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What is a multithreading program and how does it work exactly? I read some documents but I'm confused. I know that code is executed line by line, but I can't understand how the program manages this.
A simple answer would be appreciated.c# example please (only animation!)
What is a multi-threading program and how does it work exactly?
Interesting part about this question is complete books are written on the topic, but still it is elusive to lot of people. I will try to explain in the order detailed underneath.
Please note this is just to provide a gist, an answer like this can never do justice to the depth and detail required. Regarding videos, best that I have come across are part of paid subscriptions (Wintellect and Pluralsight), check out if you can listen to them on trial basis, assuming you don't already have the subscription:
Wintellect by Jeffery Ritcher (from his Book, CLR via C#, has same chapter on Thread Fundamentals)
CLR Threading by Mike Woodring
Explanation Order
What is a thread ?
Why were threads introduced, main purpose ?
Pitfalls and how to avoid them, using Synchronization constructs ?
Thread Vs ThreadPool ?
Evolution of Multi threaded programming API, like Parallel API, Task API
Concurrent Collections, usage ?
Async-Await, thread but no thread, why they are best for IO
What is a thread ?
It is software implementation, which is purely a Windows OS concept (multi-threaded architecture), it is bare minimum unit of work. Every process on windows OS has at least one thread, every method call is done on the thread. Each process can have multiple threads, to do multiple things in parallel (provided hardware support).
Other Unix based OS are multi process architecture, in fact in Windows, even the most complex piece of software like Oracle.exe have single process with multiple threads for different critical background operations.
Why were threads introduced, main purpose ?
Contrary to the perception that concurrency is the main purpose, it was robustness that lead to the introduction of threads, imagine every process on Windows is running using same thread (in the initial 16 bit version) and out of them one process crash, that simply means system restart to recover in most of the cases. Usage of threads for concurrent operations, as multiple of them can be invoked in each process, came in picture down the line. In fact it is even important to utilize the processor with multiple cores to its full ability.
Pitfalls and how to avoid using Synchronization constructs ?
More threads means, more work completed concurrently, but issue comes, when same memory is accessed, especially for Write, as that's when it can lead to:
Memory corruption
Race condition
Also, another issue is thread is a very costly resource, each thread has a thread environment block, Kernel memory allocation. Also for scheduling each thread on a processor core, time is spent for context switching. It is quite possible that misuse can cause huge performance penalty, instead of improvement.
To avoid Thread related corruption issues, its important to use the Synchronization constructs, like lock, mutex, semaphore, based on requirement. Read is always thread safe, but Write needs appropriate Synchronization.
Thread Vs ThreadPool ?
Real threads are not the ones, we use in C#.Net, that's just the managed wrapper to invoke Win32 threads. Challenge remain in user's ability to grossly misuse, like invoking lot more than required number of threads, assigning the processor affinity, so isn't it better that we request a standard pool to queue the work item and its windows which decide when the new thread is required, when an already existing thread can schedule the work item. Thread is a costly resource, which needs to be optimized in usage, else it can be bane not boon.
Evolution of Multi threaded programming, like Parallel API, Task API
From .Net 4.0 onward, variety of new APIs Parallel.For, Parallel.ForEach for data paralellization and Task Parallelization, have made it very simple to introduce concurrency in the system. These APIs again work using a Thread pool internally. Task is more like scheduling a work for sometime in the future. Now introducing concurrency is like a breeze, though still synchronization constructs are required to avoid memory corruption, race condition or thread safe collections can be used.
Concurrent Collections, usage ?
Implementations like ConcurrentBag, ConcurrentQueue, ConcurrentDictionary, part of System.Collections.Concurrent are inherent thread safe, using spin-wait and much easier and quicker than explicit Synchronization. Also much easier to manage and work. There's another set API like ImmutableList System.Collections.Immutable, available via nuget, which are thread safe by virtue of creating another copy of data structure internally.
