The following is a snippet of a larger program and is done using Pthreads.
The UpdateFunction reads from a text file. The FunctionMap is just used to output (key,1). Here essentially UpdateFunction and FunctionMap run on different threads.
queue <list<string>::iterator> mapperpool;
void *UpdaterFunction(void* fn) {
std::string *x = static_cast<std::string*>(fn);
string filename = *x;
ifstream file (filename.c_str());
string word;
list <string> letterwords[50];
char alphabet = '0';
bool times = true;
int charno=0;
while(file >> word) {
if(times) {
alphabet = *(word.begin());
times = false;
}
if (alphabet != *(word.begin())) {
alphabet = *(word.begin());
mapperpool.push(letterwords[charno].begin());
letterwords[charno].push_back("xyzzyspoon");
charno++;
}
letterwords[charno].push_back(word);
}
file.close();
cout << "UPDATER DONE!!" << endl;
pthread_exit(NULL);
}
void *FunctionMap(void *i) {
long num = (long)i;
stringstream updaterword;
string toQ;
int charno = 0;
fprintf(stderr, "Print me %ld\n", num);
sleep(1);
while (!mapperpool.empty()) {
list<string>::iterator it = mapperpool.front();
while(*it != "xyzzyspoon") {
cout << "(" << *it << ",1)" << "\n";
cout << *it << "\n";
it++;
}
mapperpool.pop();
}
pthread_exit(NULL);
}
If I add the while(!mapperpool.empty()) in the UpdateFunction then it gives me the perfect output. But when I move it back to the FunctionMap then it gives me a weird out and Segfaults later.
Output when used in UpdateFunction:
Print me 0
course
cap
class
culture
class
cap
course
course
cap
culture
concurrency
.....
[Each word in separate line]
Output when used in FunctionMap (snippet shown above):
Print me 0
UPDATER DONE!!
(course%0+�0#+�0�+�05P+�0����cap%�+�0�+�0,�05�+�0����class5P?�0
����xyzzyspoon%�+�0�+�0(+�0%P,�0,�0�,�05+�0����class%p,�0�,�0-�05�,�0����cap%�,�0�,�0X-�05�,�0����course%-�0 -�0�-�050-�0����course%-�0p-�0�-�05�-�0����cap%�-�0�-�0H.�05�-�0����culture%.�0.�0�.�05 .�0
����concurrency%P.�0`.�0�.�05p.�0����course%�.�0�.�08/�05�.�0����cap%�.�0/�0�/�05/�0Segmentation fault (core dumped)
How do I fix this issue?
list <string> letterwords[50] is local to UpdaterFunction. When UpdaterFunction finishes, all its local variables got destroyed. When FunctionMap inspects iterator, that iterator already points to deleted memory.
When you insert while(!mapperpool.empty()) UpdaterFunction waits for FunctionMap completion and letterwords stays 'alive'.
Here essentially UpdateFunction and FunctionMap run on different threads.
And since they both manipulate the same object (mapperpool) and neither of them uses either pthread_mutex nor std::mutex (C++11), you have a data race. If you have a data race, you have Undefined Behaviour and the program might do whatever it wants. Most likely it will write garbage all over memory until eventually crashing, exactly as you see.
How do I fix this issue?
By locking the mapperpool object.
Why is list not thread-safe?
Well, in vast majority of use-cases, a single list (or any other collection) won't be used by more than one thread. In significant part of the rest the lock will have to extend over more than one operation on the collection, so the client will have to do its own locking anyway. The remaining tiny percentage of cases where locking in the operations themselves would help is not worth adding the overhead for everyone; C++ key design principle is that you only pay for what you use.
The collections are only reentrant, meaning that using different instances in parallel is safe.
Note on pthreads
C++11 introduced threading library that integrates well with the language. Most notably, it uses RAII for locking of std::mutex via std::lock_guard, std::unique_lock and std::shared_lock (for reader-writer locking). Consistently using these can eliminate large class of locking bugs that otherwise take considerable time to debug.
If you can't use C++11 yet (on desktop you can, but some embedded platforms did not get a compiler update yet), you should first consider Boost.Thread as it provides the same benefits.
If you can't use even then, still try to find, or write, a simple RAII wrapper for locking like the C++11/Boost do. The basic wrapper is just a couple of lines, but it will save you a lot of debugging.
