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Asp.Net caching pattern

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a status change, I would like to wait and get the latest info rather than the current info, which if returned, would be out of date.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.

Lock text file during read and write or alternative

I have an application where I need to create files with a unique and sequential number as part of the file name. My first thought was to use (since this application does not have any other data storage) a text file that would contain a number and I would increment this number so then my application would always create a file with a unique id.
Then I thought that maybe at a time when there are more than one user submitting to this application at the same time, one process might be reading the txt file before it has been written by the previous process. So then I am looking for a way to read and write to a file (with try catch so then I can know when it's being used by another process and then wait and try to read from it a few other times) in the same 'process' without unlocking the file in between.
If what I am saying above sounds like a bad option, could you please give me an alternative to this? How would you then keep track of unique identification numbers for an application like my case?
Thanks.

If it's a single application then you can store the current number in your application settings. Load that number at startup. Then with each request you can safely increment it and use the result. Save the sequential number when the program shuts down. For example:
private int _fileNumber;
// at application startup
_fileNumber = LoadFileNumberFromSettings();
// to increment
public int GetNextFile()
{
return Interlocked.Increment(ref _fileNumber);
}
// at application shutdown
SaveFileNumberToSettings(_fileNumber);
Or, you might want to make sure that the file number is saved whenever it's incremented. If so, change your GetNextFile method:
private readonly object _fileLock = new object();
public int GetNextFile()
{
lock (_fileLock)
{
int result = ++_fileNumber;
SaveFileNumbertoSettings(_fileNumber);
return result;
}
}
Note also that it might be reasonable to use the registry for this, rather than a file.

Edit: As Alireza pointed in the comments, it is not a valid way to lock between multiple applications.
You can always lock the access to the file (so you won't need to rely on exceptions).
e.g:
// Create a lock in your class
private static object LockObject = new object();
// and then lock on this object when you access the file like this:
lock(LockObject)
{
... access to the file
}
Edit2: It seems that you can use Mutex to perform inter-application signalling.
private static System.Threading.Mutex m = new System.Threading.Mutex(false, "LockMutex");
void AccessMethod()
{
try
{
m.WaitOne();
// Access the file
}
finally
{
m.ReleaseMutex();
}
}
But it's not the best pattern to generate unique ids. Maybe a sequence in a database would be better ? If you don't have a database, you can use Guids or a local database (even Access would be better I think)

