Here's the situation.
I have an application which for all intents and purposes I have to treat like a black box.
I need to be able to open multiple instances of this application each with a set of files. The syntax for opening this is executable.exe file1.ext file2.ext.
If I run executable.exe x amount of times with no arguments, new instances open fine.
If I run executable.exe file1.ext followed by executable.exe file2.ext then the second call opens file 2 in the existing window rather than creating a new instance. This interferes with the rest of my solution and is the problem.
My solution wraps this application and performs various management operations on it, here's one of my wrapper classes:
public class myWrapper
{
public event EventHandler<IntPtr> SplashFinished;
public event EventHandler ProcessExited;
private const string aaTrendLocation = #"redacted";
//private const string aaTrendLocation = "notepad";
private readonly Process _process;
private readonly Logger _logger;
public myWrapper(string[] args, Logger logger =null)
{
_logger = logger;
_logger?.WriteLine("Intiialising new wrapper object...");
if (args == null || args.Length < 1) args = new[] {""};
ProcessStartInfo info = new ProcessStartInfo(aaTrendLocation,args.Aggregate((s,c)=>$"{s} {c}"));
_process = new Process{StartInfo = info};
}
public void Start()
{
_logger?.WriteLine("Starting process...");
_logger?.WriteLine($"Process: {_process.StartInfo.FileName} || Args: {_process.StartInfo.Arguments}");
_process.Start();
Task.Run(()=>MonitorSplash());
Task.Run(() => MonitorLifeTime());
}
private void MonitorLifeTime()
{
_logger?.WriteLine("Monitoring lifetime...");
while (!_process.HasExited)
{
_process.Refresh();
Thread.Sleep(50);
}
_logger?.WriteLine("Process exited!");
_logger?.WriteLine("Invoking!");
ProcessExited?.BeginInvoke(this, null, null, null);
}
private void MonitorSplash()
{
_logger?.WriteLine("Monitoring Splash...");
while (!_process.MainWindowTitle.Contains("Trend"))
{
_process.Refresh();
Thread.Sleep(500);
}
_logger?.WriteLine("Splash finished!");
_logger?.WriteLine("Invoking...");
SplashFinished?.BeginInvoke(this,_process.MainWindowHandle,null,null);
}
public void Stop()
{
_logger?.WriteLine("Killing trend...");
_process.Kill();
}
public IntPtr GetHandle()
{
_logger?.WriteLine("Fetching handle...");
_process.Refresh();
return _process.MainWindowHandle;
}
public string GetMainTitle()
{
_logger?.WriteLine("Fetching Title...");
_process.Refresh();
return _process.MainWindowTitle;
}
}
My wrapper class all works fine until I start providing file arguments and this unexpected instancing behaviour kicks in.
I can't modify the target application and nor do I have access to its source to determine whether this instancing is managed with Mutexes or through some other feature. Consequently, I need to determine if there is a way to prevent the new instance seeing the existing one. Would anyone have any suggestions?
TLDR: How do I prevent an application that is limited to a single instance determining that there is already an instance running
To clarify (following suspicious comments), my company's R&D team wrote executable.exe but I don't have time to wait for their help in this matter (I have days not months) and have permission to do whatever required to deliver the required functionality (there's a lot more to my solution than this question mentions) swiftly.
With some decompiling work I can see that the following is being used to find the existing instance.
Process[] processesByName = Process.GetProcessesByName(Process.GetCurrentProcess().ProcessName);
Is there any way to mess with this short of creating multiple copies of the application with different names? I looked into renaming the Process on the fly but apparently this isn't possible short of writing kernel exploits...
I have solved this problem in the past by creating copies of the source executable. In your case, you could:
Save the 'original.exe' in a specific location.
Each time you need to call it, create a copy of original.exe and name it 'instance_xxxx.exe', where xxxx is a unique number.
Execute your new instance exe as required, and when it completes you can delete it
You could possibly even re-use the instances by creating a pool of them
Building on Dave Lucre's answer I solved it by creating new instances of the executable bound to my wrapper class. Initially, I inherited IDisposable and removed the temporary files in the Disposer but for some reason that was causing issues where the cleanup would block the application, so now my main program performs cleanup at the end.
My constructor now looks like:
public AaTrend(string[] args, ILogger logger = null)
{
_logger = logger;
_logger?.WriteLine("Initialising new aaTrend object...");
if (args == null || args.Length < 1) args = new[] { "" };
_tempFilePath = GenerateTempFileName();
CreateTempCopy(); //Needed to bypass lazy single instance checks
HideTempFile(); //Stops users worrying
ProcessStartInfo info = new ProcessStartInfo(_tempFilePath, args.Aggregate((s, c) => $"{s} {c}"));
_process = new Process { StartInfo = info };
}
With the two new methods:
private void CreateTempCopy()
{
_logger?.WriteLine("Creating temporary file...");
_logger?.WriteLine(_tempFilePath);
File.Copy(AaTrendLocation, _tempFilePath);
}
private string GenerateTempFileName(int increment = 0)
{
string directory = Path.GetDirectoryName(AaTrendLocation); //Obtain pass components.
string fileNameWithoutExtension = Path.GetFileNameWithoutExtension(AaTrendLocation);
string extension = Path.GetExtension(AaTrendLocation);
string tempName = $"{directory}\\{fileNameWithoutExtension}-{increment}{extension}"; //Re-assemble path with increment inserted.
return File.Exists(tempName) ? GenerateTempFileName(++increment) : tempName; //If this name is already used, increment an recurse otherwise return new path.
