What is the translation of " 事件流处理 " in English?

• event stream processing

Examples of using 事件流处理 in Chinese and their translations into English

事件流处理系统.
Event Stream Processing System.

快速创建实时事件流处理应用程序，管理和执行解决方案。
Rapidly create real-time event stream processing applications and manage and execute solutions.

事件流处理.
Event Stream Processing.

持续型智能利用多种技术，如增强分析、事件流处理、优化、业务规则管理和ML。
Continuous intelligence leverages multiple technologies such as augmented analytics, event stream processing, optimization, business rule management and ML.

了解物联网，以及事件流处理如何帮助您了解物联网的快速数据流。
Learn about the Internet of Things and how event stream processing helps you understand the IoT's rapid fire data streams..

事件流处理系统使您能够通过实时数据清理和分析及时处理这些数据。
Event stream processing systems enable you to act on this information in a timely fashion through real-time data cleansing and analytics.

SAS事件流处理将分析流数据，捕获数据并实时触发警报。
SAS Event Stream Processing will be used to analyze the streaming data, capture that data and trigger alerts in real time.

事件流处理系统首先实时分析数据，从而能够对事件做出即时响应。
Event stream processing systems first analyze data in real time, enabling immediate response to events..

分布式事件流处理已逐渐成为大数据领域的热点话题。
Distributed event stream processing has become an increasingly hot topic in the area of Big Data.

事件流处理为您提供了多个从数据中提取价值的机会。
Event stream processing gives you multiple opportunities to extract value from your data.

最后，事件流处理系统还将指定的数据存储在数据仓库或Hadoop中。
Finally, the event stream processing system also stores specified data in a data warehouse or Hadoop.

该系统基于复杂事件处理（CEP）和事件流处理（ESP）。
The system is based on Complex Event Processing(CEP) and Event Stream Processing(ESP).

SAS事件流处理（SASEventStreamProcessing）：帮助客户随时分析成千上万的事件。
SAS Event Stream Processing helps customers analyze millions of events per second.

Confluent由ApacheKafka®的原创人员创立，是企业就绪型事件流处理平台的先驱。
Confluent, founded by the original creators of Apache Kafka, pioneered the enterprise-ready event streaming platform.

可以利用实时流处理框架对此进行改进，如Mantis（Netflix的事件流处理系统）和ApacheSparkStreaming。
Improved approaches could leverage advancements in real-time stream processing frameworks such as Mantis(Netflix's Event Stream Processing System) and Apache Spark Streaming..

随着大量数据快速流入系统，事件流处理系统会立即清理、规范和聚合内存中的数据。
As large amounts of data rapidly stream into the system, event stream processing systems cleanse, normalize and aggregate data immediately in memory.

Riemann用于聚合和处理事件流，同时还添加了警报功能。
Riemann is used to aggregate and process event streams while adding some alerting capabilities to the process as well.

是否需要处理许多实时事件流？?
Is there a lot of real-time event streams handling needed?

是否需要处理许多实时事件流？?
Will you be handling a lot of real-time event streams?

Riemann用于汇总和处理事件流，同时为流程添加一些警报功能。
Riemann is used to aggregate and process event streams while adding some alerting capabilities to the process as well.

这种类型的系统通常包含可以处理和分析事件流的工具。
This type of system usually involves tools that can process and analyze streams of events.

处理：编写流处理应用程序，对实时事件进行响应。
Process: Write scalable stream processing applications that react to events in real time.

Eventbuses或者Clickevents本质上就是异步事件流，你可以监听并处理这些事件。
Event buses or typical click events are really asynchronous event streams, on which you can listen and react accordingly.

它利用KSQL的新API功能，使用Java轻松构建UDF/UDAF函数，对传入事件进行连续流处理。
It leverages the new API features of KSQL to build UDF/ UDAF functions easily with Java to do continuous stream processing on incoming events.

如果你正在构建实时流处理应用程序，那么事件时间处理是你迟早必须使用的功能之一。
If you are building a Realtime streaming application, Event Time processing is one of the features that you will have to use sooner or later.

提取数据之后，事件经过一个或多个流处理器，这些处理器可以路由数据(例如，到存储)或执行分析和其他处理。
After ingestion, events go through one or more stream processors that can route the data(for example, to storage) or perform analytics and other processing.

数据分析和工作流：ServiceFabric的快速读取和写入使必须可靠处理事件或数据流的应用程序成为可能。
Data analytics and workflows: The fast reads and writes of Service Fabric enable applications that must reliably process events or streams of data.

对于这些快速流动的数据的行业术语可以是“流数据”或“复杂事件处理”。
Industry terminology for such fast-moving data tends to be either“streaming data,” or“complex event processing.”.

包括分布式流计算平台（DSCP）与事件处理平台（EPP）在内的事件流处理技术正在快速成熟。
ESP technology, including distributed stream computing platforms(DSCPs) and event processing platforms(EPPs), is maturing rapidly.