这是否意味着两个线程不能同时更改底层数据?或者它是否意味着当多个线程执行给定的代码段时,该代码段将以可预测的结果运行?
当前回答
线程安全代码是指即使有多个线程同时执行也能正常工作的代码。
http://mindprod.com/jgloss/threadsafe.html
其他回答
线程安全代码是指即使有多个线程同时执行也能正常工作的代码。
http://mindprod.com/jgloss/threadsafe.html
至少在c++中,我认为线程安全有点用词不当,因为它在名称中遗漏了很多内容。要实现线程安全,代码通常必须具有前瞻性。这通常不是一种被动的品质。
For a class to be thread-safe, it has to have "extra" features that add overhead. These features are part of the implementation of the class and generally speaking, hidden from the interface. That is, different threads can access any of the class' members without ever having to worry about conflicting with a concurrent access by a different thread AND can do so in a very lazy manner, using some plain old regular human coding style, without having to do all that crazy synchronization stuff that is already rolled into the guts of the code being called.
这就是为什么有些人更喜欢使用内部同步这个术语。
术语集
我遇到的这些概念主要有三组术语。第一个,历史上更受欢迎(但最糟糕)的是:
线程安全的 不线程安全
第二个(更好的)是:
线程的证据 线程兼容 线程敌意
第三个(甚至更好)是:
内部同步 外部同步 unsynchronizable
类比
线程安全~线程证明~内部同步
An example of an internally synchronized (aka. thread-safe or thread proof) system is a restaurant where a host greets you at the door, and disallows you from queueing yourself. The host is part of the mechanism of the restaurant for dealing with multiple customers, and can use some rather tricky tricks for optimizing the seating of waiting customers, like taking the size of their party into account, or how much time they look like they have, or even taking reservations over the phone. The restaurant is internally synchronized because all of this is included "behind the scenes" when you interact with it. You, the customer, don't do any of it. The host does all of it for you.
不是线程安全的(但是很好)~线程兼容~外部同步~自由线程
假设你去银行。有一条线,即争夺银行出纳员。因为你不是野蛮人,所以你知道在争夺资源的过程中,最好的办法就是像文明人一样排队。严格来说没人逼你这么做。我们希望你有必要的社会规划来自己做这件事。从这个意义上说,银行大厅在外部是同步的。
我们是否可以说它是线程不安全的?如果使用线程安全的、线程不安全的双极术语集,就会出现这种情况。这不是一个很好的术语集合。更好的术语是外部同步。银行大厅对多个客户的访问没有敌意,但它也不做同步他们的工作。这些都是客户自己做的。
This is also called "free threaded," where "free" is as in "free from lice"--or in this case, locks. Well, more accurately, synchronization primitives. That doesn't mean the code can run on multiple threads without those primitives. It just means it doesn't come with them already installed and it's up to you, the user of the code, to install them yourself however you see fit. Installing your own synchronization primitives can be difficult and requires thinking hard about the code, but also can lead to the fastest possible program by allowing you to customize how the program executes on today's hyperthreaded CPUs.
不线程安全(和坏)~线程敌对~不可同步
An example everyday analogy of a thread-hostile system is some jerk with a sports car refusing to use their blinkers and changing lanes willy-nilly. Their driving style is thread hostile or unsychronizable because you have no way to coordinate with them, and this can lead to contention for the same lane, without resolution, and thus an accident as two cars attempt to occupy the same space, without any protocol to prevent this. This pattern can also be thought of more broadly as anti-social, though that's less specific to threads and more generally applicable to many areas of programming.
为什么线程安全/不线程安全是一个糟糕的术语集
The first and oldest terminology set fails to make the finer distinction between thread hostility and thread compatibility. Thread compatibility is more passive than so-called thread safety, but that doesn't mean the called code is unsafe for concurrent thread use. It just means it's passive about the synchronization that would allow this, putting it off to the calling code, instead of providing it as part of its internal implementation. Thread compatible is how code should probably be written by default in most cases but this is also sadly often erroneously thought of as thread unsafe, as if it's inherently anti safety, which is a major point of confusion for programmers.
NOTE: Many software manuals actually use the term "thread-safe" to refer to "thread-compatible," adding even more confusion to what was already a mess! I avoid the term "thread-safe" and "thread-unsafe" at all costs for this very reason, as some sources will call something "thread-safe" while others will call it "thread-unsafe" because they can't agree on whether you have to meet some extra standards for safety (pre-installed synchronization primitives), or just NOT be hostile to be considered "safe". So avoid those terms and use the smarter terms instead, to avoid dangerous miscommunications with other engineers.
提醒我们的目标
本质上,我们的目标是颠覆混乱。
We do that by creating semi-deterministic systems we can rely on. Determinism is expensive, mostly due to the opportunity costs of losing parallelism, pipelining, and reordering. We try to minimize the amount of determinism we need to keep our costs low, while also avoiding making decisions that will further erode what little determinism we can afford. Thus, the semi- prefix. We just want certain little bits of our code's state to be deterministic, while the computational machinery underneath doesn't have to be completely so. Synchronization of threads is about increasing the order and decreasing the chaos in a multi-threaded system because having multiple threads leads to a greater amount of non-determinism naturally which must be subdued somehow.
