我认为单例的使用与数据库中的多对一关系是一样的。如果代码中有许多不同的部分需要处理对象的单个实例，那么使用单例就很有意义了。

单例候选人必须满足三个要求:

控制对共享资源的并发访问。 将从系统的多个不同部分请求对资源的访问。 只能有一个对象。

如果你提议的单例只有其中的一两个需求，那么重新设计几乎总是正确的选择。

例如，打印机假脱机程序不太可能从多个位置(打印菜单)调用，因此可以使用互斥来解决并发访问问题。

简单的日志记录器是可能有效的单例的最明显的例子，但这可能会在更复杂的日志记录方案中发生变化。

当您想要确保一个类将有一个实例，并且该实例将有一个全局访问点时，您可以使用单例设计模式。

假设您有一个应用程序，它需要数据库来处理CRUD操作。理想情况下，您应该使用与数据库相同的连接对象来访问数据库并执行CRUD操作。

因此，为了确保数据库类有一个对象，并且该对象将在整个应用程序中使用，我们实现了单例设计模式。

确保构造函数是私有的，并且提供了一个静态方法来提供对单例类的单个对象的访问

一个实例可以在Test::Builder中找到，这个类支持几乎所有现代Perl测试模块。Builder单例存储并代理测试流程的状态和历史记录(历史测试结果，计算运行的测试次数)以及测试输出流向等内容。这些都是协调由不同作者编写的多个测试模块以在单个测试脚本中一起工作所必需的。

The history of Test::Builder's singleton is educational. Calling new() always gives you the same object. First, all the data was stored as class variables with nothing in the object itself. This worked until I wanted to test Test::Builder with itself. Then I needed two Test::Builder objects, one setup as a dummy, to capture and test its behavior and output, and one to be the real test object. At that point Test::Builder was refactored into a real object. The singleton object was stored as class data, and new() would always return it. create() was added to make a fresh object and enable testing.

Currently, users are wanting to change some behaviors of Test::Builder in their own module, but leave others alone, while the test history remains in common across all testing modules. What's happening now is the monolithic Test::Builder object is being broken down into smaller pieces (history, output, format...) with a Test::Builder instance collecting them together. Now Test::Builder no longer has to be a singleton. Its components, like history, can be. This pushes the inflexible necessity of a singleton down a level. It gives more flexibility to the user to mix-and-match pieces. The smaller singleton objects can now just store data, with their containing objects deciding how to use it. It even allows a non-Test::Builder class to play along by using the Test::Builder history and output singletons.

似乎在数据的协调和行为的灵活性之间存在着一种推拉关系，这种关系可以通过在共享数据周围使用尽可能少的行为来缓解，以确保数据的完整性。

Singleton pattern is the most pervasive pattern in the Spring containerization approach. If we look at that in terms of architectural primitives - they form a blackboard graph of objects, to which every thread can read and write. They do the dramatic act of synchronizing between multiple threads. The very reason why multiple threads need to synchronize is because there are always resources that underlie a computational program, over which contention might occur. Consider what is called a 'last seat problem'. A flight is being booked, but there are multiple ways to do it. For simplicity lets assume that the data about the flight occupancy is stored in a flat file rather than a database. Now, if there are two threads, each functionally different (i.e represented by different endpoints in the webapp) and let one of these threads A, be the thread which a prospective passenger uses to make a booking and the other one B is which a flight manager uses to close the booking - virtually closing the boarding door. Then, if these threads do not use singleton, the flight object would be detached from the real resource out-there, which we say not the actual aeroplane but the entry in the flat file. The A thread would have reference to an object, while the passenger is still fighting a dilemma whether to fly or not and then finally when he makes up his mind, the B thread would already have closed the door. But the object referenced by the A thread would still show one more seat to go. Now, cutting out the RDBMS due to our initial assumption, the system would write a ticket for the passenger and issue it to him eventhough the boarding is closed. Now, in a singleton implementation, the moment the theread B accesses the system, the universal object Flight is updated with status closed. Hence, if the passenger finally makes up his mind and clicks confirm, he would get an error right away. All this would not have been possible without the singleton. Hence, singleton allows you to stay close to the resources and avoids thread contention.

正如大家所说，共享资源——特别是不能处理并发访问的资源。

我所见过的一个具体例子是Lucene搜索索引写入器。