揭示过程：我们强大的广告活动构建器的创造

In a previous blog, we introduced Trident, Grab’s internal marketing campaign platform. Trident empowers our marketing team to configure If This, Then That (IFTTT) logic and processes real-time events based on that.

在之前的博客中，我们介绍了 Trident，Grab 的内部营销活动平台。Trident 赋予我们的营销团队配置 If This, Then That (IFTTT) 逻辑并基于实时事件进行处理的能力。

While we mainly covered how we scaled up the system to handle large volumes of real-time events, we did not explain the implementation of the event processing mechanism. This blog will fill up this missing piece. We will walk you through the various processing mechanisms supported in Trident and how they were built.

虽然我们主要介绍了如何扩展系统以处理大量实时事件，但我们没有解释事件处理机制的实现。本博客将填补这个缺失的部分。我们将为您介绍Trident支持的各种处理机制以及它们是如何构建的。

Base building block: Treatment

基本构建块：处理方式

In our system, we use the term “treatment” to refer to the core unit of a full IFTTT data structure. A treatment is an amalgamation of three key elements - an event, conditions (which are optional), and actions. For example, consider a promotional campaign that offers “100 GrabPoints for completing a ride paid with GrabPay Credit”. This campaign can be transformed into a treatment in which the event is “ride completion”, the condition is “payment made using GrabPay Credit”, and the action is “awarding 100 GrabPoints”.

在我们的系统中，我们使用术语“处理方式”来指代完整的 IFTTT 数据结构的核心单元。处理方式是三个关键元素的融合 - 事件、条件（可选）和操作。例如，考虑一个促销活动，提供“完成使用 GrabPay Credit 支付的乘车可获得 100 GrabPoints”的奖励。这个活动可以转化为一个处理方式，其中事件是“乘车完成”，条件是“使用 GrabPay Credit 进行支付”，操作是“奖励 100 GrabPoints”。

Data generated across various Kafka streams by multiple services within Grab forms the crux of events and conditions for a treatment. Trident processes these Kafka streams, treating each data object as an event for the treatments. It evaluates the set conditions against the data received from these events. If all conditions are met, Trident then executes the actions.

Grab 内的多个服务通过各种 Kafka 流生成数据，这些数据构成了处理的事件和条件的核心。Trident 处理这些 Kafka 流，将每个数据对象视为处理的事件。它根据从这些事件接收到的数据评估设置的条件。如果所有条件都满足，Trident 就会执行相应的操作。

Figure 1. Trident processes Kafka st...