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Event batching

This topic describes how the Optimizely Go SDK uses the event processor to batch impressions and conversion events into a single payload before sending it to Optimizely.

The Optimizely Full Stack Go SDK batches impression and conversion events into a single payload before sending it to Optimizely. This is achieved through an SDK component called the event processor.

Event batching has the advantage of reducing the number of outbound requests to Optimizely depending on how you define, configure, and use the event processor. It means less network traffic for the same number of Impression and conversion events tracked.

In the Go SDK, QueueingEventProcessor provides implementation of the EventProcessor interface and batches events. You can control batching based on two parameters:

  • Batch size – Defines the number of events that are batched together before sending to Optimizely.
  • Flush interval – Defines the amount of time after which any batched events should be sent to Optimizely.

An event consisting of the batched payload is sent as soon as the batch size reaches the specified limit or flush interval reaches the specified time limit. BatchEventProcessor options are described in more detail below.

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Note

Event batching works with both out-of-the-box and custom event dispatchers.

The event batching process does not remove any personally identifiable information (PII) from events. Please ensure that you are not sending any unnecessary PII to Optimizely.

Basic example

import optly "github.com/optimizely/go-sdk"

// the default client will have a BatchEventProcessor with the default options
optlyClient, err := optly.Client("SDK_KEY_HERE")

By default, batch size is 10 and flush interval is 30 seconds.

Advanced example

To customize the event processor, you can use the client factory methods.

import (
  "time"
  
	"github.com/optimizely/go-sdk/pkg/client"
	"github.com/optimizely/go-sdk/pkg/event"
  "github.com/optimizely/go-sdk/pkg/utils"
)

optimizelyFactory := &client.OptimizelyFactory{
		SDKKey: "SDK_KEY",	
}

// You can configure the batch size and flush interval
eventProcessor := event.NewBatchEventProcessor(
  event.WithBatchSize(10), 
  event.WithFlushInterval(30 * time.Second),
)
optlyClient, err := optimizelyFactory.Client(
  client.WithEventProcessor(eventProcessor),
)

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Warning

The maximum payload size is 3.5 MB. Optimizely rejects requests with a 400 response code, Bad Request Error, if the batch payload exceeds this limit.

The size limitation is because of the Optimizely Events API, which Full Stack uses to send data to Optimizely.

The most common cause of a large payload size is a high batch size. If your payloads exceed the size limit, try configuring a smaller batch size.

BatchEventProcessor

BatchEventProcessor is an implementation of EventProcessor where events are batched. The class maintains a single consumer thread that pulls events off of an in-memory queue and buffers them for either a configured batch size or a maximum duration before the resulting LogEvent is sent to the EventDispatcher and NotificationCenter.

The following properties can be used to customize the BatchEventProcessor configuration.

PropertyDefault valueDescription
event.EventDispatcherNewQueueEventDispatcherUsed to dispatch event payload to Optimizely.
event.BatchSize10The maximum number of events to batch before dispatching. Once this number is reached, all queued events are flushed and sent to Optimizely.
event.FlushInterval30000 (30 Seconds)Milliseconds to wait before batching and dispatching events.
event.QNewInMemoryQueueBlockingCollection that queues individual events to be batched and dispatched by the executor.
event.MaxQueueSize2000The maximum number of events that can be queued.

For more information, see Initialize the Go SDK.

Side effects

The table lists other Optimizely functionality that may be triggered by using this method:

FunctionalityDescription
LogEventWhenever the event processor produces a batch of events, a LogEvent object will be created using the event factory.

It contains batch of conversion and impression events.

This object will be dispatched using the provided event dispatcher and also it will be sent to the notification subscribers
Notification ListenersFlush invokes the LOGEVENT notification listener if this listener is subscribed to.

Register and unregister LogEvent listener

The following code shows how to add and remove a LogEvent notification listener:

import (
	"fmt"

	"github.com/optimizely/go-sdk/pkg/client"
	"github.com/optimizely/go-sdk/pkg/event"
)

// Callback for log event notification
	callback := func(notification event.LogEvent) {

		// URL to dispatch log event to
		fmt.Print(notification.EndPoint)
		// Batched event
		fmt.Print(notification.Event)
	}

	optimizelyFactory := &client.OptimizelyFactory{
		SDKKey: "SDK_KEY",
}
	optimizelyClient, err := optimizelyFactory.Client()

	// Add callback for logEvent notification
	id, err := optimizelyClient.EventProcessor.(*event.BatchEventProcessor).OnEventDispatch(callback)

	// Remove callback for logEvent notification
	err = optimizelyClient.EventProcessor.(*event.BatchEventProcessor).RemoveOnEventDispatch(id)

LogEvent

LogEvent object gets created using factory. It represents the batch of impression and conversion events we send to the Optimizely backend.

ObjectTypeDescription
EndPoint
Required (non null)
StringURL to dispatch log event to.
Event
Required
[event.Batch]Contains all the information regarding every event which is batched. including list of visitors which contains UserEvent.

Close Optimizely on application exit

If you enable event batching, it is important that you call the Close method (optimizelyClient.Close()) prior to exiting. This ensures that queued events are flushed as soon as possible to avoid any data loss.

Warning

Because the Optimizely client maintains a buffer of queued events, you must call Close() on the Optimizely instance before shutting down your application or whenever dereferencing the instance.

MethodDescription
Close()Stops all executor threads and flushes the event queue. This method will also stop any scheduledExecutorService that is running for the datafile manager.