Async-Await, thread but no thread, why they are best for IO
This is an important aspect of concurrency meant for IO calls (disk, network), other APIs discussed till now, are meant for compute based concurrency so threads are important and make it faster, but for IO calls thread has no use except waiting for the call to return, IO calls are processed on hardware based queue IO Completion ports
A simple analogy might be found in the kitchen.
You've probably cooked using a recipe before -- start with the specified ingredients, follow the steps indicated in the recipe, and at the end you (hopefully) have a delicious dish ready to eat. If you do that, then you have executed a traditional (non-multithreaded) program.
But what if you have to cook a full meal, which includes a number of different dishes? The simple way to do it would be to start with the first recipe, do everything the recipe says, and when it's done, put the finished dish (and the first recipe) aside, then start on the second recipe, do everything it says, put the second dish (and second recipe) aside, and so on until you've gone through all of the recipes one after another. That will work, but you might end up spending 10 hours in the kitchen, and of course by the time the last dish is ready to eat, the first dish might be cold and unappetizing.
So instead you'd probably do what most chefs do, which is to start working on several recipes at the same time. For example, you might put the roast in the oven for 45 minutes, but instead of sitting in front of the oven waiting 45 minutes for the roast to cook, you'd spend the 45 minutes chopping the vegetables. When the oven timer rings, you put down your vegetable knife, pull the cooked roast out of the oven and let it cool, then go back to chopping vegetables, and so on. If you can do that, then you are successfully multitasking several recipes/programs. That is, you aren't literally working on multiple recipes at once (you still have only two hands!), but you are jumping back and forth from following one recipe to following another whenever necessary, and thereby making progress on several tasks rather than twiddling your thumbs a lot. Do this well and you can have the whole meal ready to eat in a much shorter amount of time, and everything will be hot and fresh at about the same time too. If you do this, you are executing a simple multithreaded program.
Then if you wanted to get really fancy, you might hire a few other chefs to work in the kitchen at the same time as you, so that you can get even more food prepared in a given amount of time. If you do this, your team is doing multiprocessing, with each chef taking one part of the total work and all of them working simultaneously. Note that each chef may well be working on multiple recipes (i.e. multitasking) as described in the previous paragraph.
As for how a computer does this sort of thing (no more analogies about chefs), it usually implements it using a list of ready-to-run threads and a timer. When the timer goes off (or when the thread that is currently executing has nothing to do for a while, because e.g. it is waiting to load data from a slow hard drive or something), the operating system does a context switch, in which pauses the current thread (by putting it into a list somewhere and no longer executing instructions from that thread's code anymore), then pulls another ready-to-run thread from the list of ready-to-run threads and starts executing instructions from that thread's code instead. This repeats for as long as necessary, often with context switches happening every few milliseconds, giving the illusion that multiple programs are running "at the same time" even on a single-core CPU. (On a multi-core CPU it does this same thing on each core, and in that case it's no longer just an illusion; multiple programs really are running at the same time)
Why don't you refer to Microsoft's very own documentation of the .net class System.Threading.Thread?
It has a handfull of simple example programs written in C# (at the bottom of the page) just as you asked for:
Thread Examples
actually multi thread is do multiple process at the same time together . and you can complete process parallel .
it's actually multi thread is do multiple process at the same time together . and you can complete process parallel . you can take task from your main thread then execute some other way and done .
I have a thread reading from a specific plc's memory and it works perfectly. Now what I want is to start another thread to test the behavior of the system (simulate the first thread) in case of a conectivity issue, and when everything is Ok, continue the first thread. But I think I'll have problems with that because these two threads will need to use the same port.
My first idea was to abort the first thread, start the second one and when the everything's OK again, abort this thread and 'restart' the first one.
I've read some other forums and people say that aborting or suspending a thread is the worst solution, and I've read about syncronization of threads but I dont really know if this is useful in this case because I've never used it.
My question is, what is the correct way to solve this kind of situations?
You have a shared resource that you need to coordinate thread access to. There are a number of mechanisms in .NET available for that coordination.