I would prefer a complex and universal solution with the global mutex. It uses a mutex with name prefixed with "Global\" which makes it system-wide i.e. one mutex instance is shared across all processes. if your program runs in friendly environment or you can specify strict permissions limited to a user account you can trust then it works well.
Keep in mind that this solution is not transactional and is not protected against thread-abortion/process-termination.
Not transactional means that if your process/thread is caught in the middle of storage file modification and is terminated/aborted then the storage file will be left in unknown state. For instance it can be left empty. You can protect yourself against loss of data (loss of last used index) by writing the new value first, saving the file and only then removing the previous value. Reading procedure should expect a file with multiple numbers and should take the greatest.
Not protected against thread-abortion means that if a thread which obtained the mutex is aborted unexpectedly and/or you do not have proper exception handling then the mutex could stay locked for the life of the process that created that thread. In order to make solution abort-protected you will have to implement timeouts on obtaining the lock i.e. replace the following line which waits forever
blnResult = iLock.Mutex.WaitOne();
with something with timeout.
Summing this up I try to say that if you are looking for a really robust solution you will come to utilizing some kind of a transactional database or write a kind of such a database yourself :)
Here is the working code without timeout handling (I do not need it in my solution). It is robust enough to begin with.
using System;
using System.IO;
using System.Security.AccessControl;
using System.Security.Principal;
using System.Threading;
namespace ConsoleApplication31
{
class Program
{
//You only need one instance of that Mutex for each application domain (commonly each process).
private static SMutex mclsIOLock;
static void Main(string[] args)
{
//Initialize the mutex. Here you need to know the path to the file you use to store application data.
string strEnumStorageFilePath = Path.Combine(
Environment.GetFolderPath(Environment.SpecialFolder.LocalApplicationData),
"MyAppEnumStorage.txt");
mclsIOLock = IOMutexGet(strEnumStorageFilePath);
}
//Template for the main processing routine.
public static void RequestProcess()
{
//This flag is used to protect against unwanted lock releases in case of recursive routines.
bool blnLockIsSet = false;
try
{
//Obtain the lock.
blnLockIsSet = IOLockSet(mclsIOLock);
//Read file data, update file data. Do not put much of long-running code here.
//Other processes may be waiting for the lock release.
}
finally
{
//Release the lock if it was obtained in this particular call stack frame.
IOLockRelease(mclsIOLock, blnLockIsSet);
}
//Put your long-running code here.
}
private static SMutex IOMutexGet(string iMutexNameBase)
{
SMutex clsResult = null;
clsResult = new SMutex();
string strSystemObjectName = #"Global\" + iMutexNameBase.Replace('\\', '_');
//Give permissions to all authenticated users.
SecurityIdentifier clsAuthenticatedUsers = new SecurityIdentifier(WellKnownSidType.AuthenticatedUserSid, null);
MutexSecurity clsMutexSecurity = new MutexSecurity();
MutexAccessRule clsMutexAccessRule = new MutexAccessRule(
clsAuthenticatedUsers,
MutexRights.FullControl,
AccessControlType.Allow);
clsMutexSecurity.AddAccessRule(clsMutexAccessRule);
//Create the mutex or open an existing one.
bool blnCreatedNew;
clsResult.Mutex = new Mutex(
false,
strSystemObjectName,
out blnCreatedNew,
clsMutexSecurity);
clsResult.IsMutexHeldByCurrentAppDomain = false;
return clsResult;
}
//Release IO lock.
private static void IOLockRelease(
SMutex iLock,
bool? iLockIsSetInCurrentStackFrame = null)
{
if (iLock != null)
{
lock (iLock)
{
if (iLock.IsMutexHeldByCurrentAppDomain &&
(!iLockIsSetInCurrentStackFrame.HasValue ||
iLockIsSetInCurrentStackFrame.Value))
{
iLock.MutexOwnerThread = null;
iLock.IsMutexHeldByCurrentAppDomain = false;
iLock.Mutex.ReleaseMutex();
}
}
}
}
//Set the IO lock.
private static bool IOLockSet(SMutex iLock)
{
bool blnResult = false;
try
{
if (iLock != null)
{
if (iLock.MutexOwnerThread != Thread.CurrentThread)
{
blnResult = iLock.Mutex.WaitOne();
iLock.IsMutexHeldByCurrentAppDomain = blnResult;
if (blnResult)
{
iLock.MutexOwnerThread = Thread.CurrentThread;
}
else
{
throw new ApplicationException("Failed to obtain the IO lock.");
}
}
}
}
catch (AbandonedMutexException iMutexAbandonedException)
{
blnResult = true;
iLock.IsMutexHeldByCurrentAppDomain = true;
iLock.MutexOwnerThread = Thread.CurrentThread;
}
return blnResult;
}
}
internal class SMutex
{
public Mutex Mutex;
public bool IsMutexHeldByCurrentAppDomain;
public Thread MutexOwnerThread;
}
}

Monitor.TryEnter for multiple resources

I tried searching for this but did not find the suggestion best suited for the issue that I am facing.
My issue is that we have list/stack of available resources (Calculation Engines). These resources are used to perform certain calculation.
The request to perform the calculation is triggered from an external process. So when the request for calculation is made, I need to check if any of the available resources are currently not performing other calculations, If so wait for some time and check again.
I was wondering what the best way to implement this is. I have the following code in place, but not sure if it is very safe.
If you have any further suggestions, that will be great:
void Process(int retries = 0) {
CalcEngineConnection connection = null;
bool securedConnection = false;
foreach (var calcEngineConnection in _connections) {
securedConnection = Monitor.TryEnter(calcEngineConnection);
if (securedConnection) {
connection = calcEngineConnection;
break;
}
}
if (securedConnection) {
//Dequeue the next request
var calcEnginePool = _pendingPool.Dequeue();
//Perform the operation and exit.
connection.RunCalc(calcEnginePool);
Monitor.Exit(connection);
}
else {
if (retries < 10)
retries += 1;
Thread.Sleep(200);
Process(retries);
}
}

