What are examples of non-idempotent HTTP sequences of idempotent HTTP methods? I've been thinking of possible examples as well as trying to find ones on the Internet but I simple don't really understand what "non-idempotent sequence" means - although I do understand what an idempotent (single) method is.
Let us take a look at https://www.rfc-editor.org/rfc/rfc2616.pdf
However, it is possible that a sequence of several requests is non-idempotent, even if all of the methods executed in
that sequence are idempotent. (A sequence is idempotent if a single execution of the entire sequence always yields a
result that is not changed by a reexecution of all, or part, of that sequence.) For example, a sequence is non-idempotent if its result depends on a value that is later modified in the same sequence.
What exactly does "result" mean here? I've read that PUT -> GET sequence (The TCP/IP Guide: A Comprehensive, Illustrated Internet Protocols Reference, 1349) on the same resource is non-idempotent because the result of the second request depends on the result of the first one. But let us analyze it:
PUT("mysite.com", "Hello world");
GET("mysite.com", "Hello world");
The state of the site after this operations will be that it will contain the "Hello World" text.
OK, so now we are after the first execution of our sequence. Now we do:
PUT("mysite.com", "Hello world");
The state of the site doesn't change. If the result of a method should be interpreted as the state of the site after this method is applied on a given resource, then the result is clearly the same as it was after the first execution of the entire sequence. However it's also possible that it should be understood that the result of applying PUT method is that contents of the site after this method is applied and the result of GET method is the response received by a user. If that is the case, the result of the last operation is not the same as the result of the initial sequence, simply because PUT and GET methods do different things. But this interpretation lead to further complications as I will show later in this post. For now, let us go on:
GET("mysite.com", "Hello world");
The result of that operation is clearly the same as the result of the execution of the initial sequence.
Now, I'll explain what complications of the interpretation I gave above are (or would be): it'd simply basically mean that practically any sequence of GET methods wouldn't be idempotent (unless every GET asked for the same resource). Indeed, the result of GET("mysite.com", "img1.jpg") will be always different than GET("mysite.com", "img2.jpg"). It'd effectively make pipelining GET requests impossible (RFC2616 states clearly that "Clients SHOULD NOT pipeline requests using non-idempotent methods or non-idempotent sequences of methods").
However, the fact that idempotent methods are used within the context of pipelining allowed me to do some educated guesses about its intended meaning. Namely: I suppose that it was primarily defined in order to prevent HTTP servers from processing requests in parallel if the reponse to the n-th response could depend on the effect(s) of one (or many) of previous reqests (RFC2616 allows processing requests in parallel although it states that responses to the received requests must be sent in the order in which these requests were received). But if this is the case, then the original definition's simply wrong and it should be stated in the manner similar to that:
"Let us assume that we have a sequence a_n of HTTP methods numbered from 1 to n. Let us say that for any i in {1, 2, .., n} method number i returns result R_i. Let us construct a sequence w_p by adhering to the following rules:
1) p is any arbitrary taken non-negative natural number,
2) for each p w_p belongs to {a_1, a_2, ..., a_n}.
If for every w_p the condition:
if w_p = a_j, then the result of w_p is R_j
holds, then we say that the sequence a_n is idempotent".
However what I presented are just my suppositions.
Can you tell me if they are right or wrong?
I've the same question and I think the point is in "A sequence is idempotent if [...] is not changed by a reexecution of all, or part, of that sequence.".
So a squence defined by:
R := { "PUT /test", "DELETE /test", "GET /test" }
could give different results if a subset of request are reexecuted, despite of the fact that for each request r ∈ R will have the same side effects of N identical reexecutions of r.
Sorry if my question seems stupid. My background is in PHP, Ruby, Python, Lua and similar languages, and I have no understanding of pointers in real-life scenarios.
From what I've read on the Internet and what I've got as responses in a question I asked (When is a pointer idiomatic?), I have understood that:
Pointers should be used when copying large data. Instead of getting the whole object hierarchy, receive its address and access it.
