I've been trying to solve this issue for quite some time now. I've written some example code showcasing the usage of lock in C#. Running my code manually I can see that it works the way it should, but of course I would like to write a unit test that confirms my code.
I have the following ObjectStack.cs class:
enum ExitCode
{
Success = 0,
Error = 1
}
public class ObjectStack
{
private readonly Stack<Object> _objects = new Stack<object>();
private readonly Object _lockObject = new Object();
private const int NumOfPopIterations = 1000;
public ObjectStack(IEnumerable<object> objects)
{
foreach (var anObject in objects) {
Push(anObject);
}
}
public void Push(object anObject)
{
_objects.Push(anObject);
}
public void Pop()
{
_objects.Pop();
}
public void ThreadSafeMultiPop()
{
for (var i = 0; i < NumOfPopIterations; i++) {
lock (_lockObject) {
try {
Pop();
}
//Because of lock, the stack will be emptied safely and no exception is ever caught
catch (InvalidOperationException) {
Environment.Exit((int)ExitCode.Error);
}
if (_objects.Count == 0) {
Environment.Exit((int)ExitCode.Success);
}
}
}
}
public void ThreadUnsafeMultiPop()
{
for (var i = 0; i < NumOfPopIterations; i++) {
try {
Pop();
}
//Because there is no lock, an exception is caught when popping an already empty stack
catch (InvalidOperationException) {
Environment.Exit((int)ExitCode.Error);
}
if (_objects.Count == 0) {
Environment.Exit((int)ExitCode.Success);
}
}
}
}
And Program.cs:
public class Program
{
private const int NumOfObjects = 100;
private const int NumOfThreads = 10000;
public static void Main(string[] args)
{
var objects = new List<Object>();
for (var i = 0; i < NumOfObjects; i++) {
objects.Add(new object());
}
var objectStack = new ObjectStack(objects);
Parallel.For(0, NumOfThreads, x => objectStack.ThreadUnsafeMultiPop());
}
}
I'm trying to write a unit that tests the thread unsafe method, by checking the exit code value (0 = success, 1 = error) of the executable.
I tried to start and run the application executable as a process in my test, a couple of 100 times, and checked the exit code value each time in the test. Unfortunately, it was 0 every single time.
Any ideas are greatly appreciated!
Logically, there is one, very small, piece of code where this problem can happen. Once one of the threads enters the block of code that pops a single element, then either the pop will work in which case the next line of code in that thread will Exit with success OR the pop will fail in which case the next line of code will catch the exception and Exit.
This means that no matter how much parallelization you put into the program, there is still only one single point in the whole program execution stack where the issue can occur and that is directly before the program exits.
The code is genuinely unsafe, but the probability of an issue happening in any single execution of the code is extremely low as it requires the scheduler to decide not to execute the line of code that will exit the environment cleanly and instead let one of the other Threads raise an exception and exit with an error.
It is extremely difficult to "prove" that a concurrency bug exists, except for really obvious ones, because you are completely dependent on what the scheduler decides to do.
Looking up some other posts I see this post which is written related to Java but references C#: How should I unit test threaded code?
It includes a link to this which might be useful to you: http://research.microsoft.com/en-us/projects/chess/
Hope this is useful and apologies if it is not. Testing concurrency is inherently unpredictable as is writing example code to cause it.
Thanks for all the input! Although I do agree that this is a concurrency issue quite hard to detect due to the scheduler execution among other things, I seem to have found an acceptable solution to my problem.