I'm not sure that using Monitor is the best approach here anyway, but if you do decide to go that route, I'd refactor the above code to:
bool TryProcessWithRetries(int retries) {
for (int attempt = 0; attempt < retries; attempt++) {
if (TryProcess()) {
return true;
}
Thread.Sleep(200);
}
// Throw an exception here instead?
return false;
}
bool TryProcess() {
foreach (var connection in _connections) {
if (TryProcess(connection)) {
return true;
}
}
return false;
}
bool TryProcess(CalcEngineConnection connection) {
if (!Monitor.TryEnter(connection)) {
return false;
}
try {
var calcEnginePool = _pendingPool.Dequeue();
connection.RunCalc(calcEnginePool);
} finally {
Monitor.Exit(connection);
}
return true;
}
This decomposes the three pieces of logic:
Retrying several times
Trying each connection in a collection
Trying a single connection
It also avoids using recursion for the sake of it, and puts the Monitor.Exit call into a finally block, which it absolutely should be in.
You could replace the middle method implementation with:
return _connections.Any(TryProcess);
... but that may be a little too "clever" for its own good.
Personally I'd be tempted to move TryProcess into CalcEngineConnection itself - that way this code doesn't need to know about whether or not the connection is able to process something - it's up to the object itself. It means you can avoid having publicly visible locks, and also it would be flexible if some resources could (say) process two requests at a time in the future.

There are multiple issues that could potentially occur, but let's simplify your code first:
void Process(int retries = 0)
{
foreach (var connection in _connections)
{
if(Monitor.TryEnter(connection))
{
try
{
//Dequeue the next request
var calcEnginePool = _pendingPool.Dequeue();
//Perform the operation and exit.
connection.RunCalc(calcEnginePool);
}
finally
{
// Release the lock
Monitor.Exit(connection);
}
return;
}
}
if (retries < 10)
{
Thread.Sleep(200);
Process(retries+1);
}
}
This will correctly protect your connection, but note that one of the assumptions here is that your _connections list is safe and it will not be modified by another thread.
Furthermore, you might want to use a thread safe queue for the _connections because at certain load levels you might end up using only the first few connections (not sure if that will make a difference). In order to use all of your connections relatively evenly, I would place them in a queue and dequeue them. This will also guarantee that no two threads are using the same connection and you don't have to use the Monitor.TryEnter().

Pattern for concurrent cache sharing

Ok I was a little unsure on how best name this problem :) But assume this scenarion, you're
going out and fetching some webpage (with various urls) and caching it locally. The cache part is pretty easy to solve even with multiple threads.
However, imagine that one thread starts fetching an url, and a couple of milliseconds later another want to get the same url. Is there any good pattern for making the seconds thread's method wait on the first one to fetch the page , insert it into the cache and return it so you don't have to do multiple requests. With little enough overhead that it's worth doing even for requests that take about 300-700 ms? And without locking requests for other urls
Basically when requests for identical urls comes in tightly after each other I want the second request to "piggyback" the first request
I had some loose idea of having a dictionary where you insert an object with the key as url when you start fetching a page and lock on it. If there's any matching the key already it get's the object, locks on it and then tries to fetch the url for the actual cache.
I'm a little unsure of the particulars however to make it really thread-safe, using ConcurrentDictionary might be one part of it...
Is there any common pattern and solutions for scenarios like this?
Breakdown wrong behavior:
Thread 1: Checks the cache, it doesnt exists so starts fetching the url
Thread 2: Starts fetching the same url since it still doesn't exist in Cache
Thread 1: finished and inserts into the cache, returns the page
Thread 2: Finishes and also inserts into cache (or discards it), returns the page
Breakdown correct behavior:
Thread 1: Checks the cache, it doesnt exists so starts fetching the url
Thread 2: Wants the same url, but sees it's currently being fetched so waits on thread 1
Thread 1: finished and inserts into the cache, returns the page
Thread 2: Notices that thread 1 is finished and returns the page thread 1 it fetched
EDIT
Most solutions sofar seem to misunderstand the problem and only addressing the caching, as I said that isnt the problem, the problem is when doing an external web fetch to make the second fetch that is done before the first one has cached it to use the result from the first rather then doing a second

You could use a ConcurrentDictionary<K,V> and a variant of double-checked locking:
public static string GetUrlContent(string url)
{
object value1 = _cache.GetOrAdd(url, new object());
if (value1 == null) // null check only required if content
return null; // could legitimately be a null string
var urlContent = value1 as string;
if (urlContent != null)
return urlContent; // got the content
// value1 isn't a string which means that it's an object to lock against
lock (value1)
{
object value2 = _cache[url];
// at this point value2 will *either* be the url content
// *or* the object that we already hold a lock against
if (value2 != value1)
return (string)value2; // got the content
urlContent = FetchContentFromTheWeb(url); // todo
_cache[url] = urlContent;
return urlContent;
}
}
private static readonly ConcurrentDictionary<string, object> _cache =
new ConcurrentDictionary<string, object>();

