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  1. DZone
  2. Data Engineering
  3. Data
  4. Cache: It Ain't Just Remembering Stuff

Cache: It Ain't Just Remembering Stuff

Oren Eini user avatar by
Oren Eini
·
Oct. 17, 13 · Interview
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I mentioned that this piece of code has an issue:

public class LocalizationService
{
    MyEntities _ctx;
    Cache _cache;

    public LocalizationService(MyEntities ctx, Cache cache)
    {
        _ctx = ctx;
        _cache = cache;
        Task.Run(() =>
        {
            foreach(var item in _ctx.Resources)
            {
                _cache.Set(item.Key + "/" + item.LanguageId, item.Text);
            }
        });
    }    

    public string Get(string key, string languageId)
    {
        var cacheKey = key +"/" + languageId;
        var item = _cache.Get(cacheKey);
        if(item != null)
            return item;

        item = _ctx.Resources.Where(x=>x.Key == key && x.LanguageId == languageId).SingleOrDefault();
        _cache.Set(cacheKey, item);
        return item;
    }
}

And I am pretty sure that a lot of you will be able to find a lot of additional issues that I’ve not thought about.

But there are at least three major issues in the code above. It doesn’t do anything to solve the missing value problem, it doesn’t have good handling for expiring values and have no way to handle changing values.

Look at the code above, assume that I am making continuous calls to Get(“does not exists”, “nh-YI”), or something like that. The way the code is currently written, it will always hit the database to get that value.

The second problem is that if we have had a cache cleanup run, which expired some values, we will actually load them one at a time, in pretty much the worst possible way from the point of view of performance.

Then we have the problem of how to actually handle updating values.

Let us see how we can at least approach this. We will replace the Cache with a ConcurrentDictionary. That will mean that the data cannot just go away from under us, and since we expect the number of resources to be relatively low, there is no issue in holding all of them in memory.

Because we know we hold all of them in memory, we can be sure that if the value isn’t there, it isn’t in the database either, so we can immediately return null, without checking with the database.

Last, we will add a StartRefreshingResources task, which will do the actual refreshing in an async manner. In other words:

public class LocalizationService
{
    MyEntities _ctx;
    ConcurrentDictionary<Tuple<string,string>,string> _cache = new ConcurrentDictionary<Tuple<string,string>,string>();

    Task _refreshingResourcesTask;

    public LocalizationService(MyEntities ctx)
    {
        _ctx = ctx;
        StartRefreshingResources();
    } 

    public void StartRefreshingResources()
    {
         _refreshingResourcesTask = Task.Run(() =>
        {
            foreach(var item in _ctx.Resources)
            {
                _cache.Set(item.Key + "/" + item.LanguageId, item.Text);
            }
        });
    }

    public string Get(string key, string languageId)
    {
        var cacheKey = Tuplce.Create(key,languageId);
        var item = _cache.Get(cacheKey);
        if(item != null || _refreshingResourcesTask.IsCompleted)
            return item;

        item = _ctx.Resources.Where(x=>x.Key == key && x.LanguageId == languageId).SingleOrDefault();
        _cache.Set(cacheKey, item);
        return item;
    }
}

Note that there is a very subtle thing going on in here. As long as the async process is running, if we can’t find the value in the cache, we will go to the database to find it. This gives us a good balance between stopping the system entirely for startup/refresh and having the values immediately available.



Cache (computing)

Published at DZone with permission of Oren Eini, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • The Power of Caching: Boosting API Performance and Scalability
  • DevSecOps: Enhancing Security With Vulnerability Scanning of Images and Source Code in CI/CD
  • Designing High-Performance APIs
  • API and Database Performance Optimization Strategies

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