获得许多系统内存异常

Question

我的程序使用linq查询从数据表中读取数据并将其写入本地文件。我将流和streamwriter包含在使用语句中，但我得到了许多系统内存异常。我是否应该在我的代码中调用数据表上的dispose方法？这是我能想到的唯一解决方案

我的代码：

public static async void getTrainingData(string symbol, string market)
    {
        decimal returnPct = 0, shortRating = 0, rsi = 0, mfi = 0, williamsR = 0, macd = 0, sma20 = 0, sma50 = 0, sma200 = 0;
        string path = "training.csv";
        List<Task> taskList = new List<Task>();
        int count = 0;

        try
        {
            using (Calculations calc = createCalcClass(symbol, market))
            {
                using (FileStream fs = new FileStream(path, FileMode.Append, FileAccess.Write, FileShare.Write, 4096, FileOptions.Asynchronous))
                using (TextWriter writer = new StreamWriter(fs))
                {
                    DateTime date;

                            var amexQuery = from c in calc.dailyAmexTable.AsEnumerable()
                                            orderby c.Date descending
                                            select c;

                            count = Convert.ToInt32(calc.dailyAmexAdapter.ScalarQuerySymbol(symbol));
                            for (int i = 0; i < count - 14; i++)
                            {
                                if (i != count - 15)
                                {
                                    returnPct = calc.calculateReturnPercentage(amexQuery.ElementAtOrDefault(i + 1).AdjustedClose, amexQuery.ElementAtOrDefault(i).AdjustedClose);
                                    date = amexQuery.ElementAtOrDefault(i + 1).Date;

                                    if (returnPct >= 10)
                                    {
                                        calc.calculatePctGainsLosses(14, date);
                                        shortRating = calculateRating(calc, ratingType.short_rating, date);
                                        rsi = calc.calculateRSI(14, date);
                                        mfi = calc.calculateMFI(14, date);
                                        williamsR = calc.calculateWilliamsR(14, date);
                                        macd = calc.calculateMACDDivergence(date);
                                        sma20 = calc.calculateReturnPercentage(calc.calculateSMA(20, date),
                                            calc.getSpecificValues(Calculations.valueType.Most_Recent_Close, 0, date));
                                        sma50 = calc.calculateReturnPercentage(calc.calculateSMA(50, date),
                                            calc.getSpecificValues(Calculations.valueType.Most_Recent_Close, 0, date));
                                        sma200 = calc.calculateReturnPercentage(calc.calculateSMA(200, date),
                                            calc.getSpecificValues(Calculations.valueType.Most_Recent_Close, 0, date));
                                        Task write = TextWriter.Synchronized(writer).WriteLineAsync(returnPct + "," + symbol + "," + shortRating + "," +
                                            rsi + "," + mfi + "," + williamsR + "," + macd + "," + sma20 + "," + sma50 + "," + sma200);
                                        taskList.Add(write);
                                        // add the necessary info to the training data file
                                        // stock rating, pct change, rsi, mfi, williams r, macd, 20 day sma, 50 day sma, 200 day sma
                                    }
                                }
                            }

                    await writer.FlushAsync();
                }

                // wait for all tasks to complete
                Task.WaitAll(taskList.ToArray());
                Console.WriteLine("Return percentages for " + symbol + " saved to training file.");
            }
        }
        catch (Exception ex)
        {
            Console.WriteLine(ex.Message);
        }
    }

示例输出：