Pointers have to be used when you have a function on a struct that modifies it.
So, pointers seem like a great thing: I should just always get them as function arguments because they are so lightweight, and it's okay if I somehow end up not needing to modify anything on the struct.
However, looking at that statement intuitively, I can feel that it sounds very creepy, and yet I don't know why.
So, as someone who is designing a struct and its related functions, or just functions, when should I receive a pointer? When should I receive a value, and why?
In other words, when should my NewAuthor method return &Author{ ... }, and when should it return Author{ ... }? When should my function get a pointer to an author as an argument, and when should it just get the value (a copy) of type Author?
There's tradeoffs for both pointers and values.
Generally speaking, pointers will point to some other region of memory in the system. Be it the stack of the function that wants to pass a pointer to a local variable or some place on the heap.
func A() {
i := 25
B(&i) // A sets up stack frame to call B,
// it copies the address of i so B can look it up later.
// At this point, i is equal to 30
}
func B(i *int){
// Here, i points to A's stack frame.
// For this to execute, I look at my variable "i",
// see the memory address it points to, then look at that to get the value of 25.
// That address may be on another page of memory,
// causing me to have to look it up from main memory (which is slow).
println(10 + (*i))
// Since I have the address to A's local variable, I can modify it.
*i = 30
}
Pointers require me to de-reference them constantly whenever I was to see the data it points to. Sometimes you don't care. Other times it matters a lot. It really depends on the application.
If that pointer has to be de-referenced a lot (ie: you pass in a number to use in a bunch of different calcs), then you keep paying the cost.
Compared to using values:
func A() {
i := 25
B(i) // A sets up the stack frame to call B, copying in the value 25
// i is still 25, because A gave B a copy of the value, and not the address.
}
func B(i int){
// Here, i is simply on the stack. I don't have to do anything to use it.
println(10 + i)
// Since i here is a value on B's stack, modifications are not visible outside B's scpe
i = 30
}
Since there's nothing to dereference, it's basically free to use the local variable.
The down side of passing values happens if those values are large because copying data to the stack isn't free.
For an int it's a wash because pointers are "int" sized. For a struct, or an array, you are copying all the data.
Also, large objects on the stack can make the stack extra big. Go handles this well with stack re-allocation, but in high performance scenarios, it may be too much of an impact to performance.
There's a data safety aspect as well (can't modify something I pass by value), but I don't feel that is usually an issue in most code bases.
Basically, if your problem was already solvable by ruby, python or other language without value types, then these performance nuances don't super-matter.
In general, passing structs as pointers will usually do "the right thing" while learning the language.
For all other types, or things that you want to keep as read-only, pass values.
There are exceptions to that rule, but it's best that you learn those as needs arise rather than try to redefine your world all at once. If that makes sense.
Simply you can use pointers anywhere you want, sometimes you don't want to change your data. It may stand for abstract data, and you don't want to explicitly copy the data. Just pass by value and let compiler do its job.
In another question, a user suggested to write code like to that:
def list = ['a', 'b', 'c', 'd']
def i = 0;
assert list.collect { [i++] } == [0, 1, 2, 3]
Such code is, in other languages, considered bad practice because the content of collect changes the state of it's context (here it changes the value of i). In other words, the closure has side-effects.
Such higher order functions should be able to run the closure in parallel, and assemble it in a new list again. If the processing in the closure are long, CPU intensive operations, it may be worth executing them in separate threads. It would be easy to change collect to use an ExecutorCompletionService to achieve that, but it would break the above code.
Another example of a problem is if, for some reason, collect browse the collection in, say, reverse order, in which case the result would be [3, 2, 1, 0]. Note that in this case, the list have not been reverted, 0 is really the result of applying the closure to 'd'!
Interestingly, these functions are documented with "Iterates through this collection" in Collection's JavaDoc, which suggests the iteration is sequential.
