What is the difference between non blocking and asynchronous calls - asynchronous

What is the difference when you say the call is non blocking vs when you say the call is asynchronous

If Asynchronous property for any ajax call is set true then script execution will pause until first request response will not come, That's why it's blocking.

Related

Does the ZooKeeper asynchronous api watcher callback arrive before the completion callback?

I used zookpeer asynchronous api with c client to monitor my cluster, such as zwget. I found some confusing bugs when my app is running for a while (zookeeper cluster was unstable and a new leader may be selected in this time).
The problem is:
The Watcher of the asynchronous api is called first before completion callback.
And I have searched zookeeper offical docs,so the following passage hints that it is possible for the asynchronous API to notify Watcher before the completion callback, am I right?
Synchronous calls may not return in the correct order. For example, assume a client does the following processing: issues an asynchronous read of node /a with watch set to true, and then in the completion callback of the read it does a synchronous read of /a. (Maybe not good practice, but not illegal either, and it makes for a simple example.)
Note that if there is a change to /a between the asynchronous read and the synchronous read, the client library will receive the watch event saying /a changed before the response for the synchronous read, but because the completion callback is blocking the event queue, the synchronous read will return with the new value of /a before the watch event is processed.

Flink timer async

I have a question regarding Flink and its timer service.
I have a keyBy stream which uses a timer,
When the timer is called I need to send an http request which might take time to respond.
My question is, should I make the http call async?
or flink is making the timer call already as a new thread with async per key?
Thanks in advance
You can use a ProcessFunction that stores the data required for the HTTP request, and that can have a timer. When it fires, you emit a record that has the request data, which a subsequent AsyncFunction will use to make the periodic request that you need.
If You are asking if the onTimer method is invoked in a separate thread for each key, then I am pretty sure that it is not. So, You would need to invoke the HTTP call asynchronously in this case.
But to be completely honest, I don't think this is a good idea, in general, to use the onTimer function to perform HTTP calls. I don't know anything about Your use-case, but I think You should consider using different mechanisms like creating side-output and then using the Flink Async operator. Using asynchronous calls inside the onTimer can be tricky, especially if You consider things like retries, timeouts and possible failures.
So according to comment the use-case is to make a call to service each X mins and then post something to Kafka. So, what You could do is to simply have a process function that schedules timers. Each time the timer is fired You then generate some output record with data needed for request if there is any data needed. Then You use the Async operator to actually perform the requests, parse the response and based on the response generate some output record that can be then saved to Kafka.

How is asynchronous callback implemented?