}
Then in my main program:
private static void DeleteTempFiles()
{
string dir = Path.GetDirectoryName(AaTrend.AaTrendLocation);
foreach (string file in Directory.GetFiles(dir, "aaTrend-*.exe", SearchOption.TopDirectoryOnly))
{
File.Delete(file);
}
}
As a side-note, this approach will only work for applications with (lazy) methods of determining instancing that rely on Process.GetProcessByName(); it won't work if a Mutex is used or if the executable name is explicitly set in the manifests.
I have some code that loads up and AppDomain(call it domain) calling an object function within the domain. The purpose is to get a list of items from a usb device using the device API to retrieve the information. The API requires a callback to return the information.
var AppDomain.CreateDomain(
$"BiometricsDomain{System.IO.Path.GetRandomFileName()}");
var proxy = domain.CreateInstanceAndUnwrap(proxy.Assembly.FullName, proxy.FullName
?? throw new InvalidOperationException()) as Proxy;
var ids = obj.GetIdentifications();
The proxy code loaded into the domain is as follows
public class Proxy : MarshalByRefObject
{
public List<String> GetIdentifications()
{
var control = new R100DeviceControl();
control.OnUserDB += Control_OnUserDB;
control.Open();
int nResult = control.DownloadUserDB(out int count);
// need to be able to return the list here but obviously that is not
// going to work.
}
private void Control_OnUserDB(List<String> result)
{
// Get the list of string from here
}
}
Is there a way to be able to wait on the device and return the information as needed when the callback is called? Since the GetIdentifications() has already returned I don't know how to get the
You can consider wrapping the Event-Based Asynchronous Pattern (EAP) operations as one task by using a TaskCompletionSource<TResult> so that the event can be awaited.
public class Proxy : MarshalByRefObject {
public List<String> GetIdentifications() {
var task = GetIdentificationsAsync();
return task.Result;
}
private Task<List<String>> GetIdentificationsAsync() {
var tcs = new TaskCompletionSource<List<string>>();
try {
var control = new R100DeviceControl();
Action<List<string>> handler = null;
handler = result => {
// Once event raised then set the
// Result property on the underlying Task.
control.OnUserDB -= handler;//optional to unsubscribe from event
tcs.TrySetResult(result);
};
control.OnUserDB += handler;
control.Open();
int count = 0;
//call async event
int nResult = control.DownloadUserDB(out count);
} catch (Exception ex) {
//Bubble the error up to be handled by calling client
tcs.TrySetException(ex);
}
// Return the underlying Task. The client code
// waits on the Result property, and handles exceptions
// in the try-catch block there.
return tcs.Task;
}
}
You can also improve on it by adding the ability to cancel using a CancellationToken for longer than expected callbacks.
With that the proxy can then be awaited
List<string> ids = proxy.GetIdentifications();
Reference How to: Wrap EAP Patterns in a Task
NOTE: Though there may be more elegant solutions to the problem of asynchronous processing, the fact that this occurs in a child AppDomain warrants child AppDomain best practices. (see links below)
i.e.
do not allow code meant for a child AppDomain to be executed in the parent domain
do not allow complex types to bubble to the parent AppDomain
do not allow exceptions to cross AppDomain boundaries in the form of custom exception types
OP:
I am using it for fault tolerance
First I would probably add a Open or similar method to give time for the data to materialise.
var proxy = domain.CreateInstanceAndUnwrap(proxy.Assembly.FullName, proxy.FullName
?? throw new InvalidOperationException()) as Proxy;
proxy.Open(); // <------ new method here
.
. some time later
.
var ids = obj.GetIdentifications();
Then in your proxy make these changes to allow for data processing to occur in the background so that by the time you call GetNotifications data may be ready.
public class Proxy : MarshalByRefObject
{
ConcurrentBag<string> _results = new ConcurrentBag<string>();
public void Open()
{
var control = new R100DeviceControl();
control.OnUserDB += Control_OnUserDB;
control.Open();
// you may need to store nResult and count in a field?
nResult = control.DownloadUserDB(out int count);
}
public List<String> GetIdentifications()
{
var copy = new List<string>();
while (_results.TryTake(out var x))
{
copy.Add(x);
}
return copy;
}
private void Control_OnUserDB(List<String> result)
{
// Get the list of string from here
_results.Add (result);
}
}
Now you could probably improve upon GetNotifications to accept a timeout in the event either GetNotifications is called before data is ready or if you call it multiply but before subsequent data to arrive.
More
How to: Run Partially Trusted Code in a Sandbox
Not sure why you just don't maintain a little state and then wait for the results in the call:
public class Proxy : MarshalByRefObject
{
bool runningCommand;
int lastResult;
R100DeviceControl DeviceControl { get{ if(deviceControl == null){ deviceControl = new R100DeviceControl(); deviceControl.OnUserDB += Control_OnUserDB; } return deviceControl; } }
public List<String> GetIdentifications()
{
if(runningCommand) return null;
DeviceControl.Open();
runningCommand = true;
lastResult = control.DownloadUserDB(out int count);
}
private void Control_OnUserDB(List<String> result)
{
runningCommand = false;
// Get the list of string from here
}
}
Once you have a pattern like this you can easily switch between async and otherwise whereas before it will look a little harder to understand because you integrated the async logic, this way you can implement the sync method and then make an async wrapper if you desire.
I'm writing a Windows Service that will execute different data import logic, from different data source to eventually write it to a single target, a MS CRM instance. Right now, the only thing I think will be problematic, is the writing to CRM part. The concurent reading of data from different (sometimes same) data source shouldn't really be an issue (I may be wrong on this...) So I came up with a way to make sure there are no concurent writes (create or updates) to CRM.