Does the groovy specification explicitly defines the order of execution in higher order functions like collect or each? Is the above code broken, or is it OK?
I don't like explicit external variables being relied upon in my closures for the reasons you give above.
Indeed, the less variables I have to define, the happier I am ;-)
For the possibly parallel things as well, always code with a view to wrapping it with some level of GPars loveliness should it prove too much for a single thread to handle. For this, as you say, you want as little mutability as possible and to try and completely avoid side-effects (such as the external counter pattern above)
As for the question itself, if we take collect as an example function, and examine the source code, we can see that given an Object (Collection and Map are done in a similar way with slight differences as to how the Iterator is referenced) it iterates along InvokerHelper.asIterator(self), adding the result of each closure call to the resultant list.
InvokerHelper.asIterator (again source is here) basically calls the iterator() method on the Object passed in.
So for Lists, etc it will iterate down the objects in the order defined by the iterator.
It is therefore possible to compose your own class which follows the Iterable interface design (doesn't need to implement Iterable though, thanks to duck-typing), and define how the collection will be iterated.
I think by asking about the Groovy specification though, this answer might not be what you want, but I don't think there is an answer. Groovy has never really had a 'complete' specification (indeed this is point about groovy that some people dislike).
I think keeping the functions passed collect or findAll side-effect free is a good idea in general, not only for keeping the complexity low but making the code more parallel-friendly in case parallel execution is needed in the future.
But in the case of each there is not much point in keeping the function side-effect free, as it wouldn't do anything (in fact the sole purpose of this method is to replace act as a for-each loop). The Groovy's documentation have some examples of using each (and its variants, eachWithIndex and reverseEach) that require an execution order to be defined.
Now, from a pragmatic point of view, I think it can sometimes be OK to use functions with some side effects in methods like collect. For example, to transform a list in [index, value] pairs a transpose and range can be used
def list = ['a', 'b', 'c']
def enumerated = [0..<list.size(), list].transpose()
assert enumerated == [[0,'a'], [1,'b'], [2,'c']]
Or even an inject
def enumerated = list.inject([]) { acc, val -> acc << [acc.size(), val] }
But a collect and a counter does the trick too and I think the result is the most readable:
def n = 0, enumerated = list.collect{ [n++, it] }
Now, this example wouldn't make sense if Groovy provided acollect and similar methods with a index-value-param function (see Jira issue), but it kinda shows that sometimes practicality beats purity IMO :)
What is the difference between asynchronous and non-blocking calls? Also between blocking and synchronous calls (with examples please)?
In many circumstances they are different names for the same thing, but in some contexts they are quite different. So it depends. Terminology is not applied in a totally consistent way across the whole software industry.
For example in the classic sockets API, a non-blocking socket is one that simply returns immediately with a special "would block" error message, whereas a blocking socket would have blocked. You have to use a separate function such as select or poll to find out when is a good time to retry.
But asynchronous sockets (as supported by Windows sockets), or the asynchronous IO pattern used in .NET, are more convenient. You call a method to start an operation, and the framework calls you back when it's done. Even here, there are basic differences. Asynchronous Win32 sockets "marshal" their results onto a specific GUI thread by passing Window messages, whereas .NET asynchronous IO is free-threaded (you don't know what thread your callback will be called on).
So they don't always mean the same thing. To distil the socket example, we could say:
Blocking and synchronous mean the same thing: you call the API, it hangs up the thread until it has some kind of answer and returns it to you.
Non-blocking means that if an answer can't be returned rapidly, the API returns immediately with an error and does nothing else. So there must be some related way to query whether the API is ready to be called (that is, to simulate a wait in an efficient way, to avoid manual polling in a tight loop).
Asynchronous means that the API always returns immediately, having started a "background" effort to fulfil your request, so there must be some related way to obtain the result.
synchronous / asynchronous is to describe the relation between two modules.
blocking / non-blocking is to describe the situation of one module.
An example:
Module X: "I".
Module Y: "bookstore".
