cardinality

简明释义

英[kɑːdɪˈnælɪti]美[ˌkɑːrdɪˈnæləti]

n. 基数；集的势

复 数 c a r d i n a l i t i e s

英英释义

单词用法

同义词

反义词

例句

1.Cardinality affects join orders and join methods to a large extent.

这个基数会大大影响连接顺序和连接方法。

2.Cardinality adherence for element data as well as for required attributes.

元素数据以及所需属性的基数性。

3.Standard statistics from source data (such as cardinality or indexes).

源数据(例如基数或是索引)的标准统计。

4.Changing cardinality of existing input data structures from mandatory to optional.

将现有输入数据结构的基数性由强制更改为可选。

5.You use the radio buttons on this page of the wizard to specify the cardinality of the relationship.

使用向导此页的单选按钮指定关系的基数性。

6.In Figure 14, notice that the annotation describing the cardinality of the relationship is now One-to-One.

在图14之中，注意关系的性质现在描述的是一对一。

7.The higher the cardinality, the more probes into the inner table, one per qualifying (outer) record.

基数越高，进入内部表、每一条合格的（外部）记录的探测就越多。

8.In this case, the cardinality 基数 of the relationship is one-to-many.

在这种情况下，关系的cardinality 基数是一对多。

9.To improve query performance, you should analyze the cardinality 基数 of your indexes.

为了提高查询性能，您应该分析索引的cardinality 基数。

10.The cardinality 基数 of a set refers to the number of elements it contains.

一个集合的cardinality 基数指的是它包含的元素数量。

11.In database design, understanding the cardinality 基数 of relationships helps to optimize data structure.

在数据库设计中，理解关系的cardinality 基数有助于优化数据结构。

12.The cardinality 基数 of a database table can impact how efficiently it can be queried.

数据库表的cardinality 基数会影响其查询效率。

作文

In the realm of mathematics and computer science, the term cardinality refers to the number of elements in a set or the size of a collection. Understanding cardinality is crucial for various fields, including data science, database management, and even philosophy. In simple terms, cardinality helps us quantify the concept of 'how many' when we deal with different sets or groups. For example, consider a classroom filled with students. If there are 30 students, we say that the cardinality of the set of students in that classroom is 30. This basic understanding of cardinality can be extended to more complex systems, such as databases where we might want to know how many records exist in a table. In this case, the cardinality indicates the number of rows in that table, which is essential for efficient data retrieval and management.Moreover, cardinality can also describe relationships between different sets. In relational databases, we often encounter terms like one-to-one, one-to-many, and many-to-many relationships, which fundamentally rely on the concept of cardinality. For example, in a one-to-many relationship, one record in a table can be associated with multiple records in another table. Understanding the cardinality of these relationships helps database designers create effective and efficient schemas that can handle data relationships appropriately.In addition to its importance in databases, cardinality plays a significant role in set theory, a branch of mathematical logic that studies collections of objects. The cardinality of finite sets is straightforward; however, when we delve into infinite sets, things become more fascinating. For instance, the cardinality of the set of natural numbers is different from the cardinality of the set of real numbers. While both are infinite, the set of real numbers has a greater cardinality, indicating that there are more real numbers than natural numbers, despite both being infinite. This distinction leads to profound implications in mathematics and philosophy, particularly in discussions about the nature of infinity.Furthermore, in the context of data science and machine learning, understanding cardinality is vital when it comes to feature engineering. High cardinality features, which have a large number of unique values, can pose challenges for algorithms, as they may lead to overfitting. Conversely, low cardinality features might not provide enough information for the model to learn effectively. Thus, data scientists must carefully assess the cardinality of their features to optimize their models and improve performance.In conclusion, the concept of cardinality is fundamental across various disciplines, from mathematics to computer science and data analysis. Its ability to quantify sets and relationships provides clarity and structure in a world filled with data. As we continue to navigate through an increasingly data-driven society, a solid understanding of cardinality will undoubtedly enhance our analytical capabilities and decision-making processes. Whether one is designing a database, studying set theory, or building a predictive model, the significance of cardinality cannot be overstated. It serves as a foundational element that connects various concepts and applications, making it an essential topic of study for anyone engaged in analytical thinking.

在数学和计算机科学领域，术语cardinality指的是集合中元素的数量或集合的大小。理解cardinality对于数据科学、数据库管理甚至哲学等多个领域都是至关重要的。简单来说，cardinality帮助我们在处理不同集合或群体时量化“多少”的概念。例如，考虑一个装满学生的教室。如果有30个学生，我们会说这个教室中学生的集合的cardinality是30。这种对cardinality的基本理解可以扩展到更复杂的系统，例如数据库，在这里我们可能想知道某个表中存在多少条记录。在这种情况下，cardinality表示该表中的行数，这对于高效的数据检索和管理至关重要。此外，cardinality还可以描述不同集合之间的关系。在关系数据库中，我们经常遇到一对一、一对多和多对多的关系，这些关系从根本上依赖于cardinality的概念。例如，在一对多关系中，表中的一条记录可以与另一个表中的多条记录相关联。理解这些关系的cardinality有助于数据库设计师创建有效且高效的架构，以适当地处理数据关系。除了在数据库中的重要性外，cardinality在集合论中也发挥着重要作用，集合论是研究对象集合的数学逻辑分支。有限集合的cardinality是简单明了的；然而，当我们深入探讨无限集合时，事情变得更加迷人。例如，自然数集合的cardinality与实数集合的cardinality是不同的。虽然两者都是无限的，但实数集合的cardinality更大，这表明尽管两者都是无限的，实数的数量比自然数的数量更多。这一区别在数学和哲学中具有深远的意义，特别是在关于无限性质的讨论中。此外，在数据科学和机器学习的背景下，理解cardinality在特征工程中至关重要。高cardinality特征具有大量唯一值，可能会给算法带来挑战，因为它们可能导致过拟合。相反，低cardinality特征可能无法为模型提供足够的信息以有效学习。因此，数据科学家必须仔细评估其特征的cardinality以优化模型并提高性能。总之，cardinality的概念在各个学科中都是基础性的，从数学到计算机科学再到数据分析。它量化集合和关系的能力在充满数据的世界中提供了清晰性和结构。随着我们继续在一个日益数据驱动的社会中导航，对cardinality的扎实理解无疑会增强我们的分析能力和决策过程。无论是设计数据库、研究集合论还是构建预测模型，cardinality的重要性都不容小觑。它作为一个基础元素，将各种概念和应用连接在一起，使其成为任何参与分析思维的人的必修课题。