Note that C++11 and Boost also have atomic operations library that pthreads sorely miss.
Related
I have made multiple runs of the program. I do not see that the output is incorrect, even though I do not use the mutex. My goal is to demonstrate the need of a mutex. My thinking is that different threads with different "num" values will be mixed.
Is it because the objects are different?
using VecI = std::vector<int>;
class UseMutexInClassMethod {
mutex m;
public:
VecI compute(int num, VecI veci)
{
VecI v;
num = 2 * num -1;
for (auto &x:veci) {
v.emplace_back(pow(x,num));
std::this_thread::sleep_for(std::chrono::seconds(1));
}
return v;
}
};
void TestUseMutexInClassMethodUsingAsync()
{
const int nthreads = 5;
UseMutexInClassMethod useMutexInClassMethod;
VecI vec{ 1,2,3,4,5 };
std::vector<std::future<VecI>> futures(nthreads);
std::vector<VecI> outputs(nthreads);
for (decltype(futures)::size_type i = 0; i < nthreads; ++i) {
futures[i] = std::async(&UseMutexInClassMethod::compute,
&useMutexInClassMethod,
i,vec
);
}
for (decltype(futures)::size_type i = 0; i < nthreads; ++i) {
outputs[i] = futures[i].get();
for (auto& x : outputs[i])
cout << x << " ";
cout << endl;
}
}
If you want an example that does fail with a high degree of certainty you can look at the below. It sets up a variable called accumulator to be shared by reference to all the futures. This is what is missing in your example. You are not actually sharing any memory. Make sure you understand the difference between passing by reference and passing by value.
#include <vector>
#include <memory>
#include <thread>
#include <future>
#include <iostream>
#include <cmath>
#include <mutex>
struct UseMutex{
int compute(std::mutex & m, int & num)
{
for(size_t j = 0;j<1000;j++)
{
///////////////////////
// CRITICAL SECTIION //
///////////////////////
// this code currently doesn't trigger the exception
// because of the lock on the mutex. If you comment
// out the single line below then the exception *may*
// get called.
std::scoped_lock lock{m};
num++;
std::this_thread::sleep_for(std::chrono::nanoseconds(1));
num++;
if(num%2!=0)
throw std::runtime_error("bad things happened");
}
return 0;
}
};
template <typename T> struct F;
void TestUseMutexInClassMethodUsingAsync()
{
const int nthreads = 16;
int accumulator=0;
std::mutex m;
std::vector<UseMutex> vs{nthreads};
std::vector<std::future<int>> futures(nthreads);
for (auto i = 0; i < nthreads; ++i) {
futures[i]= std::async([&,i](){return vs[i].compute(m,accumulator);});
}
for(auto i = 0; i < nthreads; ++i){
futures[i].get();
}
}
int main(){
TestUseMutexInClassMethodUsingAsync();
}
You can comment / uncomment the line
std::scoped_lock lock{m};
which protects the increment of the shared variable num. The rule for this mini program is that at the line
if(num%2!=0)
throw std::runtime_error("bad things happened");
num should be a multiple of two. But as multiple threads are accessing this variable without a lock you can't guarantee this. However if you add a lock around the double increment and test then you can be sure no other thread is accessing this memory during the duration of the increment and test.
Failing
https://godbolt.org/z/sojcs1WK9
Passing
https://godbolt.org/z/sGdx3x3q3
Of course the failing one is not guaranteed to fail but I've set it up so that it has a high probability of failing.
Notes
[&,i](){return vs[i].compute(m,accumulator);};
is a lambda or inline function. The notation [&,i] means it captures everything by reference except i which it captures by value. This is important because i changes on each loop iteration and we want each future to get a unique value of i
Is it because the objects are different?
Yes.
Your code is actually perfectly thread safe, no need for mutex here. You never share any state between threads except for copying vec from TestUseMutexInClassMethodUsingAsync to compute by std::async (and copying is thread-safe) and moving computation result from compute's return value to futures[i].get()'s return value. .get() is also thread-safe: it blocks until the compute() method terminates and then returns its computation result.