X asks Y: do you have a book named "c++ primer"?
blocking: before Y answers X, X keeps waiting there for the answer. Now X (one module) is blocking. X and Y are two threads or two processes or one thread or one process? we DON'T know.
non-blocking: before Y answers X, X just leaves there and do other things. X may come back every two minutes to check if Y has finished its job? Or X won't come back until Y calls him? We don't know. We only know that X can do other things before Y finishes its job. Here X (one module) is non-blocking. X and Y are two threads or two processes or one process? we DON'T know. BUT we are sure that X and Y couldn't be one thread.
synchronous: before Y answers X, X keeps waiting there for the answer. It means that X can't continue until Y finishes its job. Now we say: X and Y (two modules) are synchronous. X and Y are two threads or two processes or one thread or one process? we DON'T know.
asynchronous: before Y answers X, X leaves there and X can do other jobs. X won't come back until Y calls him. Now we say: X and Y (two modules) are asynchronous. X and Y are two threads or two processes or one process? we DON'T know. BUT we are sure that X and Y couldn't be one thread.
Please pay attention on the two bold-sentences above. Why does the bold-sentence in the 2) contain two cases whereas the bold-sentence in the 4) contains only one case? This is a key of the difference between non-blocking and asynchronous.
Let me try to explain the four words with another way:
blocking: OMG, I'm frozen! I can't move! I have to wait for that specific event to happen. If that happens, I would be saved!
non-blocking: I was told that I had to wait for that specific event to happen. OK, I understand and I promise that I would wait for that. But while waiting, I can still do some other things, I'm not frozen, I'm still alive, I can jump, I can walk, I can sing a song etc.
synchronous: My mom is gonna cook, she sends me to buy some meat. I just said to my mom: We are synchronous! I'm so sorry but you have to wait even if I might need 100 years to get some meat back...
asynchronous: We will make a pizza, we need tomato and cheeze. Now I say: Let's go shopping. I'll buy some tomatoes and you will buy some cheeze. We needn't wait for each other because we are asynchronous.
Here is a typical example about non-blocking & synchronous:
// thread X
while (true)
{
msg = recv(Y, NON_BLOCKING_FLAG);
if (msg is not empty)
{
break;
}
else
{
sleep(2000); // 2 sec
}
}
// thread Y
// prepare the book for X
send(X, book);
You can see that this design is non-blocking (you can say that most of time this loop does something nonsense but in CPU's eyes, X is running, which means that X is non-blocking. If you want you can replace sleep(2000) with any other code) whereas X and Y (two modules) are synchronous because X can't continue to do any other things (X can't jump out of the loop) until it gets the book from Y.
Normally in this case, making X blocking is much better because non-blocking spends much resource for a stupid loop. But this example is good to help you understand the fact: non-blocking doesn't mean asynchronous.
The four words do make us confused easily, what we should remember is that the four words serve for the design of architecture. Learning about how to design a good architecture is the only way to distinguish them.
For example, we may design such a kind of architecture:
// Module X = Module X1 + Module X2
// Module X1
while (true)
{
msg = recv(many_other_modules, NON_BLOCKING_FLAG);
if (msg is not null)
{
if (msg == "done")
{
break;
}
// create a thread to process msg
}
else
{
sleep(2000); // 2 sec
}
}
// Module X2
broadcast("I got the book from Y");
// Module Y
// prepare the book for X
send(X, book);
In the example here, we can say that
X1 is non-blocking
X1 and X2 are synchronous
X and Y are asynchronous
If you need, you can also describe those threads created in X1 with the four words.
One more time: the four words serve for the design of architecture. So what we need is to make a proper architecture, instead of distinguishing the four words like a language lawyer. If you get some cases, where you can't distinguish the four words very clearly, you should forget about the four words, use your own words to describe your architecture.
So the more important things are: when do we use synchronous instead of asynchronous? when do we use blocking instead of non-blocking? Is making X1 blocking better than non-blocking? Is making X and Y synchronous better than asynchronous? Why is Nginx non-blocking? Why is Apache blocking? These questions are what you must figure out.
