Initialize Java SDK

Use the Optimizely Builder to initialize the Java SDK and instantiate an instance of the Optimizely client class that exposes API methods like the Decide methods.

Version

4.0.0-beta and higher

Description

The SDK provides a default implementation, but you may want to override the optional parameters for your production environments.

For example, you can override the defaults to:

• Set up an error handler and logger to catch issues.
• Manage network calls via a custom event dispatcher.
• Ensure sticky bucketing using your own User Profile Service.

Parameters

The table below lists the optional builder methods.

Returns

An instantiated instance of the Optimizely class

Example

The example below shows how to initialize the Optimizely Feature Experimentation Java SDK using the builder options.

Optimizely Feature Experimentation provides default implementations of HttpProjectConfigManager, BatchEventProcessor and AsyncEventHandler.

ProjectConfigManager configManager = HttpProjectConfigManager.builder()
    .withSdkKey(sdkKey)
    .withDatafile(datafile)
    .build();

EventHandler eventHandler = AsyncEventHandler.builder()
    .withQueueCapacity(20000)
    .withNumWorkers(1)
    .build();

EventProcessor batchProcessor = BatchEventProcessor.builder()
    .withBatchSize(50)
    .withEventHandler(eventHandler)
    .withFlushInterval(TimeUnit.MINUTES.toMillis(1))
    .build();

Optimizely optimizely = Optimizely.builder()
    .withConfigManager(configManager)
    .withEventProcessor(batchProcessor)
    .build();

Exceptions

HttpProjectConfigManager

Whenever the experiment configuration changes, the SDK uses automatic datafile management (ADM) to handle the change for you.

HttpProjectConfigManager is an implementation of the abstract PollingProjectConfigManager. The poll method is extended and makes an HTTP GET request to the configured URL to asynchronously download the project datafile and initialize an instance of the ProjectConfig.

By default, HttpProjectConfigManager blocks until the first successful datafile retrieval, up to a configurable timeout.

Set the frequency of the polling method and the blocking timeout with withPollingInterval() and withBlockingTimeout(), pulling the default values from global properties.

The example below shows how to initialize the HttpProjectConfigManager with builder options.

ProjectConfigManager projectConfigManager = HttpProjectConfigManager.builder()
    .withSdkKey(sdkKey)
    .withDatafile(datafile)
    .withPollingInterval(1, TimeUnit.MINUTES)
    .withBlockingTimeout(10, TimeUnit.SECONDS)
    .build();

SDK key

The SDK key composes the outbound HTTP request to the default datafile location on the Optimizely CDN.

Polling interval

The polling interval specifies a fixed delay between consecutive HTTP requests for the datafile.

Initial datafile

You can provide an initial datafile via the builder to bootstrap the ProjectConfigManager to use it immediately without blocking execution. The initial datafile also serves as a fallback datafile if an HTTP connection cannot be established. This is useful in mobile environments where internet connectivity is not guaranteed.

The preceding datafile is discarded after the first successful datafile poll.

Builder methods

You can use the following builder methods to customize the HttpProjectConfigManager configuration.

Advanced configuration

The following properties can be set to override the default configuration for HttpProjectConfigManager.

Update Config Notifications

The SDK triggers a notification signal after fetching a new datafile. To subscribe to these notifications, use Optimizely.addUpdateConfigNotificationHandler:

NotificationHandler<UpdateConfigNotification> handler = message ->
    System.out.println("Received new datafile configuration");
optimizely.addUpdateConfigNotificationHandler(handler);

Alternatively, you can add the handler directly to the NotificationCenter:

notificationCenter.addNotificationHandler(UpdateConfigNotification.class, handler);

AsyncEventHandler

AsyncEventHandler provides an implementation of EventHandler backed by a ThreadPoolExecutor. The event handler queues the triggered events from the SDK immediately as discrete tasks to the executor and processes them in submission order. --comment check my rewording

Each worker must make outbound HTTP requests to the Optimizely Feature Experimentation log endpoint for metrics tracking. Configure the default queue size and number of workers via global properties. Use AsyncEventHandler.Builder to override the default queue size and number of workers.

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Note

When using the Optimizely builder class, you must provide an implementation of the event handler as shown below. Otherwise, the Optimizely Feature Experimentation instance will default to a no-op event handler.

To use AsyncEventHandler, you must build an instance with AsyncEventHandler.Builder and pass the instance to the Optimizely.Builder.

You can also initialize the SDK with the OptimizelyFactory methods if you want to use the default AsyncEventHandler implementation.