It's actually nice to see that even a deliberate attempt to get a race condition failed :)
You probably have to fully redo your example to demonstrate is how simultaneous* access to a shared object breaks things. Get rid of std::async and std::future, use simple std::thread with capture-by-reference, remove sleep_for (so both threads do a lot of operations instead of one per second), significantly increase number of operations and you will get a visible race. It may look like a crash, though.
* - yes, I'm aware that "wall-clock simulateneous access" does not exist in multithreaded systems, strictly speaking. However, it helps getting a rough idea of where to look for visible race conditions for demonstration purposes.
Comments have called out the fact that just not protecting a critical section does not guarantee that the risked behavior actually occurs.
That also applies for multiple runs, because while you are not allowed to test a few times and then rely on the repeatedly observed behavior, it is likely that optimization mechanisms cause a likely enough reoccurring observation as to be perceived has reproducible.
If you intend to demonstrate the need for synchronization you need to employ synchronization to poise things to a near guaranteed misbehavior of observable lack of protection.
Allow me to only outline a sequence for that, with a few assumptions on scheduling mechanisms (this is based on a rather simple, single core, priority based scheduling environment I have encountered in an embedded environment I was using professionally), just to give an insight with a simplified example:
start a lower priority context.
optionally set up proper protection before entering the critical section
start critical section, e.g. by outputting the first half of to-be-continuous output
asynchronously trigger a higher priority context, which is doing that which can violate your critical section, e.g. outputs something which should not be in the middle of the two-part output of the critical section
(in protected case the other context is not executed, in spite of being higher priority)
(in unprotected case the other context is now executed, because of being higher priority)
end critical section, e.g. by outputting the second half of the to-be-continuous output
optionally remove the protection after leaving the critical section
(in protected case the other context is now executed, now that it is allowed)
(in unprotected case the other context was already executed)
Note:
I am using the term "critical section" with the meaning of a piece of code which is vulnerable to being interrupted/preempted/descheduled by another piece of code or another execution of the same code. Specifically for me a critical section can exist without applied protection, though that is not a good thing. I state this explicitly because I am aware of the term being used with the meaning "piece of code inside applied protection/synchronization". I disagree but I accept that the term is used differently and requires clarification in case of potential conflicts.
I wish I could have thought of a more descriptive title, but that is the case. I've got some code that I'd like to do some image processing with. I also need to get some statistical data from those processed images, and I'd like to do that on a separate thread so my main thread can keep doing image processing.
All that aside, here's my code. It shouldn't really be relevant, other than the fact that my Image class wraps an OpenCV Mat (though I'm not using OMP or anything, as far as I'm aware):
#include <thread>
#include <iostream>
#include <vector>
using namespace std;
//Data struct
struct CenterFindData{
//Some images I'd like to store
Image in, bpass, bpass_thresh, local_max, tmp;
//Some Data (Particle Data = float[8])
vector<ParticleData> data;
//My thread flag
bool goodToGo{ false };
//Constructor
CenterFindData(const Image& m);
};
vector<ParticleData> statistics(CenterFindData& CFD);
void operate(vector<CenterFindData> v_CFD);
..........................................
..........................................
..........................................
void operate(vector<CenterFindData> v_CFD){
//Thread function, gathers statistics on processed images
thread T( [&](){
int nProcessed(0);
for (auto& cfd : v_CFD){
//Chill while the images are still being processed
while (cfd.goodToGo == false){
//This works if I uncomment this print statement
/*cout << "Waiting" << endl;*/
}
cout << "Statistics gathered from " << nProcessed++ << " images" << endl;
//This returns vector<ParticleData>
cfd.data = m_Statistics(cfd);
}
});
//Run some filters on the images before statistics
int nProcessed(0);
for (auto& cfd : v_CFD){
//Preprocess images
RecenterImage(cfd.in);
m_BandPass(cfd);
m_LocalMax(cfd);
RecenterImage(cfd.bpass_thresh);
//Tell thread to do statistics, on to the next
cfd.goodToGo = true;
cout << "Ran filters on " << nProcessed++ << " images" << endl;
}
//Join thread
T.join();
}
I figure that the delay from cout is avoid some race condition I otherwise run into, but what? Because only one thread modified the bool goodToGo, while the other checks it, should that be a thread safe way of "gating" the two functions?