Here's the general design for the moment:
What happens when the service starts:
Timers = new List<System.Timers.Timer>();
CrmTransactionQueue.Lock = new object { }; //Static class. The object for locking purposes...
System.Threading.Thread.Sleep(20000); //for debugging purpose so I can attach to process before everything kicks in...
//retrieve all types that are extending BaseSyncStrategy..
var strategyTypes = Assembly.GetExecutingAssembly().GetTypes().Where(x => x.BaseType == typeof(BaseSyncStrategy));
foreach (Type strategyType in strategyTypes)
{
//create a instance of that type....
var strategy = (BaseSyncStrategy)Activator.CreateInstance(strategyType);
//create a timer for each of these, they will have different intervals...
System.Timers.Timer t = new System.Timers.Timer
{
Interval = strategy.Interval * 1000,
AutoReset = false,
Enabled = true
};
Timers.Add(t);
t.Elapsed += (sender, e) => TimerElapsed(sender, e, strategy);
t.Start();
}
What happens when the timers' interval are expired:
private void TimerElapsed(object sender, ElapsedEventArgs e, BaseSyncStrategy strategy)
{
//get timer back
var timer = (Timer)sender;
try
{
strategy.Execute();
}
catch (Exception ex)
{
Logger.WriteEntry(EventLogEntryType.Error, $"Error executing strategy {strategy.GetType().Name}: ", ex);
}
timer.Start();
}
And within all the Execute methods of objects extending BaseSyncStrategy, each time I want to update or create something in the target CRM instance, I do this:
XrmServiceContext XrmCtx = new XrmServiceContext();
//....
//code that fetches data from foreign sources and creates CRM entities...
//....
Action<XrmServiceContext> action = (XrmServiceContext ctx) =>
{
//write those created/updated objects
//ctx lets me query entities and write back to CRM...
};
CrmTransactionQueue.Execute(action, XrmCtx);
And the simple code to make sure (I think) no concurent writes to CRM happen:
public static class CrmTransactionQueue
{
public static object Lock { get; set; }
public static void Execute(Action<XrmServiceContext> transaction, XrmServiceContext Ctx)
{
lock (Lock)
{
transaction.Invoke(Ctx);
}
}
}
Is this sound design or there's a better way to do this ?
I assume this code has concurrency issues:
const string CacheKey = "CacheKey";
static string GetCachedData()
{
string expensiveString =null;
if (MemoryCache.Default.Contains(CacheKey))
{
expensiveString = MemoryCache.Default[CacheKey] as string;
}
else
{
CacheItemPolicy cip = new CacheItemPolicy()
{
AbsoluteExpiration = new DateTimeOffset(DateTime.Now.AddMinutes(20))
};
expensiveString = SomeHeavyAndExpensiveCalculation();
MemoryCache.Default.Set(CacheKey, expensiveString, cip);
}
return expensiveString;
}
The reason for the concurrency issue is that multiple threads can get a null key and then attempt to insert data into cache.
What would be the shortest and cleanest way to make this code concurrency proof? I like to follow a good pattern across my cache related code. A link to an online article would be a great help.
UPDATE:
I came up with this code based on #Scott Chamberlain's answer. Can anyone find any performance or concurrency issue with this?
If this works, it would save many line of code and errors.
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Runtime.Caching;
namespace CachePoc
{
class Program
{
static object everoneUseThisLockObject4CacheXYZ = new object();
const string CacheXYZ = "CacheXYZ";
static object everoneUseThisLockObject4CacheABC = new object();
const string CacheABC = "CacheABC";
static void Main(string[] args)
{
string xyzData = MemoryCacheHelper.GetCachedData<string>(CacheXYZ, everoneUseThisLockObject4CacheXYZ, 20, SomeHeavyAndExpensiveXYZCalculation);
string abcData = MemoryCacheHelper.GetCachedData<string>(CacheABC, everoneUseThisLockObject4CacheXYZ, 20, SomeHeavyAndExpensiveXYZCalculation);
}
private static string SomeHeavyAndExpensiveXYZCalculation() {return "Expensive";}
private static string SomeHeavyAndExpensiveABCCalculation() {return "Expensive";}
public static class MemoryCacheHelper
{
public static T GetCachedData<T>(string cacheKey, object cacheLock, int cacheTimePolicyMinutes, Func<T> GetData)
where T : class
{
//Returns null if the string does not exist, prevents a race condition where the cache invalidates between the contains check and the retreival.
T cachedData = MemoryCache.Default.Get(cacheKey, null) as T;
if (cachedData != null)
{
return cachedData;
}
lock (cacheLock)
{
//Check to see if anyone wrote to the cache while we where waiting our turn to write the new value.
cachedData = MemoryCache.Default.Get(cacheKey, null) as T;
if (cachedData != null)
{
return cachedData;
}
//The value still did not exist so we now write it in to the cache.
