// Wait on the backpressure to clear somehow
Individual gameplay features are implemented as API calls from the Unreal game client to our backend with the actual logic living exclusively in the C# microservice codebase. The service receives a request to perform a particular action on a specific player’s inventory. The service fetches the inventory from the Azure Cosmos database, confirms that the requested action is valid, modifies the inventory appropriately, persists the updated inventory back to the database, and returns a response to the game client that includes a list of all item changes as well as any other side effects that may have occurred from the action.
，详情可参考WPS下载最新地址
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在 AI 场景中，Apache Spark 凭借其强大的批处理能力与 Python 生态兼容性，广泛用于大模型训练前的数据清洗、特征工程与推理任务。而 Ray 因其低延迟、高并发特性，被 OpenAI 等头部机构用于分布式训练与强化学习。两者共同构成 Data + AI 的核心计算底座，支持从数据准备到模型推理的全流程高效执行。