There is a wonderful resource that provides both an introduction to thread concepts in .NET, and discusses advanced concepts in an approachable manner
http://www.albahari.com/threading/
In your case, have a look at the section on locking
Exclusive locking is used to ensure that only one thread can enter particular sections of code at a time. The two main exclusive locking constructs are lock and Mutex. Of the two, the lock construct is faster and more convenient. Mutex, though, has a niche in that its lock can span applications in different processes on the computer.
http://www.albahari.com/threading/part2.aspx#_Locking
You can structure your two threads so that they must acquire a specific lock to work with the port. Have your first thread release that lock before you start the second thread, then have the first thread wait to acquire that lock again (which the second thread will hold until done).
I want to use a ConcurrentDictionary in my app, but first I need to make sure I understand correctly how it works. In my app, I'll have one or more threads that write to, or delete from, the dictionary. And, I'll have one or more threads that read from the dictionary. Potentially, all at the same time.
Am I correct that the implementation of ConcurrentDictionary takes care of all the required locking for this to happen, and I don't need to provide my own locking? In other words, if one thread is writing to, or deleting from, the dictionary, a reading thread (or another write thread) will be blocked until the update or delete is finished?
Thanks very much.
The current implementation uses a mixture of striped locks (the technique I suggested in an answer to someone yesterday at https://stackoverflow.com/a/11950835/400547) and thinking very very hard about the situations in which an operation cannot possibly cause problems for or have problems cause by, a concurrent operation (there's quite a lot of these, but you have to be very sure if you make use of them).
As such if you have several operations happening on the concurrent dictionary at once, each of the following is possible:
No threads even lock, but everything happens correctly.
Some threads lock, but they lock on separate things, and there is no lock contention.
One or two threads have lock contention with each other, and are slowed down, but the effect upon performance is less than if there were a single lock.
One or two threads need to lock the entire thing for a while (generally for internal resizing) which blocks all the threads that could possibly be blocked in case 3 above, though some can keep going (those that read).
None of this involves dirty reads, which is a matter only vaguely related to locking (my own form of concurrent dictionary uses no locks at all, and it doesn't have dirty reads either).
This thread-safety doesn't apply to batches done by your code (if you read a value and then write a value, the value read may have changed before you finished the write), but note that some common cases which would require a couple of calls on Dictionary are catered for by single methods on ConcurrentDictionary (GetOrAdd and AddOrUpdate do things that would be two calls with a Dictionary so they can be done atomically - though note that the Func involved in some overloads may be called more than once).
Due to this, there's no added danger with ConcurrentDictionary, so you should pick as follows:
If you're going to have to lock over some batches of operations that don't match what ConcurrentDictionary offers like e.g.:
lock(lockObj)
{
var test = dict[key1];
var test2 = dict[key2];
if(test < test2 && test2 < dict[key3] && SomeOtherBooleanProducer())
dict[key4] = SomeFactoryCall(key4);
}
Then you would have to lock on ConcurrentDictionary, and while there may be a way to combine that with what it offers in the way of support for concurrency, there probably won't, so just use Dictionary with a lock.
Otherwise it comes down to how much concurrent hits there will probably be. If you're mostly only going to have one thread hitting the dictionary, but you need to guard against the possibility of concurrent access, then you should definitely go for Dictionary with a lock. If you're going to have periods where half a dozen or more threads are hitting the dictionary, then you should definitely go for ConcurrentDictionary (if they're likely to be hitting the same small number of keys then take a look at my version because that's the one situation where I have better performance).
Just where the middle point between "few" and "many" threads lies, is hard to say. I'd say that if there are more than two threads on a regular basis then go with ConcurrentDictionary. If nothing else, demands from concurrency tend to increase throughout the lifetime of a project more often than they decrease.
Edit: To answer about the particular case you give, of one writer and one reader, there won't be any blocking at all, as that is safe for roughly the same reason why multiple readers and one writer is safe on Hashtable, though ConcurrentDictionary goes beyond that in several ways.
In other words, if one thread is writing to, or deleting from, the dictionary, a reading thread (or another write thread) will be blocked until the update or delete is finished?
I don't believe it will block - it will just be safe. There won't be any corruption - you'll just have a race in terms of whether the read sees the write.