Sorry if anything is unclear, I'm very new to this and seem to make a lot of obvious mistakes WRT multithreaded programming.
Thanks for your help
john
When you have:
while (cfd.goodToGo == false){ }
the compiler doesn't see any reason to "reload" the value of goodToGo (it doesn't know that this value is affected by other threads!). So it reads it once, and then loops forever.
The reason printing something makes a difference is, that the compiler doesn't know what the print function actually will and won't affect, so "just in case", it reloads that value (if the compiler could "see inside" all of the printing code, it could in fact decide that goodToGo is NOT changed by the printing, and not needing to reload - but there are limits to how much time [or some proxy for time, such as "number of levels of calls" or "number of intermediate instructions"] the compiler spends on figuring these sort of thing out [and there may of course be calls to code that the compiler doesn't actually have access to the source code of, such as the system calls to write or similar].
The solution, however, is to use thread-safe mechanisms to update the goodToGo - we could just throw a volatile attribute to the variable, but that will not guarantee that, for example, another processor gets "told" that the value has updated, so could delay the detection of the updated value significantly [or even infinitely under some conditions].
Use std::atomic_bool goodToGo and the store and load functions to access the value inside. That way, you will be guaranteed that the value is updated correctly and "immediately" (as in, a few dozen to hundreds of clock-cycles later) seen by the other thread.
As a side-note, which probably should have been the actual answer: Busy-waiting for threads is a bad idea in general, you should probably look at some thread-primitives to wait for a condition_variable or similar.
For a project I am working on, I need the program to be able to receive input from the user, but while they are inputting something, the program can continue in the loop.
For example:
while (true)
{
if (userInput == true)
{
cin >> input
}
//DO SOMETHING
}
This would mean that //DO SOMETHING would happen every loop, without the user pressing enter a million times.
Before, my solution was creating my own input using kbhit() and getch() from conio.h, but that got very messy, and I don't like using conio.h for portability reasons etc. Also, it doesn't need to use cin specifically, because there is a good chance it just wouldn't work with it, so any good solution that doesn't require me making my own input with a 'not very good' library, would be much appreciated.
It could be worth looking into multi-threading for this. I'm usually hesitant to suggest it, because multithreading pulls in a host of potential problems that can end up difficult to debug, but in this case they can be isolated fairly easily. I envision something like this:
#include <atomic>
#include <chrono>
#include <iostream>
#include <thread>
int main() {
std::atomic<bool> interrupted;
int x;
int i = 0;
do {
interrupted.store(false);
// create a new thread that does stuff in the background
std::thread th([&]() {
while(!interrupted) {
// do stuff. Just as an example:
std::cout << i << std::flush;
std::this_thread::sleep_for(std::chrono::milliseconds(100));
}
});
std::cin >> x;
// when input is complete, interrupt thread and wait for it to finish
interrupted.store(true);
th.join();
// apply x, then loop to make new thread to do stuff
i = x;
} while(x != -1); // or some other exit condition
}
At first glance this looks somewhat wasteful because it keeps spawning and throwing threads away, but user input takes, in computing terms, an eternity, so the overhead should not be prohibitive. More importantly, it does have the advantage of avoiding any suggestion of data races wholesale because the only means of communication between the main (input) loop and the background thread is the atomic interruption flag, and the application of x to shared data happens when no thread is running that could race the main loop.
Disclaimer: the following seems to be working with gcc on Linux, however for some reasons it does not work with VC++ on Windows. The specifications appear to give a lot of leeway to the implementations here, and VC++ definitely takes advantage of it...
There are multiple functions available on any std::basic_istream or its underlying std::basic_streambuf.
In order to know if there is any character available for input, you may call in_avail on std::basic_streambuf:
if (std::cin.rdbuf() and std::cin.rdbuf()->in_avail() >= 0) {
}
in_avail gives you the number of characters available without blocking, it returns -1 if there is no such character. Afterward, you can use the regular "formatted" read operations such as std::cin >> input.
Otherwise, for unformatted reads, you can use readsome from std::basic_istream, which returns up to N characters available without blocking:
size_t const BufferSize = 512;
char buffer[BufferSize];
if (std::cin.readsome(buffer, BufferSize) >= 1) {
}
However it is noted that the implementation of this method is highly variable, so for a portable program it might not be that useful.
