我正在處理機器返回的數據。該機器通常用於大農場,它將採集不同深度的每個點的數據並使用不同的設備。與大量數據嵌套的foreach導致內存不足exe123
每場可容納70-100字段和每個字段包含約10萬條數據
在這裏,我需要處理每一個數據和應用基於客戶需求的一些計算。
我需要首先遍歷農場,然後農場下的字段,然後每個農場使用的設備然後根據深度記錄每個設備。所以最後我希望我做了大約10億次的迭代。 我的代碼看起來像下面
public async void MigrateData()
{
masterData = await CatalogService.ExportMasterData(AppDataModel.Catalog, this.UserId);
foreach (var fieldItem in masterData.Fields)
{
var fieldReferenceId = fieldItem.ReferenceId;
dynamic loggedData = AppDataModel.Documents.LoggedData.Where(data => data.FieldId == fieldReferenceId);
dynamic fieldDbMappingData = fieldItem;
foreach (var data in loggedData)
{
yieldMaster.OperationalLogModalResponse = await YieldDataMigrationService.AddOperationalLogs("loggedDataDescription");
yieldMaster.OperationalLogDataModelResponse = await YieldDataMigrationService.AddOperationalLogData(fieldDbMappingData, yieldMaster.OperationalLogModalResponse);
FetchContentData(data);
}
}
}
private async void FetchContentData(LoggedData data)
{
foreach (var opdata in data.OperationData)
{
var filteredList = AggregateDataBasedOnFilter(opdata);
int count = filteredList.Count;
totalRecordCount += count;
for (int i = 1; i <= count; i = i + 1000)
{
var response = await YieldDataMigrationService.AddYiledData(filteredList.GetRange(i, i + 1000 >= count ? count - i : 1000));
}
}
//Filter data based on timestamp values , get the first data in 5 seconds interval
System.GC.Collect();
}
private dynamic AggregateDataBasedOnFilter(OperationData opdata)
{
List<dynamic> listSpacialRecords = new List<dynamic>();
IEnumerable<SpatialRecord> spacialRecords = opdata.GetSpatialRecords();
spacialRecords = GetAggregateBasedOnTimeStamb(spacialRecords);
Nullable<Guid> productid;
for (int depth = 0; depth <= opdata.MaxDepth; depth++)
{
IEnumerable<DeviceElementUse> deviceElementUses = opdata.GetDeviceElementUses(depth);
StevProduct productDbMappingData = masterData.Products.Where(product => product.ReferenceId == opdata.ProductId).FirstOrDefault();
if (productDbMappingData == null)
{
productid = null;
}
else
{
productid = productDbMappingData.Id;
}
foreach (var deviceElement in deviceElementUses)
{
List<dynamic> dvList = new List<dynamic>();
IEnumerable<WorkingData> workingData = deviceElement.GetWorkingDatas();
//foreach (var spacerecord in spacialRecords)
Parallel.ForEach(spacialRecords, (spacerecord) =>
{
List<MeterValue> dat = new List<MeterValue>();
var latitude = ((AgGateway.ADAPT.ApplicationDataModel.Shapes.Point)spacerecord.Geometry).Y;
var longitude = ((AgGateway.ADAPT.ApplicationDataModel.Shapes.Point)spacerecord.Geometry).X;
var timeStamp = spacerecord.Timestamp;
//Parallel.ForEach(workingData, (wdItem) =>
foreach (var wdItem in workingData)
{
RepresentationValue spaceMeteredValue = spacerecord.GetMeterValue(wdItem);
if (spaceMeteredValue != null && wdItem.Representation != null)
{
//row[wdItem.Representation.Code] = meteredValue.Value.Value;
var objMeterValue = new MeterValue();
objMeterValue.key = wdItem.Representation.Code;
objMeterValue.value = spaceMeteredValue.Designator != null ? Convert.ToString(spaceMeteredValue.Designator) : "";
dat.Add(objMeterValue);
}
}
var newSpacialvalue = new
{
operationLogDataId = yieldMaster.OperationalLogDataModelResponse.Id,
order = deviceElement.Order,
totalDistanceTravelled = deviceElement.TotalDistanceTravelled,
totalElapsedTime = deviceElement.TotalElapsedTime,
uploadedOn = DateTime.Now.ToUniversalTime(),
collectedOn = timeStamp.ToUniversalTime(),
cropId = "8296e610-c055-11e7-851e-ad7650a5f99c",
productId = productid,
latitude = latitude,
longitude = longitude,
deviceConfigurationId = deviceElement.DeviceConfigurationId,
operationDataId = deviceElement.OperationDataId,
spatialRecords = dat,
depth = depth,
timeStamp = timeStamp,
totaldata = totalRecordCount
};
lock (listSpacialRecords)
{
listSpacialRecords.Add(newSpacialvalue);
}
});
}
}
listSpacialRecords = listSpacialRecords
.Skip(1)
.Aggregate(
listSpacialRecords.Take(1).ToList(),
(a, x) =>
{
if (x.timeStamp.Subtract(a.Last().timeStamp).TotalSeconds >= 10.0)
{
a.Add(x);
}
return a;
});
GC.Collect();
return listSpacialRecords;
}
我真實的情景比這更復雜。它有很多foreach
和計算。整個過程運行超過30分鐘。但是在我之間我正在擺脫內存 的異常。不知道如何處理這麼龐大的數據。
任何人都有比嵌套的foreach更好的方法?或者避免內存不足的解決方案?
注意:我已將每個外觀都移動到單獨的功能中,但仍顯示內存不足錯誤。另外我有一個本地列表,它處理邏輯部分計算的數據。本地列表它不是全局對象
跳過並處理批次? –
你爲什麼要對'foreach(FieldData中的var字段)'進行三次**調用? – stuartd
@stuartd對不起,這是一個錯字。編輯 –