I wrote the following unit test:
[TestMethod]
public void Executable_Process_Is_Thread_Safe()
{
const string executablePath = "Thread.Locking.exe";
for (var i = 0; i < 1000; i++) {
var process = new Process() {StartInfo = {FileName = executablePath}};
process.Start();
process.WaitForExit();
if (process.ExitCode == 1) {
Assert.Fail();
}
}
}
When I ran the unit test, it seemed that the Parallel.For execution in Program.cs threw strange exceptions at times, so I had to change that to traditional for-loops:
public class Program
{
private const int NumOfObjects = 100;
private const int NumOfThreads = 10000;
public static void Main(string[] args)
{
var objects = new List<Object>();
for (var i = 0; i < NumOfObjects; i++) {
objects.Add(new object());
}
var tasks = new Task[NumOfThreads];
var objectStack = new ObjectStack(objects);
for (var i = 0; i < NumOfThreads; i++)
{
var task = new Task(objectStack.ThreadUnsafeMultiPop);
tasks[i] = task;
}
for (var i = 0; i < NumOfThreads; i++)
{
tasks[i].Start();
}
//Using this seems to throw exceptions from unit test context
//Parallel.For(0, NumOfThreads, x => objectStack.ThreadUnsafeMultiPop());
}
Of course, the unit test is quite dependent on the machine you're running it on (a fast processor may be able to empty the stack and exit safely before reaching the critical section in all cases).
1.) You could inject IL Inject Context switches on a post build of your code in the form of Thread.Sleep(0) using ILGenerator which would most likely help these issues to arise.
2.) I would recommend you take a look at the CHESS project by Microsoft research team.
There are a great number of articles available regarding thread safe caching, here's an example:
private static object _lock = new object();
public void CacheData()
{
SPListItemCollection oListItems;
oListItems = (SPListItemCollection)Cache["ListItemCacheName"];
if(oListItems == null)
{
lock (_lock)
{
// Ensure that the data was not loaded by a concurrent thread
// while waiting for lock.
oListItems = (SPListItemCollection)Cache[“ListItemCacheName”];
if (oListItems == null)
{
oListItems = DoQueryToReturnItems();
Cache.Add("ListItemCacheName", oListItems, ..);
}
}
}
}
However, this example depends on the request for the cache also rebuilding the cache.
I'm looking for a solution where the request and rebuild are separate. Here's the scenario.
I have a web service that I want to monitor for certain types of error. If an error occurs, I create an monitor object and cache - it is updatable and is locked accordingly during update. Alls well so far.
Elsewhere, I check for the existence of the cached object, and the data it contains. This would work straight out of the box except for one particular scenario.
If the cache object is being updated - say a status change, I would like to wait and get the latest info rather than the current info, which if returned, would be out of date. So for my fetch code, I need to check if the object is currently being created/updating, and if so wait, then retry.
As I pointed out, there are many examples of cache locking patterns but I can't seem to find one that for this scenario. Any ideas as to how to go about this would be appreciated?
You can try the following code using two locks. Write lock in the setter is quite simple and protects cache from being written by more than one threads. The getter use a simple double-check lock.
Now, the trick is in Refresh() method, which uses the same lock as the getter. The method uses the lock and in the first step removes list from the cache. It will trigger any getter to fail the first null check and wait for the lock. The method in the meantime gets items, sets cache again and releases the lock.
When it comes back to the getter, it reads the cache again and now it contains the list.
public class CacheData
{
private static object _readLock = new object();
private static object _writeLock = new object();
public SPListItemCollection ListItem
{
get
{
var oListItems = (SPListItemCollection) Cache["ListItemCacheName"];
if (oListItems == null)
{
lock (_readLock)
{
oListItems = (SPListItemCollection)Cache["ListItemCacheName"];
if (oListItems == null)
{
oListItems = DoQueryToReturnItems();
Cache.Add("ListItemCacheName", oListItems, ..);
}
}
}
return oListItems;
}
set
{
lock (_writeLock)
{
Cache.Add("ListItemCacheName", value, ..);
}
}
}
public void Refresh()
{
lock (_readLock)
{
Cache.Remove("ListItemCacheName");
var oListItems = DoQueryToReturnItems();
ListItem = oListItems;
}
}
}
You can make the method and property static, if you do not need CacheData instance.