Note: as mentioned in the comment, the in_avail approach might be spotty. I confirm it can work, however you first have to use an obscure feature of C++ IO streams: std::ios_base::sync_with_stdio(false) which allows C++ streams to buffer input (and thus steal it from C's stdio buffers).
It's sad that there is no simple portable way to checking asynchronously if a key was hit. But I guess that the standard committee has carefully evaluated the pros and cons.
If you don't want to rely on third party event management libraries, and if multithreading would be overkill, one alternative could be to have your own version of kbhit(), with conditional compiling for the environments you want to support:
if your conio.h supports kbhit() just use it.
for windows, you can refer to _kbhit()
for linux and posix, you can use Matthieu's answer, or look here for Morgan Mattews's code
It's not the most academic answer, but it's pragmatic.
Maybe, you can have a try:
while (true)
{
if (userInput == true)
{
if(cin >> input){
}else{
std::cout << "Invalid input!" << std::endl;
cin.clear();
}
}
//DO SOMETHING
}
I attended one interview two days back. The interviewed guy was good in C++, but not in multithreading. When he asked me to write a code for multithreading of two threads, where one thread prints 1,3,5,.. and the other prints 2,4,6,.. . But, the output should be 1,2,3,4,5,.... So, I gave the below code(sudo code)
mutex_Lock LOCK;
int last=2;
int last_Value = 0;
void function_Thread_1()
{
while(1)
{
mutex_Lock(&LOCK);
if(last == 2)
{
cout << ++last_Value << endl;
last = 1;
}
mutex_Unlock(&LOCK);
}
}
void function_Thread_2()
{
while(1)
{
mutex_Lock(&LOCK);
if(last == 1)
{
cout << ++last_Value << endl;
last = 2;
}
mutex_Unlock(&LOCK);
}
}
After this, he said "these threads will work correctly even without those locks. Those locks will reduce the efficiency". My point was without the lock there will be a situation where one thread will check for(last == 1 or 2) at the same time the other thread will try to change the value to 2 or 1. So, My conclusion is that it will work without that lock, but that is not a correct/standard way. Now, I want to know who is correct and in which basis?
Without the lock, running the two functions concurrently would be undefined behaviour because there's a data race in the access of last and last_Value Moreover (though not causing UB) the printing would be unpredictable.
With the lock, the program becomes essentially single-threaded, and is probably slower than the naive single-threaded code. But that's just in the nature of the problem (i.e. to produce a serialized sequence of events).
I think the interviewer might have thought about using atomic variables.
Each instantiation and full specialization of the std::atomic template defines an atomic type. Objects of atomic types are the only C++ objects that are free from data races; that is, if one thread writes to an atomic object while another thread reads from it, the behavior is well-defined.
In addition, accesses to atomic objects may establish inter-thread synchronization and order non-atomic memory accesses as specified by std::memory_order.
[Source]
By this I mean the only thing you should change is remove the locks and change the lastvariable to std::atomic<int> last = 2; instead of int last = 2;
This should make it safe to access the last variable concurrently.
Out of curiosity I have edited your code a bit, and ran it on my Windows machine:
#include <iostream>
#include <atomic>
#include <thread>
#include <Windows.h>
std::atomic<int> last=2;
std::atomic<int> last_Value = 0;
std::atomic<bool> running = true;
void function_Thread_1()
{
while(running)
{
if(last == 2)
{
last_Value = last_Value + 1;
std::cout << last_Value << std::endl;
last = 1;
}
}
}
void function_Thread_2()
{
while(running)
{
if(last == 1)
{
last_Value = last_Value + 1;
std::cout << last_Value << std::endl;
last = 2;
}
}
}
int main()
{
std::thread a(function_Thread_1);
std::thread b(function_Thread_2);
while(last_Value != 6){}//we want to print 1 to 6
running = false;//inform threads we are about to stop
a.join();
b.join();//join
while(!GetAsyncKeyState('Q')){}//wait for 'Q' press
return 0;
}
and the output is always:
1
2
3
4
5
6
Ideone refuses to run this code (compilation errors)..