CacheItemPolicy cip = new CacheItemPolicy()
{
AbsoluteExpiration = new DateTimeOffset(DateTime.Now.AddMinutes(cacheTimePolicyMinutes))
};
cachedData = GetData();
MemoryCache.Default.Set(cacheKey, cachedData, cip);
return cachedData;
}
}
}
}
}
This is my 2nd iteration of the code. Because MemoryCache is thread safe you don't need to lock on the initial read, you can just read and if the cache returns null then do the lock check to see if you need to create the string. It greatly simplifies the code.
const string CacheKey = "CacheKey";
static readonly object cacheLock = new object();
private static string GetCachedData()
{
//Returns null if the string does not exist, prevents a race condition where the cache invalidates between the contains check and the retreival.
var cachedString = MemoryCache.Default.Get(CacheKey, null) as string;
if (cachedString != null)
{
return cachedString;
}
lock (cacheLock)
{
//Check to see if anyone wrote to the cache while we where waiting our turn to write the new value.
cachedString = MemoryCache.Default.Get(CacheKey, null) as string;
if (cachedString != null)
{
return cachedString;
}
//The value still did not exist so we now write it in to the cache.
var expensiveString = SomeHeavyAndExpensiveCalculation();
CacheItemPolicy cip = new CacheItemPolicy()
{
AbsoluteExpiration = new DateTimeOffset(DateTime.Now.AddMinutes(20))
};
MemoryCache.Default.Set(CacheKey, expensiveString, cip);
return expensiveString;
}
}
EDIT: The below code is unnecessary but I wanted to leave it to show the original method. It may be useful to future visitors who are using a different collection that has thread safe reads but non-thread safe writes (almost all of classes under the System.Collections namespace is like that).
Here is how I would do it using ReaderWriterLockSlim to protect access. You need to do a kind of "Double Checked Locking" to see if anyone else created the cached item while we where waiting to to take the lock.
const string CacheKey = "CacheKey";
static readonly ReaderWriterLockSlim cacheLock = new ReaderWriterLockSlim();
static string GetCachedData()
{
//First we do a read lock to see if it already exists, this allows multiple readers at the same time.
cacheLock.EnterReadLock();
try
{
//Returns null if the string does not exist, prevents a race condition where the cache invalidates between the contains check and the retreival.
var cachedString = MemoryCache.Default.Get(CacheKey, null) as string;
if (cachedString != null)
{
return cachedString;
}
}
finally
{
cacheLock.ExitReadLock();
}
//Only one UpgradeableReadLock can exist at one time, but it can co-exist with many ReadLocks
cacheLock.EnterUpgradeableReadLock();
try
{
//We need to check again to see if the string was created while we where waiting to enter the EnterUpgradeableReadLock
var cachedString = MemoryCache.Default.Get(CacheKey, null) as string;
if (cachedString != null)
{
return cachedString;
}
//The entry still does not exist so we need to create it and enter the write lock
var expensiveString = SomeHeavyAndExpensiveCalculation();
cacheLock.EnterWriteLock(); //This will block till all the Readers flush.
try
{
CacheItemPolicy cip = new CacheItemPolicy()
{
AbsoluteExpiration = new DateTimeOffset(DateTime.Now.AddMinutes(20))
};
MemoryCache.Default.Set(CacheKey, expensiveString, cip);
return expensiveString;
}
finally
{
cacheLock.ExitWriteLock();
}
}
finally
{
cacheLock.ExitUpgradeableReadLock();
}
}
There is an open source library [disclaimer: that I wrote]: LazyCache that IMO covers your requirement with two lines of code:
IAppCache cache = new CachingService();
var cachedResults = cache.GetOrAdd("CacheKey",
() => SomeHeavyAndExpensiveCalculation());
It has built in locking by default so the cacheable method will only execute once per cache miss, and it uses a lambda so you can do "get or add" in one go. It defaults to 20 minutes sliding expiration.
There's even a NuGet package ;)
I've solved this issue by making use of the AddOrGetExisting method on the MemoryCache and the use of Lazy initialization.
Essentially, my code looks something like this:
static string GetCachedData(string key, DateTimeOffset offset)
{
Lazy<String> lazyObject = new Lazy<String>(() => SomeHeavyAndExpensiveCalculationThatReturnsAString());
var returnedLazyObject = MemoryCache.Default.AddOrGetExisting(key, lazyObject, offset);
if (returnedLazyObject == null)
return lazyObject.Value;
return ((Lazy<String>) returnedLazyObject).Value;
}
Worst case scenario here is that you create the same Lazy object twice. But that is pretty trivial. The use of AddOrGetExisting guarantees that you'll only ever get one instance of the Lazy object, and so you're also guaranteed to only call the expensive initialization method once.
I assume this code has concurrency issues:
Actually, it's quite possibly fine, though with a possible improvement.
Now, in general the pattern where we have multiple threads setting a shared value on first use, to not lock on the value being obtained and set can be:
Disastrous - other code will assume only one instance exists.
Disastrous - the code that obtains the instance is not can only tolerate one (or perhaps a certain small number) concurrent operations.
Disastrous - the means of storage is not thread-safe (e.g. have two threads adding to a dictionary and you can get all sorts of nasty errors).
Sub-optimal - the overall performance is worse than if locking had ensured only one thread did the work of obtaining the value.
Optimal - the cost of having multiple threads do redundant work is less than the cost of preventing it, especially since that can only happen during a relatively brief period.
However, considering here that MemoryCache may evict entries then:
If it's disastrous to have more than one instance then MemoryCache is the wrong approach.
If you must prevent simultaneous creation, you should do so at the point of creation.
MemoryCache is thread-safe in terms of access to that object, so that is not a concern here.
Both of these possibilities have to be thought about of course, though the only time having two instances of the same string existing can be a problem is if you're doing very particular optimisations that don't apply here*.
So, we're left with the possibilities:
It is cheaper to avoid the cost of duplicate calls to SomeHeavyAndExpensiveCalculation().
It is cheaper not to avoid the cost of duplicate calls to SomeHeavyAndExpensiveCalculation().
And working that out can be difficult (indeed, the sort of thing where it's worth profiling rather than assuming you can work it out). It's worth considering here though that most obvious ways of locking on insert will prevent all additions to the cache, including those that are unrelated.
