Class PredictionServiceClient (0.8.9)

Version 0.8.9

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public class PredictionServiceClient implements BackgroundResource

Service Description: Service for making recommendation prediction.

This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:

 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   PlacementName name =
       PlacementName.of("[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]");
   UserEvent userEvent = UserEvent.newBuilder().build();
   for (Map.Entry<String, Value> element :
       predictionServiceClient.predict(name, userEvent).iterateAll()) {
     // doThingsWith(element);
   }
 }
 

Note: close() needs to be called on the PredictionServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().

The surface of this class includes several types of Java methods for each of the API's methods:

1. A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
2. A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
3. A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.

See the individual methods for example code.

Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.

This class can be customized by passing in a custom instance of PredictionServiceSettings to create(). For example:

To customize credentials:

 PredictionServiceSettings predictionServiceSettings =
     PredictionServiceSettings.newBuilder()
         .setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
         .build();
 PredictionServiceClient predictionServiceClient =
     PredictionServiceClient.create(predictionServiceSettings);
 

To customize the endpoint:

 PredictionServiceSettings predictionServiceSettings =
     PredictionServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
 PredictionServiceClient predictionServiceClient =
     PredictionServiceClient.create(predictionServiceSettings);
 

Please refer to the GitHub repository's samples for more quickstart code snippets.

Inheritance

java.lang.Object > PredictionServiceClient

Implements

BackgroundResource

Inherited Members

Object.clone()

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.toString()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

create()

public static final PredictionServiceClient create()

Constructs an instance of PredictionServiceClient with default settings.

Returns

Type	Description
PredictionServiceClient

Exceptions

Type	Description
IOException

create(PredictionServiceSettings settings)

public static final PredictionServiceClient create(PredictionServiceSettings settings)

Constructs an instance of PredictionServiceClient, using the given settings. The channels are created based on the settings passed in, or defaults for any settings that are not set.

Parameter

Name	Description
settings	PredictionServiceSettings

Returns

Type	Description
PredictionServiceClient

Exceptions

Type	Description
IOException

create(PredictionServiceStub stub)

public static final PredictionServiceClient create(PredictionServiceStub stub)

Constructs an instance of PredictionServiceClient, using the given stub for making calls. This is for advanced usage - prefer using create(PredictionServiceSettings).

Parameter

Name	Description
stub	PredictionServiceStub

Returns

Type	Description
PredictionServiceClient

Constructors

PredictionServiceClient(PredictionServiceSettings settings)

protected PredictionServiceClient(PredictionServiceSettings settings)

Constructs an instance of PredictionServiceClient, using the given settings. This is protected so that it is easy to make a subclass, but otherwise, the static factory methods should be preferred.

Parameter

Name	Description
settings	PredictionServiceSettings

PredictionServiceClient(PredictionServiceStub stub)

protected PredictionServiceClient(PredictionServiceStub stub)

Parameter

Name	Description
stub	PredictionServiceStub

Methods

awaitTermination(long duration, TimeUnit unit)

public boolean awaitTermination(long duration, TimeUnit unit)

Parameters

Name	Description
duration	long
unit	TimeUnit

Returns

Type	Description
boolean

Exceptions

Type	Description
InterruptedException

close()

public final void close()

getSettings()

public final PredictionServiceSettings getSettings()

Returns

Type	Description
PredictionServiceSettings

getStub()

public PredictionServiceStub getStub()

Returns

Type	Description
PredictionServiceStub

isShutdown()

public boolean isShutdown()

Returns

Type	Description
boolean

isTerminated()

public boolean isTerminated()

Returns

Type	Description
boolean

predict(PlacementName name, UserEvent userEvent)

public final PredictionServiceClient.PredictPagedResponse predict(PlacementName name, UserEvent userEvent)

Makes a recommendation prediction. If using API Key based authentication, the API Key must be registered using the PredictionApiKeyRegistry service. Learn more.

Sample code:

 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   PlacementName name =
       PlacementName.of("[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]");
   UserEvent userEvent = UserEvent.newBuilder().build();
   for (Map.Entry<String, Value> element :
       predictionServiceClient.predict(name, userEvent).iterateAll()) {
     // doThingsWith(element);
   }
 }
 

Parameters

Name	Description
name	PlacementName Required. Full resource name of the format: {name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*} The id of the recommendation engine placement. This id is used to identify the set of models that will be used to make the prediction. We currently support three placements with the following IDs by default: shopping_cart: Predicts items frequently bought together with one or more catalog items in the same shopping session. Commonly displayed after add-to-cart events, on product detail pages, or on the shopping cart page. home_page: Predicts the next product that a user will most likely engage with or purchase based on the shopping or viewing history of the specified userId or visitorId. For example - Recommendations for you. product_detail: Predicts the next product that a user will most likely engage with or purchase. The prediction is based on the shopping or viewing history of the specified userId or visitorId and its relevance to a specified CatalogItem. Typically used on product detail pages. For example - More items like this. recently_viewed_default: Returns up to 75 items recently viewed by the specified userId or visitorId, most recent ones first. Returns nothing if neither of them has viewed any items yet. For example - Recently viewed. The full list of available placements can be seen at https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard
userEvent	UserEvent Required. Context about the user, what they are looking at and what action they took to trigger the predict request. Note that this user event detail won't be ingested to userEvent logs. Thus, a separate userEvent write request is required for event logging.

