dataflow

简明释义

英[/ˈdeɪtəfloʊ/]美[/ˈdeɪtəfloʊ/]

n. 数据流，信号通过

英英释义

单词用法

同义词

反义词

例句

1.Then we present an algorithm to detect unknown network virus based on network dataflow.

通过基于流量的检测，实现对于新型未知网络病毒的挖掘。

2.Every component in a dataflow pipeline performs work when it receives a message from another component.

数据流管道中的每个组件从另一个组件接收消息时执行工作。

3.Data is an important part of enterprise information. Dataflow works on the enterprise process.

数据是企业业务信息的重要组成部分，数据流转涉及企业业务组成的各个方面。

4.Processes are similar in some ways to the actor model already discussed and channels share many similarities with dataflow streams.

进程在某些方面与前面讨论的actor模型类似，而通道与数据流有很多相似之处。

5.Dataflow streams act as bounded queues of values, so data can be poured through the structure defined by the code, maintaining many of the same beneficial properties.

数据流充当值的绑定队列，因此可以通过代码定义的结构灌注数据，保留相同的有益属性。

6.Pointer analysis plays an important role in the dataflow analysis of programs which are written by c.

指针分析对于使用C语言编制程序的数据流分析有着重要的意义。

7.The software engineer designed a new architecture to optimize the dataflow 数据流 between different components of the system.

软件工程师设计了一种新架构，以优化系统各个组件之间的数据流.

8.Understanding the dataflow 数据流 is crucial for debugging the application effectively.

理解数据流对于有效调试应用程序至关重要.

9.We implemented a monitoring tool to visualize the dataflow 数据流 in real-time.

我们实施了一个监控工具，以实时可视化数据流.

10.The dataflow 数据流 diagram helped the team identify bottlenecks in the process.

该数据流图帮助团队识别流程中的瓶颈.

11.In cloud computing, managing dataflow 数据流 is essential for performance optimization.

在云计算中，管理数据流对性能优化至关重要.

作文

In the modern world, technology plays a crucial role in our daily lives. One of the key concepts that has emerged from the advancements in technology is dataflow, which refers to the movement of data between different systems and processes. Understanding dataflow is essential for anyone involved in fields such as computer science, information technology, and data analysis. It helps us comprehend how data is collected, processed, and utilized across various platforms. To illustrate the importance of dataflow, consider the example of a social media platform. When a user posts a photo, several steps occur that involve dataflow. First, the image is uploaded to the server, where it is stored temporarily. Then, the system processes the image, analyzing its content and metadata. This processing stage is vital as it determines how the image will be displayed and shared with other users. The dataflow continues as the image is sent to the user's friends' feeds, allowing them to see and interact with the post. Moreover, dataflow is not limited to social media; it is also prevalent in business environments. Companies rely on dataflow to manage their operations efficiently. For instance, in an e-commerce setting, when a customer places an order, the dataflow initiates a series of actions. The order details are sent to the inventory system to check product availability, then to the payment gateway for processing, and finally to the shipping department to arrange delivery. Each of these steps involves a seamless dataflow that ensures the transaction is completed successfully. Furthermore, understanding dataflow can significantly enhance data security. In an era where data breaches are common, organizations must monitor the dataflow within their networks to identify potential vulnerabilities. By analyzing how data moves through their systems, companies can implement security measures to protect sensitive information. For example, if a company notices unusual dataflow patterns, it can investigate further to prevent unauthorized access to its databases. On a broader scale, dataflow is pivotal in the realm of big data and analytics. As organizations collect vast amounts of data, understanding the dataflow allows them to extract valuable insights. Analysts can track how data flows from various sources, such as customer interactions, sales figures, and market trends. This comprehensive view enables companies to make informed decisions based on real-time data analysis. In conclusion, the concept of dataflow is integral to the functioning of modern technology and business practices. Whether in social media, e-commerce, or data security, a clear understanding of dataflow empowers individuals and organizations to optimize their processes and safeguard their data. As we continue to advance technologically, the significance of dataflow will only grow, making it a fundamental aspect of our digital landscape.

在现代世界中，技术在我们的日常生活中发挥着至关重要的作用。随着技术的进步，出现了一个关键概念——数据流，它指的是数据在不同系统和流程之间的移动。理解数据流对于任何参与计算机科学、信息技术和数据分析领域的人来说都是至关重要的。它帮助我们理解数据是如何在各个平台之间收集、处理和利用的。 为了说明数据流的重要性，考虑一下社交媒体平台的例子。当用户发布照片时，会发生几个步骤，这些步骤涉及数据流。首先，图像被上传到服务器，在那里临时存储。然后，系统处理图像，分析其内容和元数据。这个处理阶段至关重要，因为它决定了图像将如何显示和与其他用户共享。数据流继续进行，因为图像被发送到用户朋友的动态，让他们看到并与帖子互动。 此外，数据流不仅限于社交媒体；它在商业环境中也很普遍。公司依靠数据流来高效管理其运营。例如，在电子商务环境中，当客户下订单时，数据流启动了一系列操作。订单详情被发送到库存系统以检查产品可用性，然后发送到支付网关进行处理，最后发送到发货部门安排送货。每一个步骤都涉及无缝的数据流，确保交易成功完成。 此外，理解数据流可以显著增强数据安全性。在数据泄露普遍的时代，组织必须监控其网络中的数据流以识别潜在漏洞。通过分析数据在其系统中的流动方式，公司可以实施安全措施来保护敏感信息。例如，如果一家公司注意到不寻常的数据流模式，它可以进一步调查以防止未经授权访问其数据库。 在更广泛的层面上，数据流在大数据和分析领域至关重要。随着组织收集大量数据，理解数据流使他们能够提取有价值的见解。分析师可以跟踪数据如何从各种来源流动，例如客户互动、销售数字和市场趋势。这种全面的视角使公司能够基于实时数据分析做出明智的决策。 总之，数据流的概念是现代技术和商业实践运作的核心。无论是在社交媒体、电子商务还是数据安全方面，清晰理解数据流使个人和组织能够优化其流程并保护其数据。随着我们继续在技术上取得进步，数据流的重要性只会增加，使其成为我们数字环境中的基本方面。