From a FAQ about the lock-free-ness of the concurrent collections:
ConcurrentDictionary<TKey,TValue> uses fine-grained locking when adding to or updating data in the dictionary, but it is entirely lock-free for read operations. In this way, it’s optimized for scenarios where reading from the dictionary is the most frequent operation.
I read about lock, though not understood nothing at all.
My question is why do we use a un-used object and lock that and how this makes something thread-safe or how this helps in multi-threading ? Isn't there other way to make thread-safe code.
public class test {
private object Lock { get; set; }
...
lock (this.Lock) { ... }
...
}
Sorry is my question is very stupid, but i don't understand, although i've used it many times.
Accessing a piece of data from one thread while other thread is modifying it is called "data race condition" (or just "data race") and can lead to corruption of data. (*)
Locks are simply a mechanism for avoiding data races. If two (or more) concurrent threads lock the same lock object, then they are no longer concurrent and can no longer cause data races, for the duration of the lock. Essentially, we are serializing the access to shared data.
The trick is to keep your locks as "wide" as you must to avoid data races, yet as "narrow" as you can to gain performance through concurrent execution. This is a fine balance that can easily go out of whack in either direction, which is why multi-threaded programming is hard.
Some guidelines:
As long all threads are just reading the data and none will ever modify it, lock is unnecessary.
Conversely, if at least one thread might at some point modify the data, then all concurrent code paths accessing that same data must be properly serialized through locks, even those that only read the data.
Using a lock in one code path but not the other will leave the data wide open to race conditions.
Also, using one lock object in one code path, but a different lock object in another (concurrent) code path does not serialize these code paths and leaves you wide open to data races.
On the other hand, if two concurrent code paths access different data, they can use different lock objects. But, whenever there is more than one lock object, watch out for deadlocks. A deadlock is often also a "code race condition" (and a heisenbug, see below).
The lock object does not need to be (and usually isn't) the same thing as the data you are trying to protect. Unfortunately, there is no language facility that lets you "declare" which data is protected by which lock object, so you'll have to very carefully document your "locking convention" both for other people that might maintain your code, and for yourself (since even after a short time you will forget some of the nooks and crannies of your locking convention).
It's usually a good idea to protect the lock object from the outside world as much as you can. After all, you are using it for the very sensitive task of locking and you don't want it locked by external actors in unforeseen ways. That's why using this or a public field as a lock object is usually a bad idea.
The lock keyword is simply a more convenient syntax for Monitor.Enter and Monitor.Exit.
The lock object can be any object in .NET, but value objects will be boxed in the call to Monitor.Enter, which means threads will not share the same lock object, leaving the data unprotected. Therefore, only use reference types as lock objects.
For inter-process communication you can use a global mutex, which can be created by passing a non-empty name to Mutex Constructor. Global mutexes provide essentially the same functionality as regular "local" locking, except they can be shared between separate processes.
There are synchronization mechanisms other than locks, such as semaphores, condition variables, message queues or atomic operations. Be careful when mixing different synchronization mechanisms.
Locks also behave as memory barriers, which is increasingly important on modern multi-core, multi-cache CPUs. This is part of the reason why you need locks on reading the data and not just writing.
(*) It is called "race" because concurrent threads are "racing" towards performing an operation on the shared data and whoever wins that race determines the outcome of the operation. So the outcome depends on timing of the execution, which is essentially random on modern preemptive multitasking OSes. Worse yet, timing is easily modified by a simple act of observing the program execution through tools such as debugger, which makes them "heisenbugs" (i.e. the phenomenon being observed is changed by the mere act of observation).
Lock object is like a door into the single room where only one guest per time can enter.
The room can be your data, the guest can be your function.
define data (room)
add door (lock object)
invite guests (functions)
using lock insctruction close/open door to allow only one guest per time enter into the room.
Why we need this? If you simulatniously write a data in a file (just an example, can be 1000s others) you will need to sync an access of your funcitons (close/open door for guests) to the write file, so any function will append to the end of the file (assuming that is requierement of this example)
This is naturally not only way sync the threads, there are more out there:
Monitors
Wait hadlers
...