Returns

Type	Description
PredictionServiceClient.PredictPagedResponse

predict(PredictRequest request)

public final PredictionServiceClient.PredictPagedResponse predict(PredictRequest request)

Makes a recommendation prediction. If using API Key based authentication, the API Key must be registered using the PredictionApiKeyRegistry service. Learn more.

Sample code:

 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   PredictRequest request =
       PredictRequest.newBuilder()
           .setName(
               PlacementName.of(
                       "[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]")
                   .toString())
           .setUserEvent(UserEvent.newBuilder().build())
           .setPageSize(883849137)
           .setPageToken("pageToken873572522")
           .setFilter("filter-1274492040")
           .setDryRun(true)
           .putAllParams(new HashMap<String, Value>())
           .putAllLabels(new HashMap<String, String>())
           .build();
   for (Map.Entry<String, Value> element :
       predictionServiceClient.predict(request).iterateAll()) {
     // doThingsWith(element);
   }
 }
 

Parameter

Name	Description
request	PredictRequest The request object containing all of the parameters for the API call.

Returns

Type	Description
PredictionServiceClient.PredictPagedResponse

predict(String name, UserEvent userEvent)

public final PredictionServiceClient.PredictPagedResponse predict(String name, UserEvent userEvent)

Makes a recommendation prediction. If using API Key based authentication, the API Key must be registered using the PredictionApiKeyRegistry service. Learn more.

Sample code:

 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   String name =
       PlacementName.of("[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]")
           .toString();
   UserEvent userEvent = UserEvent.newBuilder().build();
   for (Map.Entry<String, Value> element :
       predictionServiceClient.predict(name, userEvent).iterateAll()) {
     // doThingsWith(element);
   }
 }
 

Parameters

Name	Description
name	String Required. Full resource name of the format: {name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*} The id of the recommendation engine placement. This id is used to identify the set of models that will be used to make the prediction. We currently support three placements with the following IDs by default: shopping_cart: Predicts items frequently bought together with one or more catalog items in the same shopping session. Commonly displayed after add-to-cart events, on product detail pages, or on the shopping cart page. home_page: Predicts the next product that a user will most likely engage with or purchase based on the shopping or viewing history of the specified userId or visitorId. For example - Recommendations for you. product_detail: Predicts the next product that a user will most likely engage with or purchase. The prediction is based on the shopping or viewing history of the specified userId or visitorId and its relevance to a specified CatalogItem. Typically used on product detail pages. For example - More items like this. recently_viewed_default: Returns up to 75 items recently viewed by the specified userId or visitorId, most recent ones first. Returns nothing if neither of them has viewed any items yet. For example - Recently viewed. The full list of available placements can be seen at https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard
userEvent	UserEvent Required. Context about the user, what they are looking at and what action they took to trigger the predict request. Note that this user event detail won't be ingested to userEvent logs. Thus, a separate userEvent write request is required for event logging.

Returns

Type	Description
PredictionServiceClient.PredictPagedResponse

predictCallable()

public final UnaryCallable<PredictRequest,PredictResponse> predictCallable()

Makes a recommendation prediction. If using API Key based authentication, the API Key must be registered using the PredictionApiKeyRegistry service. Learn more.

Sample code:

 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   PredictRequest request =
       PredictRequest.newBuilder()
           .setName(
               PlacementName.of(
                       "[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]")
                   .toString())
           .setUserEvent(UserEvent.newBuilder().build())
           .setPageSize(883849137)
           .setPageToken("pageToken873572522")
           .setFilter("filter-1274492040")
           .setDryRun(true)
           .putAllParams(new HashMap<String, Value>())
           .putAllLabels(new HashMap<String, String>())
           .build();
   while (true) {
     PredictResponse response = predictionServiceClient.predictCallable().call(request);
     for (Map.Entry<String, Value> element : response.getResponsesList()) {
       // doThingsWith(element);
     }
     String nextPageToken = response.getNextPageToken();
     if (!Strings.isNullOrEmpty(nextPageToken)) {
       request = request.toBuilder().setPageToken(nextPageToken).build();
     } else {
       break;
     }
   }
 }
 

Returns

Type	Description
UnaryCallable<PredictRequest,PredictResponse>

predictPagedCallable()

public final UnaryCallable<PredictRequest,PredictionServiceClient.PredictPagedResponse> predictPagedCallable()

Makes a recommendation prediction. If using API Key based authentication, the API Key must be registered using the PredictionApiKeyRegistry service. Learn more.

Sample code:

 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   PredictRequest request =
       PredictRequest.newBuilder()
           .setName(
               PlacementName.of(
                       "[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]")
                   .toString())
           .setUserEvent(UserEvent.newBuilder().build())
           .setPageSize(883849137)
           .setPageToken("pageToken873572522")
           .setFilter("filter-1274492040")
           .setDryRun(true)
           .putAllParams(new HashMap<String, Value>())
           .putAllLabels(new HashMap<String, String>())
           .build();
   ApiFuture<Map.Entry<String, Value>> future =
       predictionServiceClient.predictPagedCallable().futureCall(request);
   // Do something.
   for (Map.Entry<String, Value> element : future.get().iterateAll()) {
     // doThingsWith(element);
   }
 }
 

Returns

Type	Description
UnaryCallable<PredictRequest,PredictPagedResponse>

shutdown()

public void shutdown()

shutdownNow()

public void shutdownNow()