This means that if we had 50 threads trying to set 50 different values, then we'll have to make all 50 threads wait on each other, even though they weren't even going to do the same calculation.
As such, you're probably better off with the code you have, than with code that avoids the race-condition, and if the race-condition is a problem, you quite likely either need to handle that somewhere else, or need a different caching strategy than one that expels old entries†.
The one thing I would change is I'd replace the call to Set() with one to AddOrGetExisting(). From the above it should be clear that it probably isn't necessary, but it would allow the newly obtained item to be collected, reducing overall memory use and allowing a higher ratio of low generation to high generation collections.
So yeah, you could use double-locking to prevent concurrency, but either the concurrency isn't actually a problem, or your storing the values in the wrong way, or double-locking on the store would not be the best way to solve it.
*If you know only one each of a set of strings exists, you can optimise equality comparisons, which is about the only time having two copies of a string can be incorrect rather than just sub-optimal, but you'd want to be doing very different types of caching for that to make sense. E.g. the sort XmlReader does internally.
†Quite likely either one that stores indefinitely, or one that makes use of weak references so it will only expel entries if there are no existing uses.
Somewhat dated question, but maybe still useful: you may take a look at FusionCache ⚡🦥, which I recently released.
The feature you are looking for is described here, and you can use it like this:
const string CacheKey = "CacheKey";
static string GetCachedData()
{
return fusionCache.GetOrSet(
CacheKey,
_ => SomeHeavyAndExpensiveCalculation(),
TimeSpan.FromMinutes(20)
);
}
You may also find some of the other features interesting like fail-safe, advanced timeouts with background factory completion and support for an optional, distributed 2nd level cache.
If you will give it a chance please let me know what you think.
/shameless-plug
It is difficult to choose which one is better; lock or ReaderWriterLockSlim. You need real world statistics of read and write numbers and ratios etc.
But if you believe using "lock" is the correct way. Then here is a different solution for different needs. I also include the Allan Xu's solution in the code. Because both can be needed for different needs.
Here are the requirements, driving me to this solution:
You don't want to or cannot supply the 'GetData' function for some reason. Perhaps the 'GetData' function is located in some other class with a heavy constructor and you do not want to even create an instance till ensuring it is unescapable.
You need to access the same cached data from different locations/tiers of the application. And those different locations don't have access to same locker object.
You don't have a constant cache key. For example; need of caching some data with the sessionId cache key.
Code:
using System;
using System.Runtime.Caching;
using System.Collections.Concurrent;
using System.Collections.Generic;
namespace CachePoc
{
class Program
{
static object everoneUseThisLockObject4CacheXYZ = new object();
const string CacheXYZ = "CacheXYZ";
static object everoneUseThisLockObject4CacheABC = new object();
const string CacheABC = "CacheABC";
static void Main(string[] args)
{
//Allan Xu's usage
string xyzData = MemoryCacheHelper.GetCachedDataOrAdd<string>(CacheXYZ, everoneUseThisLockObject4CacheXYZ, 20, SomeHeavyAndExpensiveXYZCalculation);
string abcData = MemoryCacheHelper.GetCachedDataOrAdd<string>(CacheABC, everoneUseThisLockObject4CacheXYZ, 20, SomeHeavyAndExpensiveXYZCalculation);
//My usage
string sessionId = System.Web.HttpContext.Current.Session["CurrentUser.SessionId"].ToString();
string yvz = MemoryCacheHelper.GetCachedData<string>(sessionId);
if (string.IsNullOrWhiteSpace(yvz))
{
object locker = MemoryCacheHelper.GetLocker(sessionId);
lock (locker)
{
yvz = MemoryCacheHelper.GetCachedData<string>(sessionId);
if (string.IsNullOrWhiteSpace(yvz))
{
DatabaseRepositoryWithHeavyConstructorOverHead dbRepo = new DatabaseRepositoryWithHeavyConstructorOverHead();
yvz = dbRepo.GetDataExpensiveDataForSession(sessionId);
MemoryCacheHelper.AddDataToCache(sessionId, yvz, 5);
}
}
}
}
private static string SomeHeavyAndExpensiveXYZCalculation() { return "Expensive"; }
private static string SomeHeavyAndExpensiveABCCalculation() { return "Expensive"; }
public static class MemoryCacheHelper
{
//Allan Xu's solution
public static T GetCachedDataOrAdd<T>(string cacheKey, object cacheLock, int minutesToExpire, Func<T> GetData) where T : class
{
//Returns null if the string does not exist, prevents a race condition where the cache invalidates between the contains check and the retreival.
T cachedData = MemoryCache.Default.Get(cacheKey, null) as T;
if (cachedData != null)
return cachedData;
lock (cacheLock)
{
//Check to see if anyone wrote to the cache while we where waiting our turn to write the new value.
cachedData = MemoryCache.Default.Get(cacheKey, null) as T;
if (cachedData != null)
return cachedData;
cachedData = GetData();
MemoryCache.Default.Set(cacheKey, cachedData, DateTime.Now.AddMinutes(minutesToExpire));
return cachedData;
}
}
#region "My Solution"
readonly static ConcurrentDictionary<string, object> Lockers = new ConcurrentDictionary<string, object>();
public static object GetLocker(string cacheKey)
{
CleanupLockers();
return Lockers.GetOrAdd(cacheKey, item => (cacheKey, new object()));
}
public static T GetCachedData<T>(string cacheKey) where T : class
{
CleanupLockers();
T cachedData = MemoryCache.Default.Get(cacheKey) as T;
return cachedData;
}
public static void AddDataToCache(string cacheKey, object value, int cacheTimePolicyMinutes)
{
CleanupLockers();
MemoryCache.Default.Add(cacheKey, value, DateTimeOffset.Now.AddMinutes(cacheTimePolicyMinutes));
}
static DateTimeOffset lastCleanUpTime = DateTimeOffset.MinValue;
static void CleanupLockers()
{
if (DateTimeOffset.Now.Subtract(lastCleanUpTime).TotalMinutes > 1)
{
lock (Lockers)//maybe a better locker is needed?