EDIT: My code is quite a bit uglier now, but uses a separate lock per URL. This allows different URLs to be fetched asynchronously, however each URL will only be fetched once.
public class UrlFetcher
{
static Hashtable cache = Hashtable.Synchronized(new Hashtable());
public static String GetCachedUrl(String url)
{
// exactly 1 fetcher is created per URL
InternalFetcher fetcher = (InternalFetcher)cache[url];
if( fetcher == null )
{
lock( cache.SyncRoot )
{
fetcher = (InternalFetcher)cache[url];
if( fetcher == null )
{
fetcher = new InternalFetcher(url);
cache[url] = fetcher;
}
}
}
// blocks all threads requesting the same URL
return fetcher.Contents;
}
/// <summary>Each fetcher locks on itself and is initilized with null contents.
/// The first thread to call fetcher.Contents will cause the fetch to occur, and
/// block until completion.</summary>
private class InternalFetcher
{
private String url;
private String contents;
public InternalFetcher(String url)
{
this.url = url;
this.contents = null;
}
public String Contents
{
get
{
if( contents == null )
{
lock( this ) // "this" is an instance of InternalFetcher...
{
if( contents == null )
{
contents = FetchFromWeb(url);
}
}
}
return contents;
}
}
}
}

Will the Semaphore please stand up! stand up! stand up!
use Semaphore you can easily synchronize your threads with it.
on both cases where
you are trying to load a page that is currently being cached
you are saving cache to a file where a page is loading from it.
in both scenarios you will face troubles.
it is just like writers and readers problem that is a common problem in Operating System Racing Issues. just when a thread wants to rebuild a cache or start caching a page no thread should read from it. if a thread is reading it it should wait until reading finished and replace the cache, no 2 threads should cache same page in to a same file. hence it is possible for all readers to read from a cache at anytime since no writer is writing on it.
you should read some semaphore using samples on msdn, it is very easy to use. just the thread that wants to do something is call the semaphore and if the resource can granted it do the works otherwise sleeps and wait to be woken up when the resource is ready.

Disclaimer: This might be a n00bish answer. Please pardon me, if it is.
I'd recommend using some shared dictionary object with locks to keep a track of the url being currently fetched or have already been fetched.
At every request, check the url against this object.
If an entry for the url is present, check the cache. (this means one of the threads has either fetched it or is currently fetching it)
If its available in the cache, use it, else put the current thread to sleep for a while and check back again. (if not in cache, some thread is still fetching it, so wait while its done)
If the entry is not found in the dictionary object, add the url to it and send the request. Once it obtains a response, add it to cache.
This logic should work, however, you would need to take care of cache expiration and removal of the entry from the dictionary object.

my solution is use atomicBoolean to control access database when cache is timeout or unexist;
at the same moment, only one thread(i call it read-th) can access database, the other threads spin until the read-th return data and write it into cache;
here codes; implement by java;
public class CacheBreakDownDefender<K, R> {
/**
* false = do not write null to cache when get null value from database;
*/
private final boolean writeNullToCache;
/**
* cache different query key
*/
private final ConcurrentHashMap<K, AtomicBoolean> selectingDBTagMap = new ConcurrentHashMap<>();
public static <K, R> CacheBreakDownDefender<K, R> getInstance(Class<K> keyType, Class<R> resultType) {
return Singleton.get(keyType.getName() + resultType.getName(), () -> new CacheBreakDownDefender<>(false));
}
public static <K, R> CacheBreakDownDefender<K, R> getInstance(Class<K> keyType, Class<R> resultType, boolean writeNullToCache) {
return Singleton.get(keyType.getName() + resultType.getName(), () -> new CacheBreakDownDefender<>(writeNullToCache));
}
private CacheBreakDownDefender(boolean writeNullToCache) {
this.writeNullToCache = writeNullToCache;
}
public R readFromCache(K key, Function<K, ? extends R> getFromCache, Function<K, ? extends R> getFromDB, BiConsumer<K, R> writeCache) throws InterruptedException {
R result = getFromCache.apply(key);
if (result == null) {
final AtomicBoolean selectingDB = selectingDBTagMap.computeIfAbsent(key, x -> new AtomicBoolean(false));
if (selectingDB.compareAndSet(false, true)) {
try {
result = getFromDB.apply(key);
if (result != null || writeNullToCache) {
writeCache.accept(key, result);
}
} finally {
selectingDB.getAndSet(false);
selectingDBTagMap.remove(key);
}
} else {
while (selectingDB.get()) {
TimeUnit.MILLISECONDS.sleep(0L);
//do nothing...
}
return getFromCache.apply(key);
}
}
return result;
}
public static void main(String[] args) throws InterruptedException {
Map<String, String> map = new ConcurrentHashMap<>();
CacheBreakDownDefender<String, String> instance = CacheBreakDownDefender.getInstance(String.class, String.class, true);
for (int i = 0; i < 9; i++) {
int finalI = i;
new Thread(() -> {
String kele = null;
try {
if (finalI == 6) {
kele = instance.readFromCache("kele2", map::get, key -> "helloword2", map::put);
} else
kele = instance.readFromCache("kele", map::get, key -> "helloword", map::put);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
}
log.info("resut= {}", kele);
}).start();
}
TimeUnit.SECONDS.sleep(2L);
}
}