Check out the link for complete information and description of each of them
Thread Synchronization
Yes, there is indeed another way:
using System.Runtime.CompilerServices;
class Test
{
private object Lock { get; set; }
[MethodImpl(MethodImplOptions.Synchronized)]
public void Foo()
{
// Now this instance is locked
}
}
While it looks more "natural", it's not used often, because of the fact that the object is locking on itself this way, so other code could not risk locking on this object -- it could cause a deadlock.
Because of this, you usually create a (lazy-initialized) private field referring to an object, and use that object as a lock instead. This will guarantee that no one else can lock against the same object as you.
A little more detail on what's happening beneath the hood:
When you "lock on an object", you're not locking on the object itself. Rather, you're using the object as a guaranteed-to-be-unique-address-in-memory throughout your program. When you "lock", the runtime takes the object's address, uses it to look up the actual lock inside another table (which is hidden from you), and uses that object as the ""lock" (also known as a "critical section").
So really, for you, an object is just a proxy/symbol -- it isn't doing anything by itself; it's just acting as a unique indicator that will never clash with another valid object in the same program.
When you have different threads accessing same variable/resource at the same time they may over write on this variable/resource and you can have unexpected results. Lock will make sure only one thread can assess variable at on time and remain thread will queue to get access to this variable/resource till lock is released
suppose we have balance variable of an account.
Two different thread read its value which was 100
Suppose first thread adds 50 to it like 100 + 50 and saves it and balance will have 150
As second thread already read 100 and mean while. suppose it subtract 50 like 100-50 but point to note here is that first thread has made the balance 150 so second thread should to 150-50 this could cause serious problems.
So lock makes sure that when on thread wants to change some resource states it locks it and leaves after committing change
The lock statement introduces the concept of mutual exclusion. Only one thread can acquire a lock on a given object at any one time. This prevents threads from accessing shared data structures concurrently, thus corrupting them.
If other threads already hold a lock, the lock statement will block until it is able to acquire an exclusive lock on its argument before allowing its block to execute.
Note that the only thing lock does is control entry to the block of code. Access to members of the class is completely unrelated to the lock. It is up to the class itself to ensure that accesses that must be synchronized are coordinated by the use of lock or other synchronization primitives. Also note that access to some or all members may not have to be synchronized. For instance, if you want to maintain a counter, you could use the Interlocked class without locking.
An alternative to locking is lock-free data structures, which behave correctly in the presence of multiple threads. Operations on lock-free data structures must be designed very carefully, usually with the assistance of lock-free primitives such as compare-and-swap (CAS).
The general theme of such techniques is to try to perform operations on data structures atomically and detect when operations fail due to concurrent actions by other threads, followed by retries. This works well on a lightly loaded system where failures are unlikely, but can produce runaway behaviour as the failure rate climbs and retries become a dominant load. This problem can be ameliorated by backing off the retry rate, effectively throttling the load.
A more sophisticated alternative is software transactional memory. Unlike CAS, STM generalizes the concept of fail-and-retry to arbitrarily complex memory operations. In simple terms, you start a transaction, perform all your operations, and finally commit. The system detects if the operations cannot succeed due to conflicting operations performed by other threads that beat the current thread to the punch. In such cases, STM can either fail outright, requiring the application to take corrective action, or, in more sophisticated implementations, it can automatically go back to the start of the transaction and try again.
Your confusion is pretty typical for those just getting familiar with the lock keyword in C#. You are right, the object used in the lock statement is really nothing more than a token that defines a critical section. That object, in no way, has any protection from multithreaded access itself.
The way this works is that the CLR reserves a 4 byte (32-bit systems) section in the object header (type handle) called the sync block. The sync block is nothing more than an index into an array that stores the actual critical section information. When you use the lock keyword the CLR will modify this sync block value accordingly.