To make a good choice, you must analyze your need and test the performance of different architectures. There is no such an architecture that is suitable for various of needs.
Asynchronous refers to something done in parallel, say is another thread.
Non-blocking often refers to polling, i.e. checking whether given condition holds (socket is readable, device has more data, etc.)
Synchronous is defined as happening at the same time (in predictable timing, or in predictable ordering).
Asynchronous is defined as not happening at the same time. (with unpredictable timing or with unpredictable ordering).
This is what causes the first confusion, which is that asynchronous is some sort of synchronization scheme, and yes it is used to mean that, but in actuality it describes processes that are happening unpredictably with regards to when or in what order they run. And such events often need to be synchronized in order to make them behave correctly, where multiple synchronization schemes exists to do so, one of those called blocking, another called non-blocking, and yet another one confusingly called asynchronous.
So you see, the whole problem is about finding a way to synchronize an asynchronous behavior, because you've got some operation that needs the response of another before it can begin. Thus it's a coordination problem, how will you know that you can now start that operation?
The simplest solution is known as blocking.
Blocking is when you simply choose to wait for the other thing to be done and return you a response before moving on to the operation that needed it.
So if you need to put butter on toast, and thus you first need to toast the bred. The way you'd coordinate them is that you'd first toast the bred, then stare endlessly at the toaster until it pops the toast, and then you'd proceed to put butter on them.
It's the simplest solution, and works very well. There's no real reason not to use it, unless you happen to also have other things you need to be doing which don't require coordination with the operations. For example, doing some dishes. Why wait idle staring at the toaster constantly for the toast to pop, when you know it'll take a bit of time, and you could wash a whole dish while it finishes?
That's where two other solutions known respectively as non-blocking and asynchronous come into play.
Non-blocking is when you choose to do other unrelated things while you wait for the operation to be done. Checking back on the availability of the response as you see fit.
So instead of looking at the toaster for it to pop. You go and wash a whole dish. And then you peek at the toaster to see if the toasts have popped. If they haven't, you go wash another dish, checking back at the toaster between each dish. When you see the toasts have popped, you stop washing the dishes, and instead you take the toast and move on to putting butter on them.
Having to constantly check on the toasts can be annoying though, imagine the toaster is in another room. In between dishes you waste your time going to that other room to check on the toast.
Here comes asynchronous.
Asynchronous is when you choose to do other unrelated things while you wait for the operation to be done. Instead of checking on it though, you delegate the work of checking to something else, could be the operation itself or a watcher, and you have that thing notify and possibly interupt you when the response is availaible so you can proceed to the other operation that needed it.
Its a weird terminology. Doesn't make a whole lot of sense, since all these solutions are ways to create synchronous coordination of dependent tasks. That's why I prefer to call it evented.
So for this one, you decide to upgrade your toaster so it beeps when the toasts are done. You happen to be constantly listening, even while you are doing dishes. On hearing the beep, you queue up in your memory that as soon as you are done washing your current dish, you'll stop and go put the butter on the toast. Or you could choose to interrupt the washing of the current dish, and deal with the toast right away.
If you have trouble hearing the beep, you can have your partner watch the toaster for you, and come tell you when the toast is ready. Your partner can itself choose any of the above three strategies to coordinate its task of watching the toaster and telling you when they are ready.
On a final note, it's good to understand that while non-blocking and async (or what I prefer to call evented) do allow you to do other things while you wait, you don't have too. You can choose to constantly loop on checking the status of a non-blocking call, doing nothing else. That's often worse than blocking though (like looking at the toaster, then away, then back at it until it's done), so a lot of non-blocking APIs allow you to transition into a blocking mode from it. For evented, you can just wait idle until you are notified. The downside in that case is that adding the notification was complex and potentially costly to begin with. You had to buy a new toaster with beep functionality, or convince your partner to watch it for you.