Edit: But here is a working linux version :) (thanks to soon)
The interviewer doesn't know what he is talking about. Without the locks you get races on both last and last_value. The compiler could for example reorder the assignment to last before the print and increment of last_value, which could lead to the other thread executing on stale data. Furthermore you could get interleaved output, meaning things like two numbers not being seperated by a linebreak.
Another thing, which could go wrong is that the compiler might decide not to reload last and (less importantly) last_value each iteration, since it can't (safely) change between those iterations anyways (since data races are illegal by the C++11 standard and aren't acknowledged in previous standards). This means that the code suggested by the interviewer actually has a good chance of creating infinite loops of doing absoulutely doing nothing.
While it is possible to make that code correct without mutices, that absolutely needs atomic operations with appropriate ordering constraints (release-semantics on the assignment to last and acquire on the load of last inside the if statement).
Of course your solution does lower efficiency due to effectivly serializing the whole execution. However since the runtime is almost completely spent inside the streamout operation, which is almost certainly internally synchronized by the use of locks, your solution doesn't lower the efficiency anymore then it already is. Waiting on the lock in your code might actually be faster then busy waiting for it, depending on the availible resources (the nonlocking version using atomics would absolutely tank when executed on a single core machine)
I am changing a single thread program into multi thread using boost:thread library. The program uses unordered_map as a hasp_map for lookups. My question is..
At one time many threads will be writing, and at another many will be reading but not both reading and writing at the same time i.e. either all the threads will be reading or all will be writing. Will that be thread safe and the container designed for this? And if it will be, will it really be concurrent and improve performance? Do I need to use some locking mechanism?
I read somewhere that the C++ Standard says the behavior will be undefined, but is that all?
UPDATE: I was also thinking about Intel concurrent_hash_map. Will that be a good option?
STL containers are designed so that you are guaranteed to be able to have:
A. Multiple threads reading at the same time
or
B. One thread writing at the same time
Having multiple threads writing is not one of the above conditions and is not allowed. Multiple threads writing will thus create a data race, which is undefined behavior.
You could use a mutex to fix this. A shared_mutex (combined with shared_locks) would be especially useful as that type of mutex allows multiple concurrent readers.
http://eel.is/c++draft/res.on.data.races#3 is the part of the standard which guarantees the ability to concurrently use const functions on different threads. http://eel.is/c++draft/container.requirements.dataraces specifies some additional non-const operations which are safe on different threads.
std::unordered_map meets the requirements of Container (ref http://en.cppreference.com/w/cpp/container/unordered_map). For container thread safety see: http://en.cppreference.com/w/cpp/container#Thread_safety.
Important points:
"Different elements in the same container can be modified concurrently by different threads"
"All const member functions can be called concurrently by different threads on the same container. In addition, the member functions begin(), end(), rbegin(), rend(), front(), back(), data(), find(), lower_bound(), upper_bound(), equal_range(), at(), and, except in associative containers, operator[], behave as const for the purposes of thread safety (that is, they can also be called concurrently by different threads on the same container)."
Will that be thread safe and the container designed for this?
No, the standard containers are not thread safe.
Do I need to use some locking mechanism?
Yes, you do. Since you're using boost, boost::mutex would be a good idea; in C++11, there's std::mutex.
I read somewhere that the C++ Standard says the behavior will be undefined, but is that all?
Indeed, the behaviour is undefined. I'm not sure what you mean by "is that all?", since undefined behaviour is the worst possible kind of behaviour, and a program that exhibits it is by definition incorrect. In particular, incorrect thread synchronisation is likely to lead to random crashes and data corruption, often in ways that are very difficult to diagnose, so you would be wise to avoid it at all costs.
UPDATE: I was also thinking about Intel concurrent_hash_map. Will that be a good option?
It sounds good, but I've never used it myself so I can't offer an opinion.
The existing answers cover the main points:
you must have a lock to read or write to the map
you could use a multiple-reader / single-writer lock to improve concurrency
Also, you should be aware that:
using an earlier-retrieved iterator, or a reference or pointer to an item in the map, counts as a read or write operation
write operations performed in other threads may invalidate pointers/references/iterators into the map, much as they would if they were done in the same thread, even if a lock is again acquired before an attempt is made to continue using them...
