Copyright | (c) 2013-2023 Brendan Hay |
---|---|
License | Mozilla Public License, v. 2.0. |
Maintainer | Brendan Hay |
Stability | auto-generated |
Portability | non-portable (GHC extensions) |
Safe Haskell | Safe-Inferred |
Language | Haskell2010 |
Synopsis
- putEvents_userId :: Lens' PutEvents (Maybe Text)
- putEvents_trackingId :: Lens' PutEvents Text
- putEvents_sessionId :: Lens' PutEvents Text
- putEvents_eventList :: Lens' PutEvents (NonEmpty Event)
- putItems_datasetArn :: Lens' PutItems Text
- putItems_items :: Lens' PutItems (NonEmpty Item)
- putUsers_datasetArn :: Lens' PutUsers Text
- putUsers_users :: Lens' PutUsers (NonEmpty User)
- event_eventId :: Lens' Event (Maybe Text)
- event_eventValue :: Lens' Event (Maybe Double)
- event_impression :: Lens' Event (Maybe (NonEmpty Text))
- event_itemId :: Lens' Event (Maybe Text)
- event_metricAttribution :: Lens' Event (Maybe MetricAttribution)
- event_properties :: Lens' Event (Maybe Text)
- event_recommendationId :: Lens' Event (Maybe Text)
- event_eventType :: Lens' Event Text
- event_sentAt :: Lens' Event UTCTime
- item_properties :: Lens' Item (Maybe Text)
- item_itemId :: Lens' Item Text
- metricAttribution_eventAttributionSource :: Lens' MetricAttribution Text
- user_properties :: Lens' User (Maybe Text)
- user_userId :: Lens' User Text
Operations
PutEvents
putEvents_trackingId :: Lens' PutEvents Text Source #
The tracking ID for the event. The ID is generated by a call to the CreateEventTracker API.
putEvents_sessionId :: Lens' PutEvents Text Source #
The session ID associated with the user's visit. Your application generates the sessionId when a user first visits your website or uses your application. Amazon Personalize uses the sessionId to associate events with the user before they log in. For more information, see Recording Events.
putEvents_eventList :: Lens' PutEvents (NonEmpty Event) Source #
A list of event data from the session.
PutItems
putItems_datasetArn :: Lens' PutItems Text Source #
The Amazon Resource Name (ARN) of the Items dataset you are adding the item or items to.
PutUsers
putUsers_datasetArn :: Lens' PutUsers Text Source #
The Amazon Resource Name (ARN) of the Users dataset you are adding the user or users to.
Types
Event
event_eventId :: Lens' Event (Maybe Text) Source #
An ID associated with the event. If an event ID is not provided, Amazon Personalize generates a unique ID for the event. An event ID is not used as an input to the model. Amazon Personalize uses the event ID to distinquish unique events. Any subsequent events after the first with the same event ID are not used in model training.
event_eventValue :: Lens' Event (Maybe Double) Source #
The event value that corresponds to the EVENT_VALUE
field of the
Interactions schema.
event_impression :: Lens' Event (Maybe (NonEmpty Text)) Source #
A list of item IDs that represents the sequence of items you have shown
the user. For example, ["itemId1", "itemId2", "itemId3"]
.
Provide a list of items to manually record impressions data for an
event. For more information on recording impressions data, see
Recording impressions data.
event_itemId :: Lens' Event (Maybe Text) Source #
The item ID key that corresponds to the ITEM_ID
field of the
Interactions schema.
event_metricAttribution :: Lens' Event (Maybe MetricAttribution) Source #
Contains information about the metric attribution associated with an event. For more information about metric attributions, see Measuring impact of recommendations.
event_properties :: Lens' Event (Maybe Text) Source #
A string map of event-specific data that you might choose to record. For
example, if a user rates a movie on your site, other than movie ID
(itemId
) and rating (eventValue
) , you might also send the number of
movie ratings made by the user.
Each item in the map consists of a key-value pair. For example,
{"numberOfRatings": "12"}
The keys use camel case names that match the fields in the Interactions
schema. In the above example, the numberOfRatings
would match the
'NUMBER_OF_RATINGS' field defined in the Interactions schema.
event_recommendationId :: Lens' Event (Maybe Text) Source #
The ID of the list of recommendations that contains the item the user
interacted with. Provide a recommendationId
to have Amazon Personalize
implicitly record the recommendations you show your user as impressions
data. Or provide a recommendationId
if you use a metric attribution to
measure the impact of recommendations.
For more information on recording impressions data, see Recording impressions data. For more information on creating a metric attribution see Measuring impact of recommendations.
event_eventType :: Lens' Event Text Source #
The type of event, such as click or download. This property corresponds
to the EVENT_TYPE
field of your Interactions schema and depends on the
types of events you are tracking.
event_sentAt :: Lens' Event UTCTime Source #
The timestamp (in Unix time) on the client side when the event occurred.
Item
item_properties :: Lens' Item (Maybe Text) Source #
A string map of item-specific metadata. Each element in the map consists
of a key-value pair. For example, {"numberOfRatings": "12"}
.
The keys use camel case names that match the fields in the schema for
the Items dataset. In the previous example, the numberOfRatings
matches the 'NUMBER_OF_RATINGS' field defined in the Items schema. For
categorical string data, to include multiple categories for a single
item, separate each category with a pipe separator (|
). For example,
\"Horror|Action\"
.
MetricAttribution
metricAttribution_eventAttributionSource :: Lens' MetricAttribution Text Source #
The source of the event, such as a third party.
User
user_properties :: Lens' User (Maybe Text) Source #
A string map of user-specific metadata. Each element in the map consists
of a key-value pair. For example, {"numberOfVideosWatched": "45"}
.
The keys use camel case names that match the fields in the schema for
the Users dataset. In the previous example, the numberOfVideosWatched
matches the 'NUMBER_OF_VIDEOS_WATCHED' field defined in the Users
schema. For categorical string data, to include multiple categories for
a single user, separate each category with a pipe separator (|
). For
example, \"Member|Frequent shopper\"
.