And one more thing, you need to realize the trade offs all three provide. One is not obviously better than the others. Think of my example. If your toaster is so fast, you won't have time to wash a dish, not even begin washing it, that's how fast your toaster is. Getting started on something else in that case is just a waste of time and effort. Blocking will do. Similarly, if washing a dish will take 10 times longer then the toasting. You have to ask yourself what's more important to get done? The toast might get cold and hard by that time, not worth it, blocking will also do. Or you should pick faster things to do while you wait. There's more obviously, but my answer is already pretty long, my point is you need to think about all that, and the complexities of implementing each to decide if its worth it, and if it'll actually improve your throughput or performance.
Edit:
Even though this is already long, I also want it to be complete, so I'll add two more points.
There also commonly exists a fourth model known as multiplexed. This is when while you wait for one task, you start another, and while you wait for both, you start one more, and so on, until you've got many tasks all started and then, you wait idle, but on all of them. So as soon as any is done, you can proceed with handling its response, and then go back to waiting for the others. It's known as multiplexed, because while you wait, you need to check each task one after the other to see if they are done, ad vitam, until one is. It's a bit of an extension on top of normal non-blocking.
In our example it would be like starting the toaster, then the dishwasher, then the microwave, etc. And then waiting on any of them. Where you'd check the toaster to see if it's done, if not, you'd check the dishwasher, if not, the microwave, and around again.
Even though I believe it to be a big mistake, synchronous is often used to mean one thing at a time. And asynchronous many things at a time. Thus you'll see synchronous blocking and non-blocking used to refer to blocking and non-blocking. And asynchronous blocking and non-blocking used to refer to multiplexed and evented.
I don't really understand how we got there. But when it comes to IO and Computation, synchronous and asynchronous often refer to what is better known as non-overlapped and overlapped. That is, asynchronous means that IO and Computation are overlapped, aka, happening concurrently. While synchronous means they are not, thus happening sequentially. For synchronous non-blocking, that would mean you don't start other IO or Computation, you just busy wait and simulate a blocking call. I wish people stopped misusing synchronous and asynchronous like that. So I'm not encouraging it.
Edit2:
I think a lot of people got a bit confused by my definition of synchronous and asynchronous. Let me try and be a bit more clear.
Synchronous is defined as happening with predictable timing and/or ordering. That means you know when something will start and end.
Asynchronous is defined as not happening with predictable timing and/or ordering. That means you don't know when something will start and end.
Both of those can be happening in parallel or concurrently, or they can be happening sequentially. But in the synchronous case, you know exactly when things will happen, while in the asynchronous case you're not sure exactly when things will happen, but you can still put some coordination in place that at least guarantees some things will happen only after others have happened (by synchronizing some parts of it).
Thus when you have asynchronous processes, asynchronous programming lets you place some order guarantees so that some things happen in the right sequence, even though you don't know when things will start and end.
Here's an example, if we need to do A then B and C can happen at any time. In a sequential but asynchronous model you can have:
A -> B -> C
or
A -> C -> B
or
C -> A -> B
Every time you run the program, you could get a different one of those, seemingly at random. Now this is still sequential, nothing is parallel or concurrent, but you don't know when things will start and end, except you have made it so B always happens after A.
If you add concurrency only (no parallelism), you can also get things like:
A<start> -> C<start> -> A<end> -> C<end> -> B<start> -> B<end>
or
C<start> -> A<start> -> C<end> -> A<end> -> B<start> -> B<end>
or
A<start> -> A<end> -> B<start> -> C<start> -> B<end> -> C<end>
etc...
Once again, you don't really know when things will start and end, but you have made it so B is coordinated to always start after A ends, but that's not necessarily immediately after A ends, it's at some unknown time after A ends, and B could happen in-between fully or partially.
And if you add parallelism, now you have things like:
A<start> -> A<end> -> B<start> -> B<end> ->
C<start> -> C<keeps going> -> C<keeps going> -> C<end>
or
A<start> -> A<end> -> B<start> -> B<end>
C<start> -> C<keeps going> -> C<end>
etc...
