TPL数据流IO读写操作实现中的内存问题

本文关键字:内存 问题 实现 操作 数据流 IO 读写 TPL | 更新日期: 2023-09-27 18:27:52

我尝试使用File IO操作来实现读写操作,并将这些操作封装到TransformBlock中,以使这些操作线程安全,而不是使用锁定机制。

但问题是,当我尝试并行写入甚至5个文件时,会出现内存溢出异常,并且在使用此实现时会阻塞UI线程。实现是在Windows Phone项目中完成的。请指出这句话的错误之处。

文件IO操作

public static readonly IsolatedStorageFile _isolatedStore = IsolatedStorageFile.GetUserStoreForApplication();
public static readonly FileIO _file = new FileIO();
public static readonly ConcurrentExclusiveSchedulerPair taskSchedulerPair = new ConcurrentExclusiveSchedulerPair();
public static readonly ExecutionDataflowBlockOptions exclusiveExecutionDataFlow 
    = new ExecutionDataflowBlockOptions
{
    TaskScheduler = taskSchedulerPair.ExclusiveScheduler,
    BoundedCapacity = 1
};
public static readonly ExecutionDataflowBlockOptions concurrentExecutionDataFlow 
    = new ExecutionDataflowBlockOptions
{
    TaskScheduler = taskSchedulerPair.ConcurrentScheduler,
    BoundedCapacity = 1
};
public static async Task<T> LoadAsync<T>(string fileName)
{
    T result = default(T);
    var transBlock = new TransformBlock<string, T>
       (async fName =>
       {
           return await LoadData<T>(fName);
       }, concurrentExecutionDataFlow);
    transBlock.Post(fileName);
    result = await transBlock.ReceiveAsync();
    return result;
}
public static async Task SaveAsync<T>(T obj, string fileName)
{
    var transBlock = new TransformBlock<Tuple<T, string>, Task>
       (async tupleData =>
       {
          await SaveData(tupleData.Item1, tupleData.Item2);
       }, exclusiveExecutionDataFlow);
    transBlock.Post(new Tuple<T, string>(obj, fileName));
    await transBlock.ReceiveAsync();
}

MainPage.xaml.cs用法

private static string data = "vjdsskjfhkjsdhvnvndjfhjvkhdfjkgd"
private static string fileName = string.Empty;
private List<string> DataLstSample = new List<string>();
private ObservableCollection<string> TestResults = new ObservableCollection<string>();
private static string data1 = "hjhkjhkhkjhjkhkhkjhkjhkhjkhjkh";
List<Task> allTsk = new List<Task>();
private Random rand = new Random();
private string  fileNameRand
{
    get
    {
        return rand.Next(100).ToString();
    }
}
public MainPage()
{
    InitializeComponent();
    for (int i = 0; i < 5; i ++)
    {
        DataLstSample.Add((i % 2) == 0 ? data : data1);
    }
}
private void Button_Click(object sender, RoutedEventArgs e)
{
    AppIsolatedStore_TestInMultiThread_LstResultShouldBeEqual();
}
public async void AppIsolatedStore_TestInMultiThread_LstResultShouldBeEqual()
{
    TstRst.Text = "InProgress..";
    allTsk.Clear();
    foreach(var data in DataLstSample)
    {
        var fName = fileNameRand;
        var t = Task.Run(async () =>
        {
            await AppIsolatedStore.SaveAsync<string>(data, fName);
        });
        TestResults.Add(string.Format("Writing file name: {0}, data: {1}", fName, data));
        allTsk.Add(t);
    }
    await Task.WhenAll(allTsk);
    TstRst.Text = "Completed..";
}

异步保存和加载数据

        /// <summary>
        /// Load object from file
        /// </summary>
        private static async Task<T> LoadData<T>(string fileName)
        {
            T result = default(T);
            try
            {
                if (!string.IsNullOrWhiteSpace(fileName))
                {
                    using (var file = new IsolatedStorageFileStream(fileName, FileMode.OpenOrCreate, _isolatedStore))
                    {
                        var data = await _file.ReadTextAsync(file);
                        if (!string.IsNullOrWhiteSpace(data))
                        {
                            result = JsonConvert.DeserializeObject<T>(data);
                        }
                    }
                }
            }
            catch (Exception ex)
            {
                //todo: log the megatron exception in a file
                Debug.WriteLine("AppIsolatedStore: LoadAsync : An error occured while loading data : {0}", ex.Message);
            }
            finally
            {
            }
            return result;
        }

        /// <summary>
        /// Save object from file
        /// </summary>
        private static async Task SaveData<T>(T obj, string fileName)
        {
            try
            {
                if (obj != null && !string.IsNullOrWhiteSpace(fileName))
                {
                    //Serialize object with JSON or XML serializer
                    string storageString = JsonConvert.SerializeObject(obj);
                    if (!string.IsNullOrWhiteSpace(storageString))
                    {
                        //Write content to file
                        await _file.WriteTextAsync(new IsolatedStorageFileStream(fileName, FileMode.Create, _isolatedStore), storageString);
                    }
                }
            }
            catch (Exception ex)
            {
                //todo: log the megatron exception in a file
                Debug.WriteLine("AppIsolatedStore: SaveAsync : An error occured while saving the data : {0}", ex.Message);
            }
            finally
            {
            }
        }

编辑:

它出现内存异常的原因之一是我获取的数据字符串太大。字符串是链接:http://1drv.ms/1QWSAsc

但第二个问题是,如果我也添加了小数据,那么它就会阻塞UI线程。代码是否在UI踏板上执行任何任务?

TPL数据流IO读写操作实现中的内存问题

不,您使用的并发对为其任务使用默认线程池,并且您使用Run方法实例化任务,所以问题不在这里。但是这里的代码有两个主要威胁:

var transBlock = new TransformBlock<string, T>
   (async fName =>
   {
       // process file here
   }, concurrentExecutionDataFlow);

你真的不应该每次都创建transBlockTPL Dataflow的主要思想是创建一次块,然后使用它们。因此,您应该重构应用程序以减少正在实例化的块的数量,否则就不应该使用TPL Dataflow

代码中的另一个威胁是显式地阻止线程!

// Right here
await Task.WhenAll(allTsk);
TstRst.Text = "Completed..";

从同步事件处理程序的async void方法中为任务调用await会阻塞线程,因为默认情况下它会捕获同步上下文。首先,应避免async void。第二,如果您是异步的,那么您应该一直是异步的。所以事件处理程序也应该是异步的(async)。第三,您可以使用任务的延续来更新UI或使用当前同步上下文。

所以,你的代码应该是这样的:

// store the sync context in the field of your form
SynchronizationContext syncContext = SynchronizationContext.Current;
// avoid the async void :)
public async Task AppIsolatedStore_TestInMultiThread_LstResultShouldBeEqual()
// make event handler async - this is the only exception for the async void use rule from above
private async void Button_Click(object sender, RoutedEventArgs e)
// asynchronically wait the result without capturing the context
await Task.WhenAll(allTsk).ContinueWith(
  t => {
    // you can move out this logic to main method
    syncContext.Post(new SendOrPostCallback(o =>
        {
            TstRst.Text = "Completed..";
        }));
  }
);

您是否尝试过在ExecutionDataflowBlockOptions上使用BoundedCapacity参数?TPL简介中提到了区块容量:

[…]绑定在数据流网络中很有用,可以避免无边界内存发育出于可靠性原因,如果生产商最终可能更快地生成数据消费者无法处理…

我建议尝试使用此选项,以限制已处理项目的排队,并查看它是否有助于解决内存问题