{
try//bypass exceptions
{
List<string> lockersToRemove = new List<string>();
foreach (var locker in Lockers)
{
if (!MemoryCache.Default.Contains(locker.Key))
lockersToRemove.Add(locker.Key);
}
object dummy;
foreach (string lockerKey in lockersToRemove)
Lockers.TryRemove(lockerKey, out dummy);
lastCleanUpTime = DateTimeOffset.Now;
}
catch (Exception)
{ }
}
}
}
#endregion
}
}
class DatabaseRepositoryWithHeavyConstructorOverHead
{
internal string GetDataExpensiveDataForSession(string sessionId)
{
return "Expensive data from database";
}
}
}
To avoid the global lock, you can use SingletonCache to implement one lock per key, without exploding memory usage (the lock objects are removed when no longer referenced, and acquire/release is thread safe guaranteeing that only 1 instance is ever in use via compare and swap).
Using it looks like this:
SingletonCache<string, object> keyLocks = new SingletonCache<string, object>();
const string CacheKey = "CacheKey";
static string GetCachedData()
{
string expensiveString =null;
if (MemoryCache.Default.Contains(CacheKey))
{
return MemoryCache.Default[CacheKey] as string;
}
// double checked lock
using (var lifetime = keyLocks.Acquire(url))
{
lock (lifetime.Value)
{
if (MemoryCache.Default.Contains(CacheKey))
{
return MemoryCache.Default[CacheKey] as string;
}
cacheItemPolicy cip = new CacheItemPolicy()
{
AbsoluteExpiration = new DateTimeOffset(DateTime.Now.AddMinutes(20))
};
expensiveString = SomeHeavyAndExpensiveCalculation();
MemoryCache.Default.Set(CacheKey, expensiveString, cip);
return expensiveString;
}
}
}
Code is here on GitHub: https://github.com/bitfaster/BitFaster.Caching
Install-Package BitFaster.Caching
There is also an LRU implementation that is lighter weight than MemoryCache, and has several advantages - faster concurrent reads and writes, bounded size, no background thread, internal perf counters etc. (disclaimer, I wrote it).
Console example of MemoryCache, "How to save/get simple class objects"
Output after launching and pressing Any key except Esc :
Saving to cache!
Getting from cache!
Some1
Some2
class Some
{
public String text { get; set; }
public Some(String text)
{
this.text = text;
}
public override string ToString()
{
return text;
}
}
public static MemoryCache cache = new MemoryCache("cache");
public static string cache_name = "mycache";
static void Main(string[] args)
{
Some some1 = new Some("some1");
Some some2 = new Some("some2");
List<Some> list = new List<Some>();
list.Add(some1);
list.Add(some2);
do {
if (cache.Contains(cache_name))
{
Console.WriteLine("Getting from cache!");
List<Some> list_c = cache.Get(cache_name) as List<Some>;
foreach (Some s in list_c) Console.WriteLine(s);
}
else
{
Console.WriteLine("Saving to cache!");
cache.Set(cache_name, list, DateTime.Now.AddMinutes(10));
}
} while (Console.ReadKey(true).Key != ConsoleKey.Escape);
}
public interface ILazyCacheProvider : IAppCache
{
/// <summary>
/// Get data loaded - after allways throw cached result (even when data is older then needed) but very fast!
/// </summary>
/// <param name="key"></param>
/// <param name="getData"></param>
/// <param name="slidingExpiration"></param>
/// <typeparam name="T"></typeparam>
/// <returns></returns>
T GetOrAddPermanent<T>(string key, Func<T> getData, TimeSpan slidingExpiration);
}
/// <summary>
/// Initialize LazyCache in runtime
/// </summary>
public class LazzyCacheProvider: CachingService, ILazyCacheProvider
{
private readonly Logger _logger = LogManager.GetLogger("MemCashe");
private readonly Hashtable _hash = new Hashtable();
private readonly List<string> _reloader = new List<string>();
private readonly ConcurrentDictionary<string, DateTime> _lastLoad = new ConcurrentDictionary<string, DateTime>();
T ILazyCacheProvider.GetOrAddPermanent<T>(string dataKey, Func<T> getData, TimeSpan slidingExpiration)
{
var currentPrincipal = Thread.CurrentPrincipal;
if (!ObjectCache.Contains(dataKey) && !_hash.Contains(dataKey))
{
_hash[dataKey] = null;
_logger.Debug($"{dataKey} - first start");
_lastLoad[dataKey] = DateTime.Now;
_hash[dataKey] = ((object)GetOrAdd(dataKey, getData, slidingExpiration)).CloneObject();
_lastLoad[dataKey] = DateTime.Now;
_logger.Debug($"{dataKey} - first");
}
else
{
if ((!ObjectCache.Contains(dataKey) || _lastLoad[dataKey].AddMinutes(slidingExpiration.Minutes) < DateTime.Now) && _hash[dataKey] != null)
Task.Run(() =>
{
if (_reloader.Contains(dataKey)) return;
lock (_reloader)
{
if (ObjectCache.Contains(dataKey))
{
if(_lastLoad[dataKey].AddMinutes(slidingExpiration.Minutes) > DateTime.Now)
return;
_lastLoad[dataKey] = DateTime.Now;
Remove(dataKey);
}
_reloader.Add(dataKey);
Thread.CurrentPrincipal = currentPrincipal;
_logger.Debug($"{dataKey} - reload start");
_hash[dataKey] = ((object)GetOrAdd(dataKey, getData, slidingExpiration)).CloneObject();
_logger.Debug($"{dataKey} - reload");
_reloader.Remove(dataKey);
}
});
}
if (_hash[dataKey] != null) return (T) (_hash[dataKey]);
_logger.Debug($"{dataKey} - dummy start");
var data = GetOrAdd(dataKey, getData, slidingExpiration);
_logger.Debug($"{dataKey} - dummy");
return (T)((object)data).CloneObject();
}
}
Its a bit late, however...