Now if we look at the synchronous case, in a sequential setting you would have:
A -> B -> C
And this is the order always, each time you run the program, you get A then B and then C, even though C conceptually from the requirements can happen at any time, in a synchronous model you still define exactly when it will start and end. Off course, you could specify it like:
C -> A -> B
instead, but since it is synchronous, then this order will be the ordering every time the program is ran, unless you changed the code again to change the order explicitly.
Now if you add concurrency to a synchronous model you can get:
C<start> -> A<start> -> C<end> -> A<end> -> B<start> -> B<end>
And once again, this would be the order no matter how many time you ran the program. And similarly, you could explicitly change it in your code, but it would be consistent across program execution.
Finally, if you add parallelism as well to a synchronous model you get:
A<start> -> A<end> -> B<start> -> B<end>
C<start> -> C<end>
Once again, this would be the case on every program run. An important aspect here is that to make it fully synchronous this way, it means B must start after both A and C ends. If C is an operation that can complete faster or slower say depending on the CPU power of the machine, or other performance consideration, to make it synchronous you still need to make it so B waits for it to end, otherwise you get an asynchronous behavior again, where not all timings are deterministic.
You'll get this kind of synchronous thing a lot in coordinating CPU operations with the CPU clock, and you have to make sure that you can complete each operation in time for the next clock cycle, otherwise you need to delay everything by one more clock to give room for this one to finish, if you don't, you mess up your synchronous behavior, and if things depended on that order they'd break.
Finally, lots of systems have synchronous and asynchronous behavior mixed in, so if you have any kind of inherently unpredictable events, like when a user will click a button, or when a remote API will return a response, but you need things to have guaranteed ordering, you will basically need a way to synchronize the asynchronous behavior so it guarantees order and timing as needed. Some strategies to synchronize those are what I talk about previously, you have blocking, non-blocking, async, multiplexed, etc. See the emphasis on "async", this is what I mean by the word being confusing. Somebody decided to call a strategy to synchronize asynchronous processes "async". This then wrongly made people think that asynchronous meant concurrent and synchronous meant sequential, or that somehow blocking was the opposite of asynchronous, where as I just explained, synchronous and asynchronous in reality is a different concept that relates to the timing of things as being in sync (in time with each other, either on some shared clock or in a predictable order) or out of sync (not on some shared clock or in an unpredictable order). Where as asynchronous programming is a strategy to synchronize two events that are themselves asynchronous (happening at an unpredictable time and/or order), and for which we need to add some guarantees of when they might happen or at least in what order.
So we're left with two things using the word "asynchronous" in them:
Asynchronous processes: processes that we don't know at what time they will start and end, and thus in what order they would end up running.
Asynchronous programming: a style of programming that lets you synchronize two asynchronous processes using callbacks or watchers that interrupt the executor in order to let them know something is done, so that you can add predictable ordering between the processes.
A nonblocking call returns immediately with whatever data are available: the full number of bytes requested, fewer, or none at all.
An asynchronous call requests a transfer that will be performed in its whole(entirety) but will complete at some future time.
Putting this question in the context of NIO and NIO.2 in java 7, async IO is one step more advanced than non-blocking.
With java NIO non-blocking calls, one would set all channels (SocketChannel, ServerSocketChannel, FileChannel, etc) as such by calling AbstractSelectableChannel.configureBlocking(false).
After those IO calls return, however, you will likely still need to control the checks such as if and when to read/write again, etc.
For instance,
while (!isDataEnough()) {
socketchannel.read(inputBuffer);
// do something else and then read again
}
With the asynchronous api in java 7, these controls can be made in more versatile ways.
