public abstract class RecommendationAIImportUserEvents extends PTransform<PCollection<KV<java.lang.String,com.google.api.client.json.GenericJson>>,PCollectionTuple>
PTransform connecting to the Recommendations AI API
 (https://cloud.google.com/recommendations) and creating UserEvents. *
 Batch size defines how many items are at once per batch (max: 5000).
The transform consumes KV of String and GenericJsons (assumed to be
 the user event id as key and contents as value) and outputs a PCollectionTuple which will contain
 the successfully created and failed user events.
 
It is possible to provide a catalog name to which you want to add the catalog item (defaults to "default_catalog"). It is possible to provide a event store to which you want to add the user event (defaults to "default_event_store").
| Modifier and Type | Field and Description | 
|---|---|
static TupleTag<com.google.cloud.recommendationengine.v1beta1.UserEvent> | 
FAILURE_TAG  | 
static TupleTag<com.google.cloud.recommendationengine.v1beta1.UserEvent> | 
SUCCESS_TAG  | 
annotations, name, resourceHints| Constructor and Description | 
|---|
RecommendationAIImportUserEvents()  | 
| Modifier and Type | Method and Description | 
|---|---|
abstract java.lang.Integer | 
batchSize()  | 
abstract @Nullable java.lang.String | 
catalogName()  | 
abstract @Nullable java.lang.String | 
eventStore()  | 
PCollectionTuple | 
expand(PCollection<KV<java.lang.String,com.google.api.client.json.GenericJson>> input)
The transform converts the contents of input PCollection into  
UserEvents and then calls
 the Recommendation AI service to create the user event. | 
abstract Duration | 
maxBufferingDuration()  | 
abstract @Nullable java.lang.String | 
projectId()  | 
RecommendationAIImportUserEvents | 
withBatchSize(java.lang.Integer batchSize)  | 
RecommendationAIImportUserEvents | 
withCatalogName(java.lang.String catalogName)  | 
RecommendationAIImportUserEvents | 
withEventStore(java.lang.String eventStore)  | 
RecommendationAIImportUserEvents | 
withProjectId(java.lang.String projectId)  | 
addAnnotation, compose, compose, getAdditionalInputs, getAnnotations, getDefaultOutputCoder, getDefaultOutputCoder, getDefaultOutputCoder, getKindString, getName, getResourceHints, populateDisplayData, setResourceHints, toString, validate, validatepublic static final TupleTag<com.google.cloud.recommendationengine.v1beta1.UserEvent> SUCCESS_TAG
public static final TupleTag<com.google.cloud.recommendationengine.v1beta1.UserEvent> FAILURE_TAG
public abstract @Nullable java.lang.String projectId()
public abstract @Nullable java.lang.String catalogName()
public abstract @Nullable java.lang.String eventStore()
public abstract java.lang.Integer batchSize()
public abstract Duration maxBufferingDuration()
public RecommendationAIImportUserEvents withProjectId(java.lang.String projectId)
public RecommendationAIImportUserEvents withCatalogName(java.lang.String catalogName)
public RecommendationAIImportUserEvents withEventStore(java.lang.String eventStore)
public RecommendationAIImportUserEvents withBatchSize(java.lang.Integer batchSize)
public PCollectionTuple expand(PCollection<KV<java.lang.String,com.google.api.client.json.GenericJson>> input)
UserEvents and then calls
 the Recommendation AI service to create the user event.expand in class PTransform<PCollection<KV<java.lang.String,com.google.api.client.json.GenericJson>>,PCollectionTuple>input - input PCollection