There are advantages and disadvantages to this scheme. The advantage is that it made for a fairly elegant solution to defining critical sections. One obvious disadvantage is that each object instance contains the sync block and most instances never use it so it would seem to be a waste of space in most cases. Another disadvantage is that boxed value types can be used which is almost always wrong and certainly leads to confusion.
I remember way back when .NET was first released that there was a lot of chatter over whether the lock keyword was good or bad for the language. The general consensus (at least as I remember it) was that it was bad because the using keyword could have been easily used instead. In fact, a solution that used the using keyword actually would have made more sense because it could have been done without the need for the sync block. The c# design team even went on record to say that had they been given a second chance the lock keyword never would have made it into the language.1
1The only reference I could find for this is on Jon Skeet's website here.
I was wondering what are the advantages of using a upgradable read lock as opposed performing these steps:
Take read lock
Check condition to see if we need to take write lock
Release Read Lock
Take Write Lock
Perform update
Release Write Lock
One apparent disadvantage of the performing the above steps as opposed taking an upgradable read lock is, that there is an window of time between the steps 3 and 4, where another thread can take up a write lock.
Apart from this advantage what other advantages do you find for taking upgradable read lock over the steps I have mentioned above?
Let's consider the different ways in which one can use a reader-writer lock that doesn't have a separate "upgradable reader".
With your pattern, there is a race between step 3 and 4 as you point out, where another thread can take the writer lock. More to the point, there is a step between 3 and 4 where a thread can take the writer lock and change the state we observed in step 2.
Therefore, we've got four choices depending on how likey this is to happen:
We stay with your approach because this is actually impossible (e.g. a given state transition is one-way in our application, so once observed it is permanent). In this case though we could quite possibly have remodelled so as to not need a lock at all. (One-way transitions lend themselves to lock-free techniques).
We just take the writer lock in the first place, because the state we observe in step 2 is very likely to change and it's a waste of time checking it with a reader lock.
We change your steps to:
Take read lock
Check condition to see if we need to take write lock
Release Read Lock
Take Write Lock
Re-check the condition in case it changed.
Perform update
Release Write Lock
We change to:
Take a read lock on a recursion-supporting lock.
Check to see if we need to take write lock.
Take write lock (no release of read).
Perform update.
Release write lock.
Release read lock.
It's not hard to see why 4 was more tempting to some, though it is only slightly harder to see how it makes deadlocks easy to create. Sadly, that slightly harder is just enough for a lot of people to see the advantages without seeing the disadvantages.
For anyone who doesn't spot it, if two threads have a read lock and one of them upgrades to a write lock it must wait for the other to release the read-lock. However if that second thread upgrades to a write lock without releasing the read-lock then it will wait forever on the first thread, which will wait forever on it.
As said above, just which approach is best depends on how likely it is for the state to change in the meantime (or how promptly we want to react to it, I suppose). Even the last approach with the non-releasing upgrade can have its place in viable code, as long as there can only ever be one thread that ever tries to upgrade its lock without releasing.
Aside from the special case where the last option works, the difference between the other options are all about performance, and which is most performant mostly depends on the cost of re-checking the state and the likelihood of the write being aborted due to a change in the meantime.
However, note that all of them involve taking a writer lock, so all of them have the effect of blocking all reading threads, even when the write is indeed aborted.
Upgradable read-locks give us a middle-ground because while they block write-locks and other upgradable read-locks, they don't block read locks. They are perhaps better though of not as read-locks that can upgrade as a write-locks that have yet to commit to writing.* In the cases where it was decided not to upgrade, the effect on the reading threads is nil.
This means that if it's even slightly possible that the thread will decide not to change the state, the reading threads are not affected, and the performance improvement can certainly justify it's use.
*For that matter, "reader-writer" is a bit of a misnomer, we could e.g. protect an array of ints or objects with a ReaderWriterLockSlim, use the read-locks for both reading and writing individual items atomically and use the write-locks for operations that need to read the entire array without parts of it changing as it reads. In such a case it's a reading operation than needs the exclusive lock, while writing operations are fine with the shared lock.
It also prevents deadlocks that may happen because different threads operate at the same time and they wait for each other to release the locks.