One of the 2 ways is to use CompletionHandler. Notice that both read calls are non-blocking.
asyncsocket.read(inputBuffer, 60, TimeUnit.SECONDS /* 60 secs for timeout */,
new CompletionHandler<Integer, Object>() {
public void completed(Integer result, Object attachment) {...}
public void failed(Throwable e, Object attachment) {...}
}
}
As you can probably see from the multitude of different (and often mutually exclusive) answers, it depends on who you ask. In some arenas, the terms are synonymous. Or they might each refer to two similar concepts:
One interpretation is that the call will do something in the background essentially unsupervised in order to allow the program to not be held up by a lengthy process that it does not need to control. Playing audio might be an example - a program could call a function to play (say) an mp3, and from that point on could continue on to other things while leaving it to the OS to manage the process of rendering the audio on the sound hardware.
The alternative interpretation is that the call will do something that the program will need to monitor, but will allow most of the process to occur in the background only notifying the program at critical points in the process. For example, asynchronous file IO might be an example - the program supplies a buffer to the operating system to write to file, and the OS only notifies the program when the operation is complete or an error occurs.
In either case, the intention is to allow the program to not be blocked waiting for a slow process to complete - how the program is expected to respond is the only real difference. Which term refers to which also changes from programmer to programmer, language to language, or platform to platform. Or the terms may refer to completely different concepts (such as the use of synchronous/asynchronous in relation to thread programming).
Sorry, but I don't believe there is a single right answer that is globally true.
Blocking call: Control returns only when the call completes.
Non blocking call: Control returns immediately. Later OS somehow notifies the process that the call is complete.
Synchronous program: A program which uses Blocking calls. In order not to freeze during the call it must have 2 or more threads (that's why it's called Synchronous - threads are running synchronously).
Asynchronous program: A program which uses Non blocking calls. It can have only 1 thread and still remain interactive.
Non-blocking: This function won't wait while on the stack.
Asynchronous: Work may continue on behalf of the function call after that call has left the stack
Synchronous means to start one after the other's result, in a sequence.
Asynchronous means start together, no sequence is guaranteed on the result
Blocking means something that causes an obstruction to perform the next step.
Non-blocking means something that keeps running without waiting for anything, overcoming the obstruction.
Blocking eg: I knock on the door and wait till they open it. ( I am idle here )
Non-Blocking eg: I knock on the door, if they open it instantly, I greet them, go inside, etc. If they do not open instantly, I go to the next house and knock on it. ( I am doing something or the other, not idle )
Synchrounous eg: I will go out only if it rains. ( dependency exists )
Asynchronous eg: I will go out. It can rain. ( independent events, does't matter when they occur )
Synchronous or Asynchronous, both can be blocking or non-blocking and vice versa
The blocking models require the initiating application to block when the I/O has started. This means that it isn't possible to overlap processing and I/O at the same time. The synchronous non-blocking model allows overlap of processing and I/O, but it requires that the application check the status of the I/O on a recurring basis. This leaves asynchronous non-blocking I/O, which permits overlap of processing and I/O, including notification of I/O completion.
To Simply Put,
function sum(a,b){
return a+b;
}
is a Non Blocking. while Asynchronous is used to execute Blocking task and then return its response
synchronous
asynchonous
block
Block I/O must be a synchronus I/O, becuase it has to be executed in order. Synchronous I/O might not be block I/O
Not exist
non-block
Non-block and Synchronous I/O at the same time is polling/multi-plexing..
Non-block and Asynchronous I/O at the same time is parallel execution, such as signal trigger…
block/non-block describe behavior of the initializing entity itself, it means what the entity does during wating for I/O completion
synchronous/asynchronous describe behavior between I/O initilaizing entity and I/O executor(the operating system, for example), it means whether these two entity can be executed parallelly
They differ in spelling only. There is no difference in what they refer to. To be technical you could say they differ in emphasis. Non blocking refers to control flow(it doesn't block.) Asynchronous refers to when the event\data is handled(not synchronously.)
Blocking: control returns to invoking precess after processing of primitive(sync or async) completes
Non blocking: control returns to process immediately after invocation