Full implementation:
[HttpGet]
public async Task<HttpResponseMessage> GetPageFromUriOrBody(RequestQuery requestQuery)
{
log(nameof(GetPageFromUriOrBody), nameof(requestQuery));
var responseResult = await _requestQueryCache.GetOrCreate(
nameof(GetPageFromUriOrBody)
, requestQuery
, (x) => getPageContent(x).Result);
return Request.CreateResponse(System.Net.HttpStatusCode.Accepted, responseResult);
}
static MemoryCacheWithPolicy<RequestQuery, string> _requestQueryCache = new MemoryCacheWithPolicy<RequestQuery, string>();
Here is getPageContent signature:
async Task<string> getPageContent(RequestQuery requestQuery);
And here is the MemoryCacheWithPolicy implementation:
public class MemoryCacheWithPolicy<TParameter, TResult>
{
static ILogger _nlogger = new AppLogger().Logger;
private MemoryCache _cache = new MemoryCache(new MemoryCacheOptions()
{
//Size limit amount: this is actually a memory size limit value!
SizeLimit = 1024
});
/// <summary>
/// Gets or creates a new memory cache record for a main data
/// along with parameter data that is assocciated with main main.
/// </summary>
/// <param name="key">Main data cache memory key.</param>
/// <param name="param">Parameter model that assocciated to main model (request result).</param>
/// <param name="createCacheData">A delegate to create a new main data to cache.</param>
/// <returns></returns>
public async Task<TResult> GetOrCreate(object key, TParameter param, Func<TParameter, TResult> createCacheData)
{
// this key is used for param cache memory.
var paramKey = key + nameof(param);
if (!_cache.TryGetValue(key, out TResult cacheEntry))
{
// key is not in the cache, create data through the delegate.
cacheEntry = createCacheData(param);
createMemoryCache(key, cacheEntry, paramKey, param);
_nlogger.Warn(" cache is created.");
}
else
{
// data is chached so far..., check if param model is same (or changed)?
if(!_cache.TryGetValue(paramKey, out TParameter cacheParam))
{
//exception: this case should not happened!
}
if (!cacheParam.Equals(param))
{
// request param is changed, create data through the delegate.
cacheEntry = createCacheData(param);
createMemoryCache(key, cacheEntry, paramKey, param);
_nlogger.Warn(" cache is re-created (param model has been changed).");
}
else
{
_nlogger.Trace(" cache is used.");
}
}
return await Task.FromResult<TResult>(cacheEntry);
}
MemoryCacheEntryOptions createMemoryCacheEntryOptions(TimeSpan slidingOffset, TimeSpan relativeOffset)
{
// Cache data within [slidingOffset] seconds,
// request new result after [relativeOffset] seconds.
return new MemoryCacheEntryOptions()
// Size amount: this is actually an entry count per
// key limit value! not an actual memory size value!
.SetSize(1)
// Priority on removing when reaching size limit (memory pressure)
.SetPriority(CacheItemPriority.High)
// Keep in cache for this amount of time, reset it if accessed.
.SetSlidingExpiration(slidingOffset)
// Remove from cache after this time, regardless of sliding expiration
.SetAbsoluteExpiration(relativeOffset);
//
}
void createMemoryCache(object key, TResult cacheEntry, object paramKey, TParameter param)
{
// Cache data within 2 seconds,
// request new result after 5 seconds.
var cacheEntryOptions = createMemoryCacheEntryOptions(
TimeSpan.FromSeconds(2)
, TimeSpan.FromSeconds(5));
// Save data in cache.
_cache.Set(key, cacheEntry, cacheEntryOptions);
// Save param in cache.
_cache.Set(paramKey, param, cacheEntryOptions);
}
void checkCacheEntry<T>(object key, string name)
{
_cache.TryGetValue(key, out T value);
_nlogger.Fatal("Key: {0}, Name: {1}, Value: {2}", key, name, value);
}
}
nlogger is just nLog object to trace MemoryCacheWithPolicy behavior.
I re-create the memory cache if request object (RequestQuery requestQuery) is changed through the delegate (Func<TParameter, TResult> createCacheData) or re-create when sliding or absolute time reached their limit. Note that everything is async too ;)
I need to synchronize a sequence of operations that contains an asynchronous part.
The method looks into an image cache and returns the image if it's there (invokes a callback in reality). Otherwise it has to download it from the server. The download operation is asynchronous and fires an event on completion.