This is not exactly for concurrent caches but for all caches:
"A cache with a bad policy is another name for a memory leak" (Raymond Chen)

Dual-queue producer-consumer in .NET (forcing member variable flush)

I have a thread which produces data in the form of simple object (record). The thread may produce a thousand records for each one that successfully passes a filter and is actually enqueued. Once the object is enqueued it is read-only.
I have one lock, which I acquire once the record has passed the filter, and I add the item to the back of the producer_queue.
On the consumer thread, I acquire the lock, confirm that the producer_queue is not empty,
set consumer_queue to equal producer_queue, create a new (empty) queue, and set it on producer_queue. Without any further locking I process consumer_queue until it's empty and repeat.
Everything works beautifully on most machines, but on one particular dual-quad server I see in ~1/500k iterations an object that is not fully initialized when I read it out of consumer_queue. The condition is so fleeting that when I dump the object after detecting the condition the fields are correct 90% of the time.
So my question is this: how can I assure that the writes to the object are flushed to main memory when the queue is swapped?
Edit:
On the producer thread:
(producer_queue above is m_fillingQueue; consumer_queue above is m_drainingQueue)
private void FillRecordQueue() {
while (!m_done) {
int count;
lock (m_swapLock) {
count = m_fillingQueue.Count;
}
if (count > 5000) {
Thread.Sleep(60);
} else {
DataRecord rec = GetNextRecord();
if (rec == null) break;
lock (m_swapLock) {
m_fillingQueue.AddLast(rec);
}
}
}
}
In the consumer thread:
private DataRecord Next(bool remove) {
bool drained = false;
while (!drained) {
if (m_drainingQueue.Count > 0) {
DataRecord rec = m_drainingQueue.First.Value;
if (remove) m_drainingQueue.RemoveFirst();
if (rec.Time < FIRST_VALID_TIME) {
throw new InvalidOperationException("Detected invalid timestamp in Next(): " + rec.Time + " from record " + rec);
}
return rec;
} else {
lock (m_swapLock) {
m_drainingQueue = m_fillingQueue;
m_fillingQueue = new LinkedList<DataRecord>();
if (m_drainingQueue.Count == 0) drained = true;
}
}
}
return null;
}
The consumer is rate-limited, so it can't get ahead of the consumer.
The behavior I see is that sometimes the Time field is reading as DateTime.MinValue; by the time I construct the string to throw the exception, however, it's perfectly fine.

Have you tried the obvious: is microcode update applied on the fancy 8-core box(via BIOS update)? Did you run Windows Updates to get the latest processor driver?
At the first glance, it looks like you're locking your containers. So I am recommending the systems approach, as it sound like you're not seeing this issue on a good-ol' dual core box.

Assuming these are in fact the only methods that interact with the m_fillingQueue variable, and that DataRecord cannot be changed after GetNextRecord() creates it (read-only properties hopefully?), then the code at least on the face of it appears to be correct.
In which case I suggest that GregC's answer would be the first thing to check; make sure the failing machine is fully updated (OS / drivers / .NET Framework), becasue the lock statement should involve all the required memory barriers to ensure that the rec variable is fully flushed out of any caches before the object is added to the list.