Guidelines and requirements
When creating a filter expression, note the following guidelines and requirements:
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You can't use filters to include or exclude items based on unstructured textual item metadata such as product descriptions.
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If you are filtering based on item or action interactions data, you can only filter based on event type. You can't filter based on other interaction metadata, such as contextual metadata.
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Amazon Personalize ignores case only when matching event types.
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You can't use Item Interaction and Item datasets in one expression. To create a filter that filters by Interaction and then Item datasets (or the opposite), you must chain two or more expressions together. For more information, see Combining multiple expressions.
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You can't use Item interaction and Action datasets in one expression. To create a filter that filters by Item interaction and then Action datasets (or the opposite), you must chain two or more expressions together. For more information, see Combining multiple expressions.
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You can't use item interactions filters with the Item-Attribute-Affinity recipe.
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You can't create filter expressions that filter using values with a boolean type in your schema. To filter based on boolean values, use a schema with a field of type String and use the values
"True"
and"False"
in your data. Or you can use type int or long and values0
and1
. -
The maximum number of distinct dataset fields for a filter, either in one expression or across multiple expressions chained together, is 5. The maximum number of distinct dataset fields across all filters in a dataset group is 10.
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You can apply a filter with the CurrentItem element only if your domain use case or custom recipe generates related items recommendations, such as the Similar-Items recipe or the More Like X domain use case.
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You can't use placeholder parameters in a filter expression that uses the NOT_IN operator. Instead, use the IN operator and use the opposite Action. For example, use Include instead of Exclude (or the reverse).
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You can't create filters that filter based on
Action expiration timestamp
andRepeat frequency
data. Amazon Personalize automatically filters action recommendations based on this data.