总而言之,一些代码主体可以在“杂耍刀”上投入三种主要程度的努力。在多线程上下文中正确地工作。
The highest degree (thread-proof, etc.) means that a system behaves in a predictable manner even if you call it from multiple threads sloppily. It does the work necessary to achieve this itself so you don't have to. It makes this nice interface for you, the programmer writing calling code, so that you can pretend to live in a world without synchronization primitives. Because it's already included them internally. It's also expensive and slow and also somewhat unpredictable when it comes to how long it takes for tasks to complete due to synchronization it's doing, which must always be greater than the amount you need for your specific program because it doesn't know what your code will do. Great for casual coders who code in various scripting languages to do science or something, but aren't themselves writing highly efficient close-to-the-metal code. They don't need to juggle knives.
第二级(线程兼容等)意味着系统运行良好,调用代码能够可靠地及时检测到不可预测性,并在运行时使用自己安装的同步原语正确地处理它。D-I-Y同步。BYOSP =自带同步原语。至少你知道你调用的代码会很好地处理它们。这是为接近金属的专业程序员准备的。
The third degree (thread-hostile, etc.) means that the system doesn't behave well enough to play with anyone else and can only EVER be run single-threaded without incurring chaos. This is classic early 90s and earlier code, essentially. It was programmed with a lack of awareness about how it might be called or used from multiple threads to such a high degree that even if you try to add those synchronization primitives yourself, it just won't work because it makes old fashioned assumptions that these days seem anti-social and unprofessional.
However, some code only really makes sense called single-threaded and so is still written to be called that way intentionally. This is true especially for software that already has an efficient pipeline and memory access sequence, and doesn't benefit from the main purpose of multi-threading: hiding memory access latencies. Accessing non-cache memory is ridiculously slower than most other instructions. So whenever an application is waiting for some bit of memory access, it should switch to another task thread in the meantime to keep the processor working. Of course, these days, that could mean switching to another coroutine/fiber/etc. within the same thread, when available, because these are much more efficient than a thread context switch. But once even those are exhausted for the time being, it's time to switch threads executing on our core.
但有时,你已经很好地打包和排序了所有的内存访问,你最不想做的就是切换到另一个线程,因为你已经流水线化了你的代码来尽可能有效地处理这个问题。那么,丝线不会带来伤害。这是一个例子,但还有其他例子。
一般来说,我认为在编程要调用的代码时,尽可能地实现线程兼容是有意义的,特别是如果没有真正的理由不这样做,并且它只需要你在编码时意识到这一点。
从本质上讲,在多线程环境中,许多事情都可能出错(指令重新排序,部分构造的对象,由于CPU级别的缓存,相同的变量在不同的线程中具有不同的值等)。
我喜欢Java并发实践中给出的定义:
如果一个[部分代码]在从多个线程访问时行为正确,那么它就是线程安全的,而不考虑运行时环境对这些线程的调度或交错执行,并且在调用代码方面没有额外的同步或其他协调。
正确的意思是程序的行为符合它的规范。
的例子
假设您实现了一个计数器。你可以说它的行为是正确的,如果:
Counter.next()从不返回之前已经返回过的值(为了简单起见,我们假设没有溢出等) 从0到当前值的所有值都已在某个阶段返回(没有跳过任何值)
线程安全计数器将根据这些规则进行操作,而不管并发有多少线程访问它(通常不是简单实现的情况)。
注意:交叉贴在程序员上
一个信息量更大的问题是,是什么使代码不线程安全——答案是,有四个条件必须成立……想象一下下面的代码(它是机器语言翻译)
totalRequests = totalRequests + 1
MOV EAX, [totalRequests] // load memory for tot Requests into register
INC EAX // update register
MOV [totalRequests], EAX // store updated value back to memory
The first condition is that there are memory locations that are accessible from more than one thread. Typically, these locations are global/static variables or are heap memory reachable from global/static variables. Each thread gets its own stack frame for function/method scoped local variables, so these local function/method variables, otoh, (which are on the stack) are accessible only from the one thread that owns that stack. The second condition is that there is a property (often called an invariant), which is associated with these shared memory locations, that must be true, or valid, for the program to function correctly. In the above example, the property is that “totalRequests must accurately represent the total number of times any thread has executed any part of the increment statement”. Typically, this invariant property needs to hold true (in this case, totalRequests must hold an accurate count) before an update occurs for the update to be correct. The third condition is that the invariant property does NOT hold during some part of the actual update. (It is transiently invalid or false during some portion of the processing). In this particular case, from the time totalRequests is fetched until the time the updated value is stored, totalRequests does not satisfy the invariant. The fourth and final condition that must occur for a race to happen (and for the code to therefore NOT be "thread-safe") is that another thread must be able to access the shared memory while the invariant is broken, thereby causing inconsistent or incorrect behavior.
一个更容易理解的方法是,是什么使代码不是线程安全的。有两个主要问题会使线程应用程序产生不需要的行为。
Accessing shared variable without locking This variable could be modified by another thread while executing the function. You want to prevent it with a locking mechanism to be sure of the behavior of your function. General rule of thumb is to keep the lock for the shortest time possible. Deadlock caused by mutual dependency on shared variable If you have two shared variable A and B. In one function, you lock A first then later you lock B. In another function, you start locking B and after a while, you lock A. This is a potential deadlock where first function will wait for B to be unlocked when second function will wait for A to be unlocked. This issue will probably not occur in your development environment and only from time to time. To avoid it, all locks must always be in the same order.