alerts when failures exceed the defined threshold (e.g., 70%).
Source configuration
To configure the data source for import:
- Select an adapter – Choose the appropriate adapter for your import.
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Import from – Choose between:
- Table – Selecting this option reveals a Table dropdown where you can choose the specific table to import.
- View – Selecting this option reveals a View dropdown where you can choose the appropriate database view.
- Click Continue to proceed.
Data configuration & validation
- Sample Data: Displays 10 records fetched from the source to assist in field mapping.
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Field Mapping:
- Map the Source Attribute Name to the corresponding Destination Attribute Name and specify the Destination Data Type.
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Mapping Instructions:
- Only columns mapped to a destination attribute will be imported.
- Map Floating point numeric data types from the source to Decimal in Blueshift.
- Example: For events like purchase, add_to_cart, wishlist, or view, map a column to product_ids (required for events interacting with product catalogs).
- Ensure one column is mapped to a customer identifier, such as customer_id, email, my_custom_id, cookie, device_id, or my_external_id.
Data Quality Check:
- Use Check Data Quality to validate field mappings.
- View data quality percentages, errors, and hints for corrections in the modal.
- Adjust mappings as needed.
Test Run:
- Click Test Run to validate with up to 10 records.
- The modal displays source data alongside mapped JSON.
- Update mappings and re-run tests if necessary.
- Next Steps: Address all validation issues and click Continue to proceed with the import.
Additional configuration
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Type of import:
- Full import – Imports the entire table or view for each iteration.
- Incremental import – Imports only new or updated data for each iteration.
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Difference identification (for incremental import):
- Select Time or Number Based to identify incremental records using an attribute from the source data.
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Difference identifier (for incremental import):
- Choose the attribute used to track incremental changes (e.g.,
joined_at
).
- Choose the attribute used to track incremental changes (e.g.,
Click Continue to proceed.
Scheduling and launching the import task
- Select the Start Date using the date picker.
- Check 'Is it a recurring data import?' to enable recurring imports.
- Choose when the task ends:
- 'Never' for an indefinite schedule.
- 'At some time' to set an End Date.
- Set the execution frequency (e.g., every 15 minutes).
- Scheduling options: Minutes, Hourly, Daily, Weekly, and Monthly.
Review the setup and the top right corner of the screen:
- Click the Save button to save the task.
- Click the Launch button to start the task.
Import errors and possible causes
Some records may not be imported due to errors. Below are common errors and their possible causes:
Error message | Possible cause |
---|---|
Firefly resource not found error={"{\"errors\": [\"attribute_value_not_found\"]}"} | An item in the product_ids list is not present in the catalog. |
Firefly resource not found error={"{\"errors\": [\"product_id_not_found\"]}"} | The source_product_id itself is not in the catalog. |
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