EventHandler eventHandler = AsyncEventHandler.builder()
    .withQueueCapacity(10000)
    .withNumWorkers(5)
    .build();

Queue capacity

You can set the queue capacity to initialize the backing queue for the executor service. This drops an event if the queue fills up and logs an exception. Setting a higher queue value prevents event loss but uses more memory if the workers cannot keep up with the production rate.

Number of workers

The number of workers determines the number of threads the thread pool uses.

Builder methods

You can use the following builder methods to customize the AsyncEventHandler configuration.

Advanced configuration

You can set the following properties to override the default configuration for AsyncEventHandler.

BatchEventProcessor

The Optimizely Feature Experimentation Java SDK provides BatchEventProcessor, the default implementation of the EventProcessor interface, and batches events.

For more details and configuration options, refer to the article on event batching in Java.

EventHandler eventHandler = AsyncEventHandler.builder()
    .withQueueCapacity(10000)
    .withNumWorkers(5)
    .build();

EventProcessor batchProcessor = BatchEventProcessor.builder()
    .withBatchSize(50)
    .withEventHandler(eventHandler)
    .build();

Optimizely Properties

You can use an available optimizely.properties file within the runtime classpath to provide default values of a given Optimizely Feature Experimentation resource. Refer to the resource implementation for available configuration parameters.

An example optimizely.properties file:

http.project.config.manager.polling.duration = 1
http.project.config.manager.polling.unit = MINUTES

async.event.handler.queue.capacity = 20000
async.event.handler.num.workers = 5

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Note

You must have the Optimizely Data Platform Audience Targeting integration between Optimizely Data Platform (ODP) and Optimizely Feature Experimentation set up before being able to use odpManager.

Advanced Audience Targeting and odpManager are currently in beta. Contact your Customer Success Manager for more information or register now on Optimizely.com.

ODPManager

ODPManager contains all the logic supporting Optimizely Data Platform (ODP)-related features, including audience segments.

ODPSegmentManager

This module provides an interface to the remote ODP server for audience segment mappings.

It fetches all qualified segments for the given user context and returns them as a string array in the completion handler.

It also manages a segment's cache shared for all user contexts. The cache is in memory (not persistent), and rebooting the device or terminating the app resets it.

ODPEventManager

This module provides an interface to the remote ODP server for events.

It queues all pending events (persistent) and sends them (in batches of up to 10) to the ODP server when all resources are available, including network connection and ODP public key (in the SDK's datafile).

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Note

The Java SDK tries to dispatch all events (stored in a persistent queue and retried on recoverable errors) but does not guarantee completion.

// You must first enable the Advanced Audience Targeting integration
// before being able to calling ODPApiManager, ODPEventManager, and ODPSegmentManager.
ODPApiManager defaultODPApiManager = new DefaultODPApiManager();
ODPEventManager odpEventManager = new ODPEventManager(defaultODPApiManager);
ODPSegmentManager odpSegmentManager = new ODPSegmentManager(defaultODPApiManager);

ODPManager odpManager = ODPManager.builder()
     .withEventManager(odpEventManager) // Optional
     .withSegmentManager(odpSegmentManager) //Optional
     .withApiManager(defaultODPApiManager)
     .build();

Customize ODPApiManager

ODPApiManager is an interface, and its implementation requires the user to provide the functionality of the following methods:

public interface ODPApiManager {
    List<String> fetchQualifiedSegments(String apiKey, String apiEndpoint, String userKey, String userValue, Set<String> segmentsToCheck);

    Integer sendEvents(String apiKey, String apiEndpoint, String eventPayload);
}

Moreover, you can provide segmentFetchTimeoutMillis and eventDispatchTimeoutMillis in the constructor of DefaultODPApiManager.

int segmentFetchTimeoutMillis = 20000;    // 20,000 msecs = 20 secs
int eventDispatchTimeoutMillis = 20000;     // 20,000 msecs = 20 secs

ODPApiManager defaultODPApiManager = new DefaultODPApiManager(segmentFetchTimeoutMillis, eventDispatchTimeoutMillis)

Customize ODPEventManager

You can provide custom queueSize and flushInterval in the constructor. If set to zero, batchSize is 1; otherwise, batchSize is the default of 10.

int queueSize = 20000;

// Note: if this is set to 0 then batchSize will be set to 1, otherwise batchSize will be default, which is 10.
int flushIntervalInMillis = 10000;  // 10,000 msecs = 10 secs 

ODPEventManager odpEventManager = new ODPEventManager(defaultODPApiManager, queueSize, flushIntervalInMillis);