How do all the languages implements asynchronous callbacks?
For example in C++, one need to have a "monitor thread" to start a std::async. If it is started in main thread, it has to wait for the callback.
std::thread t{[]{std::async(callback_function).get();}}.detach();
v.s.
std::async(callback_function).get(); //Main thread will have to wait
What about asynchronous callbacks in JavaScript? In JS callbacks are massively used... How does V8 implement them? Does V8 create a lot of threads to listen on them and execute callback when it gets message? Or does it use one thread to listen on all the callbacks and keep refreshing?
For example,
setInterval(function(){},1000);
setInterval(function(){},2000);
Does V8 create 2 threads and monitor each callback state, or it has a pool thing to monitor all the callbacks?
V8 does not implement asynchronous functions with callbacks (including setInterval). Engine simply provides a way to execute JavaScript code.
As a V8 embedder you can create setInterval JavaScript function linked to your native C++ function that does what you want. For example, create thread or schedule some job. At this point it is your responsibility to call provided callback when it is necessary. Only one thread at a time can use V8 engine (V8 isolate instance) to execute code. This means synchronization is required if a callback needs to be called from another thread. V8 provides locking mechanism is you need this.
Another more common approach to solve this problem is to create a queue of functions for V8 to execute and use infinite queue processing loop to execute code on one thread. This is basically an event loop. This way you don't need to use execution lock, but instead use another thread to push callback function to a queue.
So it depends on a browser/Node.js/other embedder how they implement it.
TL;DR: To implement asynchronous callback is basically to allow the control flow to proceed without blocking for the callback. Before the callback function is finally called, the control flow is free to execute anything that has no dependence on the callback's result, e.g., the caller can proceed as if the callback function has returned, or the caller may yield its control to other functions.
Since the question is for general implementation rather than a specific language, my answer tries to be as general as to cover the implementation commonalities.
Different languages have different implementations for asynchronous callbacks, but the principles are the same. The key is to decouple the control flow from the code executed. They correspond to the execution context (like a thread of control with a runtime stack) and the executed task. Traditionally the execution context and the executed task are usually 1:1 associated. With asynchronous callbacks, they are decoupled.
1. The principles
To decouple the control flow from the code, it is helpful to think of every asynchronous callback as a conditional task. When the code registers an asynchronous callback, it virtually installs the task's condition in the system. The callback function is then invoked when the condition is satisfied. To support this, a condition monitoring mechanism and a task scheduler are needed, so that,
The programmer does not need to track the callback's condition;
Before the condition is satisfied, the program may proceed to execute other code that does not depend on the callback's result, without blocking on the condition;
Once the condition is satisfied, the callback is guaranteed to execute. The programmer does not need to schedule its execution;
After the callback is executed, its result is accessible to the caller.
2. Implementation for Portability
For example, if your code needs to process the data from a network connection, you do not need to write the code checking the connection state. You only registers a callback that will be invoked once the data is available for processing. The dirty work of connection checking is left to the language implementation, which is known to be tricky especially when we talk about scalability and portability.
The language implementation may employ asynchronous io, nonblocking io or a thread pool or whatever techniques to check the network state for you, and once the data is ready, the callback function is then scheduled to execute. Here the control flow of your code looks like directly going from the callback registration to the callback execution, because the language hides the intermediate steps. This is the portability story.
3. Implementation for Scalability
To hide the dirty work is only part of the whole story. The other part is that, your code itself does not need to block waiting for the task condition. It does not make sense to wait for one connection's data when you have lots of network connections simultaneously and some of them may already have data ready. The control flow of your code can simply register the callback, and then moves on with other tasks (e.g., the callbacks whose conditions have been satisfied), knowing that the registered callbacks will be executed anyway when their data are available.
If to satisfy the callback's condition does not involve much of the CPU (e.g., waiting for a timer, or waiting for the data from network), and the callback function itself is light-weighted, then single CPU (or single thread) is able to process lots of callbacks concurrently, such as incoming network requests processing. Here the control flow may look like jumping from one callback to another. This is the scalability story.
4. Implementation for Parallelism
Sometimes, the callbacks are not pending for non-blocking IO condition, but for blocking operations such as page fault; or the callbacks do not rely on any condition, but are pure computation logics. In this case, asynchronous callback does not save you the CPU waiting time (because there is no idle waiting). But since asynchronous callback implies that the callback function can be executed in parallel with the caller or other callbacks (subject to certain data sharing and synchronization constraints), the language implementation can dispatch the callback tasks to different threads, achieving the benefits of parallelism, if the platform has more than one hardware thread context. It still improves scalability.
5. Implementation for Productivity
The productivity with asynchronous callback may not be very positive when the code need to deal with chained callbacks, i.e., when callbacks register other callbacks in recursive way, known as callback hell. There are ways to rescue.
The semantics of an asynchronous callback can be explored so as to substitute the hopeless nested callbacks with other language constructs. Basically there can be two different views of callbacks:
From data flow point of view: asynchronous callback = event + task.
To register a callback essentially generates an event that will emit
when the task condition is satisfied. In this view, the chained
callbacks are just events whose processing triggers other event
emission. It can be naturally implemented in event-driven
programming, where the task execution is driven by events. Promise
and Observable may also be regarded as event-driven concept. When
multiple events are ready concurrently, their associated tasks can
be executed concurrently as well.
From control flow point of view: to register a callback yields the
control to other code, and the callback execution just resumes the
control flow once its condition is satisfied. In this view, chained
asynchronous callbacks are just resumable functions. Multiple
callbacks can be written as one after another in traditional
"synchronous" way, with yield operation in between (or await). It
actually becomes coroutine.
I haven't discussed the implementation of data passing between the asynchronous callback and its caller, but that is usually not difficult if using shared memory where caller and callback can share data. Actually Golang's channel can also be considered in line of yield/await but with its focus on data passing.
The callbacks that are passed to browser APIs, like setTimeout, are pushed into the same browser queue when the API has done its job.
The engine can check this queue when the stack is empty and push the next callback into the JS stack for execution.
You don’t have to monitor the progress of the API calls, you asked it to do a job and it will put your callback in the queue when it’s done.

Web API 2 - are all REST requests asynchronous?

