.Net中EF针对大数据量查询超时的一种优化

16-01-19 来源：[db:作者]

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旧代码：
--receiptIds id集合，每次查1000左右
var mappingList = new List();
mappingList.AddRange(SettlementMappingRepository.Entities.Include(o => o.ReceiptsTo).Include(d => d.FinanceSettlement).Where(d => receiptIds.Contains(d.ReceiptIdFrom)).ToList());
mappingList.AddRange(SettlementMappingRepository.Entities.Include(o => o.ReceiptsTo).Include(d => d.FinanceSettlement).Where(d => receiptIds.Contains(d.ReceiptIdTo)).ToList());
--FinanceSettlementMapping -500w数据，9个字段
--ReceiptsTo，外键表，FinanceReceipts --800w数据，64个字段
--FinanceSettlement --200w数据，15个字段
//FinanceSettlementMapping join FinanceSettlement join FinanceReceipts 表数据越大，连接越慢，可能会超时

新代码：外键表FinanceReceipts数据单独查询
var mappingList = new List();
var settlementmapFromList = SettlementMappingRepository.Entities.Include(d => d.FinanceSettlement).Where(d => receiptIds.Contains(d.ReceiptIdFrom)).ToList();
if (settlementmapFromList.Count > 0)
{
var toreceiptIds = settlementmapFromList.Select(o => o.ReceiptIdTo).ToArray();
var toreceipts = ReceiptsRepository.Entities.Where(o => toreceiptIds.Contains(o.ReceiptId)).ToList();//查询数据到内存
foreach (var map in settlementmapFromList)//循环内存数据赋值
{
var tempreceipt = toreceipts.Where(o => o.ReceiptId == map.ReceiptIdTo).FirstOrDefault();
map.ReceiptsTo = tempreceipt;
}
}
mappingList.AddRange(settlementmapFromList);
var settlementmapToList = SettlementMappingRepository.Entities.Include(d => d.FinanceSettlement).Where(d => receiptIds.Contains(d.ReceiptIdTo)).ToList();
if (settlementmapToList.Count > 0)
{
var toreceiptIds = settlementmapToList.Select(o => o.ReceiptIdTo).ToArray();
var toreceipts = ReceiptsRepository.Entities.Where(o => toreceiptIds.Contains(o.ReceiptId)).ToList();//查询数据到内存
foreach (var map in settlementmapToList)//循环内存数据赋值
{
var tempreceipt = toreceipts.Where(o => o.ReceiptId == map.ReceiptIdTo).FirstOrDefault();
map.ReceiptsTo = tempreceipt;
}
}

mappingList.AddRange(settlementmapToList);

//1000条数据，最差的线性查询时间复杂度（1+1000）*1000/2 ,本次查询的是Id,是数字类型，如果系统用的是二叉树或其他快速查询方法，就更快，再者，查询到之后，把toreceipts 值赋给map.ReceiptsTo，只是修改了map.ReceiptsTo的指针地址，没有赋值操作，当然也是很快的，实测1000数据0.006s。

解决了大数据量表的Join查询慢的问题，能加快程序总体运行速度，因为，我们网站应用，大部分时间是耗在数据库操作上，所以能减少数据库查询时间，就能减少完成一个操作的整体运行时间。

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