Customize ODPSegmentManager

You can provide cacheSize and cacheTimeout in the constructor, but a custom cache in ODPManager ignores these values. By default, ODPSegmentManager uses LRUCacheManager.

int cacheSize = 100;
int cacheTimeoutInSeconds= 600;  // 10 mins = 600 secs

ODPSegmentManager odpSegmentManager = new ODPSegmentManager(defaultODPApiManager, cacheSize, cacheTimeoutInSecs);

// Second method to set custom cache size and timeout using odpManager
ODPApiManager defaultODPApiManager = new DefaultODPApiManager();
ODPManager odpManager = ODPManager.builder()
                            .withSegmentCacheSize(cacheSize) 
                            .withSegmentCacheTimeout(cacheTimeoutInSecs) // seconds
                            .withApiManager(defaultODPApiManager)
                            .build();

Custom cache:

You can use the custom cache, which stores the fetchQualifiedSegments results, by implementing the Cache interface.

public interface Cache<T> {
   int DEFAULT_MAX_SIZE = 10000;
   int DEFAULT_TIMEOUT_SECONDS = 600;
   void save(String key, T value);
   T lookup(String key);
   void reset();
}

Here is an example of customCache implementation:

public class CustomCache<T> implements Cache<T> {
   private final Object lock = new Object();
   final Map<String, T> linkedHashMap = new LinkedHashMap<>();
   
   public CustomCache() {
   }
   
   public void save(String key, T value) {
       synchronized (lock) {
           linkedHashMap.put(key, value);
       }
   }

   public T lookup(String key) {
       synchronized (lock) {
           if (linkedHashMap.containsKey(key)) {
               T entity = linkedHashMap.get(key);
               return entity;
           }
           return null;
       }
   }

   public void reset() {
       synchronized (lock) {
           linkedHashMap.clear();
       }
   }
}

Pass this customCache object to OdpManager using its builder option and do not pass odpSegmentManager object:

ODPApiManager defaultODPApiManager = new DefaultODPApiManager();

ODPEventManager odpEventManager = new ODPEventManager(defaultODPApiManager);
                
// Note: To use custom Cache user should not pass odpSegmentManager 
ODPManager odpManager = ODPManager.builder()
     .withEventManager(odpEventManager) // Optional
     .withSegmentCache(new CustomCache<>()); //Optional
     .withApiManager(defaultODPApiManager)
     .build();

OptimizelyFactory

In this package, OptimizelyFactory provides a basic utility to instantiate the Optimizely Feature Experimentation Java SDK with a minimal number of configuration options. The package sources configuration properties from Java system properties, environment variables, or an optimizely.properties file, in that order.

OptimizelyFactory does not capture all configuration and initialization options. For more use cases, build the resources via their respective builder classes.

When instantiated with the OptimizelyFactory methods, the Java SDK uses the default configuration of HttpProjectConfigManager, BatchEventProcessor, and AsyncEventHandler.

The example below shows how to initialize the Java SDK using the OptimizelyFactory methods.

Optimizely optimizelyClient = OptimizelyFactory.newDefaultInstance(sdkKey);

// If you provide the SDK key via a global property, use the empty signature:
Optimizely optimizely = OptimizelyFactory.newDefaultInstance();

// with fallback datafile
Optimizely optimizelyClient = OptimizelyFactory.newDefaultInstance(sdkKey, datafile);

In addition to the datafile, you need to provide an event dispatcher (also called event handler) object as an argument to the Optimizely.builder function. Use our default event dispatcher implementation, or provide your own implementation as described in Configure the event dispatcher.

Use authenticated datafile in a secure environment

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Note

Authenticated datafiles are in beta. Contact your Customer Success Manager if you are interested in becoming an early user of authenticated datafiles as part of the beta secure environment feature.

You can fetch the Optimizely datafile from an authenticated endpoint using a server-side (only) Optimizely Feature Experimentation SDK. For more information, refer to Manage environments.

To use an authenticated datafile, download your Optimizely environment's access token from the Optimizely app at Settings>Environments. Select your secure environment, and copy the Datafile access token. The example below shows how to initialize the Optimizely client using an access token and sdkKey, enabling the client to fetch the authenticated datafile and complete initialization.

// fetch the datafile from an authenticated endpoint
String accessToken = "<YOUR_DATAFILE_ACCESS_TOKEN>";
String sdkKey = "<YOUR_SDK_KEY>";
Optimizely optimizelyClient = OptimizelyFactory.newDefaultInstance(sdkKey, null, accessToken);

Source files

The language/platform source files containing the implementation for Java are at Optimizely.java.