Do I need to do anything to make all requests asynchronous or are they automatically handled that way?
I ran some tests and it appears that each request comes in on its own thread, but I figure better to ask as I might have tested wrong.
Update: (I have a bad habit of not explaining fully - sorry) Here's my concern. A client browser makes a REST request to my server of http://data.domain/com/employee_database/?query=state:Colorado. That comes in to the appropriate method in the controller. That method queries the database and returns an object which is then turned into a JSON structure and returned to the calling app.
Now let's say 10,000 clients all make a similar query to the same server. So I have 10,000 requests coming in at once. Will my controller method be called simultaneously in 10,000 distinct threads? Or must the first request return before the second request is called?
I'm not asking about the code in my handler method having asynchronous components. For my case the request becomes a single SQL query so the code has nothing that can be handled asynchronously. And until I get the requested data, I can't return from the method.
No REST is not async by default. the request are handled synchronously. However, your web server (IIS) has a number of max threads setting which can work at the same time, and it maintains a queue of the request received. So, the request goes in the queue and if a thread is available it gets executed else, the request waits in the IIS queue till a thread is available
I think you should be using async IO/operations such as database calls in your case. Yes in Web Api, every request has its own thread, but threads can run out if there are many consecutive requests. Also threads use memory so if your api gets hit by too many request it may put pressure on your system.
The benefit of using async over sync is that you use your system resources wisely. Instead of blocking the thread while it is waiting for the database call to complete in sync implementation, the async will free the thread to handle more requests or assign it what ever process needs a thread. Once IO (database) call completes, another thread will take it from there and continue with the implementation. Async will also make your api run faster if your IO operations take longer to complete.
To be honest, your question is not very clear. If you are making an HTTP GET using HttpClient, say the GetAsync method, request is fired and you can do whatever you want in your thread until the time you get the response back. So, this request is asynchronous. If you are asking about the server side, which handles this request (assuming it is ASP.NET Web API), then asynchronous or not is up to how you implemented your web API. If your action method, does three things, say 1, 2, and 3 one after the other synchronously in blocking mode, the same thread is going to the service the request. On the other hand, say #2 above is a call to a web service and it is an HTTP call. Now, if you use HttpClient and you make an asynchronous call, you can get into a situation where one request is serviced by more than one thread. For that to happen, you should have made the HTTP call from your action method asynchronously and used async keyword. In that case, when you call await inside the action method, your action method execution returns and the thread servicing your request is free to service some other request and ultimately when the response is available, the same or some other thread will continue from where it was left off previously. Long boring answer, perhaps but difficult to explain just through words by typing, I guess. Hope you get some clarity.
UPDATE:
Your action method will execute in parallel in 10,000 threads (ideally). Why I'm saying ideally is because a CLR thread pool having 10,000 threads is not typical and probably impractical as well. There are physical limits as well as limits imposed by the framework as well but I guess the answer to your question is that the requests will be serviced in parallel. The correct term here will be 'parallel' but not 'async'.
Whether it is sync or async is your choice. You choose by the way to write your action. If you return a Task, and also use async IO under the hood, it is async. In other cases it is synchronous.
Don't feel tempted to slap async on your action and use Task.Run. That is async-over-sync (a known anti-pattern). It must be truly async all the way down to the OS kernel.
No framework can make sync IO automatically async, so it cannot happen under the hood. Async IO is callback-based which is a severe change in programming model.
This does not answer what you should do of course. That would be a new question.

Is ASMX WebService or WCF or aspx pages are async by default?

I involved my self within a bet, our feud is about - Async WebServices and the other stuff i mentioned above.
I am thinking logically web service by default is sync, the other said that it is not correct.
Who is right or wrong can any one explain it to me?
Thanks in advance.
All of them are by default synchronous but you can write all of them asynchronously and you can call all of them asynchronously. You should always differ between synchronous/asynchronous call and between synchronous/asynchronous execution.
Calls
Synchronous - client calls the service/page and hangs on until the service/page returns the response.
Asynchronous - client calls the service/page and can continue in work. Client is usually notified by some event (or it can poll the result) that response has arrived. In ASPX this is typical callback or AJAX call.
Execution:
Synchronous - service/page receives the call and process it. Every external processing (file access, calling other services, calling database) is done synchronously and the service/page block the executing thread for the whole duration of the request processing.
Asynchronous - service/page receives the call, prepares external processing and executes it asynchronously. Processing thread is returned back to thread pool and can server other requests in the meanwhile. Once external processing ends service/page execution is again scheduled to receive a thread from thread pool and it finishes execution and returns response. This is usually only need on high traffic pages/services with intensive external communication.
These two types of asynchronous processing are completely independent. You can have asynchronous calls to synchronous services and any other combination.

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