You can use concurrent_hash_map or employ an mutex when you access unordered_map. one of issue on using intel concurrent_hash_map is you have to include TBB, but you already use boost.thread. These two components have overlapped functionality, and hence complicate your code base.
std::unordered_map is a good fit for some multi-threaded situations.
There are also other concurrent maps from Intel TBB:
tbb:concurrent_hash_map. It supports fine-grained, per-key locking for insert/update, which is something that few other hashmaps can offer. However, the syntax is slightly more wordy. See full sample code. Recommended.
tbb:concurrent_unordered_map. It is essentially the same thing, a key/value map. However, it is much lower level, and more difficult to use. One has to supply a hasher, a equality operator, and an allocator. There is no sample code anywhere, even in the official Intel docs. Not recommended.
If you don't need all of the functionality of unordered_map, then this solution should work for you. It uses mutex to control access to the internal unordered_map. The solution supports the following methods, and adding more should be fairly easy:
getOrDefault(key, defaultValue) - returns the value associated with key, or defaultValue if no association exists. A map entry is not created when no association exists.
contains(key) - returns a boolean; true if the association exists.
put(key, value) - create or replace association.
remove(key) - remove association for key
associations() - returns a vector containing all of the currently known associations.
Sample usage:
/* SynchronizedMap
** Functional Test
** g++ -O2 -Wall -std=c++11 test.cpp -o test
*/
#include <iostream>
#include "SynchronizedMap.h"
using namespace std;
using namespace Synchronized;
int main(int argc, char **argv) {
SynchronizedMap<int, string> activeAssociations;
activeAssociations.put({101, "red"});
activeAssociations.put({102, "blue"});
activeAssociations.put({102, "green"});
activeAssociations.put({104, "purple"});
activeAssociations.put({105, "yellow"});
activeAssociations.remove(104);
cout << ".getOrDefault(102)=" << activeAssociations.getOrDefault(102, "unknown") << "\n";
cout << ".getOrDefault(112)=" << activeAssociations.getOrDefault(112, "unknown") << "\n";
if (!activeAssociations.contains(104)) {
cout << 123 << " does not exist\n";
}
if (activeAssociations.contains(101)) {
cout << 101 << " exists\n";
}
cout << "--- associations: --\n";
for (auto e: activeAssociations.associations()) {
cout << e.first << "=" << e.second << "\n";
}
}
Sample output:
.getOrDefault(102)=green
.getOrDefault(112)=unknown
123 does not exist
101 exists
--- associations: --
105=yellow
102=green
101=red
Note1: The associations() method is not intended for very large datasets as it will lock the table during the creation of the vector list.
Note2: I've purposefully not extended unordered_map in order to prevent my self from accidentally using a method from unordered_map that has not been extended and therefore might not be thread safe.
#pragma once
/*
* SynchronizedMap.h
* Wade Ryan 20200926
* c++11
*/
#include <unordered_map>
#include <mutex>
#include <vector>
#ifndef __SynchronizedMap__
#define __SynchronizedMap__
using namespace std;
namespace Synchronized {
template <typename KeyType, typename ValueType>
class SynchronizedMap {
private:
mutex sync;
unordered_map<KeyType, ValueType> usermap;
public:
ValueType getOrDefault(KeyType key, ValueType defaultValue) {
sync.lock();
ValueType rs;
auto value=usermap.find(key);
if (value == usermap.end()) {
rs = defaultValue;
} else {
rs = value->second;
}
sync.unlock();
return rs;
}
bool contains(KeyType key) {
sync.lock();
bool exists = (usermap.find(key) != usermap.end());
sync.unlock();
return exists;
}
void put(pair<KeyType, ValueType> nodePair) {
sync.lock();
if (usermap.find(nodePair.first) != usermap.end()) {
usermap.erase(nodePair.first);
}
usermap.insert(nodePair);
sync.unlock();
}
void remove(KeyType key) {
sync.lock();
if (usermap.find(key) != usermap.end()) {
usermap.erase(key);
}
sync.unlock();
}
vector<pair<KeyType, ValueType>> associations() {
sync.lock();
vector<pair<KeyType, ValueType>> elements;
for (auto it=usermap.begin(); it != usermap.end(); ++it) {
pair<KeyType, ValueType> element (it->first, it->second);
elements.push_back( element );
}
sync.unlock();
return elements;
}
};
}
#endif