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 ;)
Suppose I have the following class:
Public class FooBar
{
List<Items> _items = new List<Items>();
public List<Items> FetchItems(int parentItemId)
{
FetchSingleItem(int itemId);
return _items
}
private void FetchSingleItem(int itemId)
{
Uri url = new Uri(String.Format("http://SomeURL/{0}.xml", itemId);
HttpWebRequest webRequest = (HttpWebRequest)HttpWebRequest.Create(url);
webRequest.BeginGetResponse(ReceiveResponseCallback, webRequest);
}
void ReceiveResponseCallback(IAsyncResult result)
{
// End the call and extract the XML from the response and add item to list
_items.Add(itemFromXMLResponse);
// If this item is linked to another item then fetch that item
if (anotherItemIdExists == true)
{
FetchSingleItem(anotherItemId);
}
}
}
There could be any number of linked items that I will only know about at runtime.
What I want to do is make the initial call to FetchSingleItem and then wait until all calls have completed then return List<Items> to the calling code.
Could someone point me in the right direction? I more than happy to refactor the whole thing if need be (which I suspect will be the case!)
Getting the hang of asynchronous coding is not easy especially when there is some sequential dependency between one operation and the next. This is the exact sort of problem that I wrote the AsyncOperationService to handle, its a cunningly short bit of code.
First a little light reading for you: Simple Asynchronous Operation Runner – Part 2. By all means read part 1 but its a bit heavier than I had intended. All you really need is the AsyncOperationService code from it.
Now in your case you would convert your fetch code to something like the following.
private IEnumerable<AsyncOperation> FetchItems(int startId)
{
XDocument itemDoc = null;
int currentId = startId;
while (currentID != 0)
{
yield return DownloadString(new Uri(String.Format("http://SomeURL/{0}.xml", currentId), UriKind.Absolute),
itemXml => itemDoc = XDocument.Parse(itemXml) );
// Do stuff with itemDoc like creating your item and placing it in the list.
// Assign the next linked ID to currentId or if no other items assign 0
}
}
Note the blog also has an implementation of DownloadString which in turn uses WebClient which simplifies things. However the principles still apply if for some reason you must stick with HttpWebRequest. (Let me know if you are having trouble creating an AsyncOperation for this)
You would then use this code like this:-
int startId = GetSomeIDToStartWith();
Foo myFoo = new Foo();
myFoo.FetchItems(startId).Run((err) =>
{
// Clear IsBusy
if (err == null)
{
// All items are now fetched continue doing stuff here.
}
else
{
// "Oops something bad happened" code here
}
}
// Set IsBusy
Note that the call to Run is asynchronous, code execution will appear to jump past it before all the items are fetched. If the UI is useless to the user or even dangerous then you need to block it in a friendly way. The best way (IMO) to do this is with the BusyIndicator control from the toolkit, setting its IsBusy property after the call to Run and clearing it in the Run callback.
All you need is a thread sync thingy. I chose ManualResetEvent.
However, I don't see the point of using asynchronous IO since you always wait for the request to finish before starting a new one. But the example might not show the whole story?
Public class FooBar
{
private ManualResetEvent _completedEvent = new ManualResetEvent(false);
List<Items> _items = new List<Items>();
public List<Items> FetchItems(int parentItemId)
{
FetchSingleItem(itemId);
_completedEvent.WaitOne();
return _items
}
private void FetchSingleItem(int itemId)
{
Uri url = new Uri(String.Format("http://SomeURL/{0}.xml", itemId);
HttpWebRequest webRequest = (HttpWebRequest)HttpWebRequest.Create(url);
webRequest.BeginGetResponse(ReceiveResponseCallback, webRequest);
}
void ReceiveResponseCallback(IAsyncResult result)
{
// End the call and extract the XML from the response and add item to list
_items.Add(itemFromXMLResponse);
// If this item is linked to another item then fetch that item
if (anotherItemIdExists == true)
{
FetchSingleItem(anotherItemId);
}
else
_completedEvent.Set();
}
}
I asked a question about building custom Thread Safe Generic List now I am trying to unit test it and I absolutely have no idea how to do that. Since the lock happens inside the ThreadSafeList class I am not sure how to make the list to lock for a period of time while I am try to mimic the multiple add call. Thanks.