This is the (simplified) code.
private Dictionary<string, Bitmap> Cache;
public void GetImage(string fileName, Action<Bitmap> onGetImage)
{
if (Cache.ContainsKey(fileName))
{
onGetImage(Cache[fileName]);
}
else
{
var server = new Server();
server.ImageDownloaded += server_ImageDownloaded;
server.DownloadImageAsync(fileName, onGetImage); // last arg is just passed to the handler
}
}
private void server_ImageDownloaded(object sender, ImageDownloadedEventArgs e)
{
Cache.Add(e.Bitmap, e.Name);
var onGetImage = (Action<Bitmap>)e.UserState;
onGetImage(e.Bitmap);
}
The problem: if two threads call GetImage almost at the same time, they will both call the server and try to add the same image to the cache. What I should do is create lock at the beginning of GetImage and release it at the end of the server_ImageDownloaded handler.
Obviously this is not doable with the lock construct and it would not make sense, because it would be difficult to ensure that the lock is realeased in any case.
Now what I thought I could do is use a lambda instead of the event handler. This way I can put a lock around the whole section:
I have to lock the Cache dictionary at the beginning of the DownloadImage method and release it only at the end of the ImageDownloaded event handler.
private Dictionary<string, Bitmap> Cache;
public void GetImage(string fileName, Action<Bitmap> onGetImage)
{
lock(Cache)
{
if (Cache.ContainsKey(fileName))
{
onGetImage(Cache[fileName]);
}
else
{
var server = new Server();
server.ImageDownloaded += (s, e) =>
{
Cache.Add(e.Bitmap, e.Name);
onGetImage(e.Bitmap);
}
server.DownloadImageAsync(fileName, onGetImage); // last arg is just passed to the handler
}
}
}
Is this safe? Or the lock is immediately released after execution of GetImage, leaving the lambda expression unlocked?
Is there a better approach to solve this problem?
SOLUTION
In the end the solution was a bit of a mix of all the answers and comments, unfortunately I cannot mark-as-answer all of them. So here is my final code (removed some null checks/error cases/etc. for clarity).
private readonly object ImageCacheLock = new object();
private Dictionary<Guid, BitmapImage> ImageCache { get; set; }
private Dictionary<Guid, List<Action<BitmapImage>>> PendingHandlers { get; set; }
public void GetImage(Guid imageId, Action<BitmapImage> onDownloadCompleted)
{
lock (ImageCacheLock)
{
if (ImageCache.ContainsKey(imageId))
{
// The image is already cached, we can just grab it and invoke our callback.
var cachedImage = ImageCache[imageId];
onDownloadCompleted(cachedImage);
}
else if (PendingHandlers.ContainsKey(imageId))
{
// Someone already started a download for this image: we just add our callback to the queue.
PendingHandlers[imageId].Add(onDownloadCompleted);
}
else
{
// The image is not cached and nobody is downloading it: we add our callback and start the download.
PendingHandlers.Add(imageId, new List<Action<BitmapImage>>() { onDownloadCompleted });
var server = new Server();
server.DownloadImageCompleted += DownloadCompleted;
server.DownloadImageAsync(imageId);
}
}
}
private void DownloadCompleted(object sender, ImageDownloadCompletedEventArgs e)
{
List<Action<BitmapImage>> handlersToExecute = null;
BitmapImage downloadedImage = null;
lock (ImageCacheLock)
{
if (e.Error != null)
{
// ...
}
else
{
// ...
ImageCache.Add(e.imageId, e.bitmap);
downloadedImage = e.bitmap;
}
// Gets a reference to the callbacks that are waiting for this image and removes them from the waiting queue.
handlersToExecute = PendingHandlers[imageId];
PendingHandlers.Remove(imageId);
}
// If the download was successful, executes all the callbacks that were waiting for this image.
if (downloadedImage != null)
{
foreach (var handler in handlersToExecute)
handler(downloadedImage);
}
}
The lambda expression is converted into a delegate within a lock, but the body of the lambda expression will not automatically acquire the lock for the Cache monitor when the delegate is executed. So you may want:
server.ImageDownloaded += (s, e) =>
{
lock (Cache)
{
Cache.Add(e.Bitmap, e.Name);
}
onGetImage(e.Bitmap);
}
You have another potential problem here. This code:
if (Cache.ContainsKey(fileName))
{
onGetImage(Cache[fileName]);
}
If some other thread removes the image from the cache after your call to ContainsKey but before the next line is executed, it's going to crash.
If you're using Dictionary in a multi-threaded context where concurrent threads can be reading and writing, then you need to protect every access with a lock of some kind. lock is convenient, but ReaderWriterLockSlim will provide better performance.
I would also suggest that you re-code the above to be:
Bitmap bmp;
if (Cache.TryGetValue(fileName, out bmp))
{
onGetImage(fileName);
}
If you're running .NET 4.0, then I would strongly suggest that you look into using ConcurrentDictionary.
Why don't you just keep a a collection of image filenames that are being downloaded, and have the code for a thread be:
public void GetImage(string fileName, Action<Bitmap> onGetImage)
{
lock(Cache)
{
if (Cache.ContainsKey(fileName))
{
onGetImage(Cache[fileName]);
}
else if (downloadingCollection.contains(fileName))
{
while (!Cache.ContainsKey(fileName))
{
System.Threading.Monitor.Wait(Cache)
}
onGetImage(Cache[fileName]);
}
else
{
var server = new Server();
downloadCollection.Add(filename);
server.ImageDownloaded += (s, e) =>
{
lock (Cache)
{
downloadCollection.Remove(filename);
Cache.Add(e.Bitmap, e.Name);
System.Threading.Monitor.PulseAll(Cache);
}
onGetImage(e.Bitmap);
}
server.DownloadImageAsync(fileName, onGetImage); // last arg is just passed to the handler
}
}
}
That is more or less the standard monitor pattern, or would be if you refactored the lambda expression into a member function like GetImage. You should really do that. It will make the monitor logic easier to reason about.