Importing individual records into an Amazon Personalize dataset
After you have complete Creating a schema and a dataset, you can import individual records, including item interactions, users, items, actions, or action interactions into an existing dataset. Importing data individually allows you to add small batches of records to your Amazon Personalize datasets as your catalog grows. You can import up to 10 records per individual import operation.
If you import an item, user, or action with the same ID as a record that's already in your dataset, Amazon Personalize replaces it with the new record. If you record two item interaction or action interaction events with exactly the same timestamp and identical properties, Amazon Personalize keeps only one of the events.
If you use Apache Kafka, you can use the Kafka connector for Amazon Personalize to stream data in real time to Amazon Personalize.
For information see Kafka Connector for Amazon Personalize
If you have a large amount of historical records, we recommend that you first import data in bulk and then import data individually as necessary. See Importing bulk data into Amazon Personalize with a dataset import job.
Filter updates for individual record imports
Amazon Personalize updates any filters you created in the dataset group with your new interaction, item, and user data within 20 minutes from the last individual import. This update allows your campaigns to use your most recent data when filtering recommendations for your users.
If you already created a recommender or deployed a custom solution version with a campaign, how new individual records influence recommendations depends on the domain use case or recipe that you use. For more information, see Updating data in datasets after training.
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