Can_add_one_item_at_a_time
[Test]
public void Can_add_one_item_at_a_time() //this test won't pass
{
//I am not sure how to do this test...
var list = new ThreadSafeList<string>();
//some how need to call lock and sleep inside list instance
//say somehow list locks for 1 sec
var ta = new Thread(x => list.Add("a"));
ta.Start(); //does it need to aboard say before 1 sec if locked
var tb = new Thread(x => list.Add("b"));
tb.Start(); //does it need to aboard say before 1 sec if locked
//it involves using GetSnapshot()
//which is bad idea for unit testing I think
var snapshot = list.GetSnapshot();
Assert.IsFalse(snapshot.Contains("a"), "Should not contain a.");
Assert.IsFalse(snapshot.Contains("b"), "Should not contain b.");
}
Snapshot_should_be_point_of_time_only
[Test]
public void Snapshot_should_be_point_of_time_only()
{
var list = new ThreadSafeList<string>();
var ta = new Thread(x => list.Add("a"));
ta.Start();
ta.Join();
var snapshot = list.GetSnapshot();
var tb = new Thread(x => list.Add("b"));
tb.Start();
var tc = new Thread(x => list.Add("c"));
tc.Start();
tb.Join();
tc.Join();
Assert.IsTrue(snapshot.Count == 1, "Snapshot should only contain 1 item.");
Assert.IsFalse(snapshot.Contains("b"), "Should not contain a.");
Assert.IsFalse(snapshot.Contains("c"), "Should not contain b.");
}
Instance method
public ThreadSafeList<T> Instance<T>()
{
return new ThreadSafeList<T>();
}
Let's look at your first test, Can_add_one_item_at_a_time.
First of all, your exit conditions don't make sense. Both items should be added, just one at a time. So of course your test will fail.
You also don't need to make a snapshot; remember, this is a test, nothing else is going to be touching the list while your test is running.
Last but not least, you need to make sure that you aren't trying to evaluate your exit conditions until all of the threads have actually finished. Simplest way is to use a counter and a wait event. Here's an example:
[Test]
public void Can_add_from_multiple_threads()
{
const int MaxWorkers = 10;
var list = new ThreadSafeList<int>(MaxWorkers);
int remainingWorkers = MaxWorkers;
var workCompletedEvent = new ManualResetEvent(false);
for (int i = 0; i < MaxWorkers; i++)
{
int workerNum = i; // Make a copy of local variable for next thread
ThreadPool.QueueUserWorkItem(s =>
{
list.Add(workerNum);
if (Interlocked.Decrement(ref remainingWorkers) == 0)
workCompletedEvent.Set();
});
}
workCompletedEvent.WaitOne();
workCompletedEvent.Close();
for (int i = 0; i < MaxWorkers; i++)
{
Assert.IsTrue(list.Contains(i), "Element was not added");
}
Assert.AreEqual(MaxWorkers, list.Count,
"List count does not match worker count.");
}
Now this does carry the possibility that the Add happens so quickly that no two threads will ever attempt to do it at the same time. No Refunds No Returns partially explained how to insert a conditional delay. I would actually define a special testing flag, instead of DEBUG. In your build configuration, add a flag called TEST, then add this to your ThreadSafeList class:
public class ThreadSafeList<T>
{
// snip fields
public void Add(T item)
{
lock (sync)
{
TestUtil.WaitStandardThreadDelay();
innerList.Add(item);
}
}
// snip other methods/properties
}
static class TestUtil
{
[Conditional("TEST")]
public static void WaitStandardThreadDelay()
{
Thread.Sleep(1000);
}
}
This will cause the Add method to wait 1 second before actually adding the item as long as the build configuration defines the TEST flag. The entire test should take at least 10 seconds; if it finishes any faster than that, something's wrong.
With that in mind, I'll leave the second test up to you. It's similar.
You will need to insert some TESTONLY code that adds a delay in your lock. You can create a function like this:
[Conditional("DEBUG")]
void SleepForABit(int delay) { thread.current.sleep(delay); }
and then call it in your class. The Conditional attribute ensure it is only called in DEBUG builds and you can leave it in your compiled code.
Write something which consistently delays 100Ms or so and something that never waits and let'em slug it out.
You might want to take a look at Chess. It's a program specifically designed to find race conditions in multi-threaded code.