C# 实体框架查询性能与原始SQL执行不同

我有一个关于实体框架查询执行性能的问题

模式：

我有这样一个表结构：

CREATE TABLE [dbo].[DataLogger]
(
    [ID] [bigint] IDENTITY(1,1) NOT NULL,
    [ProjectID] [bigint] NULL,
    CONSTRAINT [PrimaryKey1] PRIMARY KEY CLUSTERED ( [ID] ASC )
)

CREATE TABLE [dbo].[DCDistributionBox]
(
    [ID] [bigint] IDENTITY(1,1) NOT NULL,
    [DataLoggerID] [bigint] NOT NULL,
    CONSTRAINT [PrimaryKey2] PRIMARY KEY CLUSTERED ( [ID] ASC )
)

ALTER TABLE [dbo].[DCDistributionBox]
    ADD CONSTRAINT [FK_DCDistributionBox_DataLogger] 
    FOREIGN KEY([DataLoggerID]) REFERENCES [dbo].[DataLogger] ([ID])

CREATE TABLE [dbo].[DCString] 
(
    [ID] [bigint] IDENTITY(1,1) NOT NULL,
    [DCDistributionBoxID] [bigint] NOT NULL,
    [CurrentMPP] [decimal](18, 2) NULL,
    CONSTRAINT [PrimaryKey3] PRIMARY KEY CLUSTERED ( [ID] ASC )
)

ALTER TABLE [dbo].[DCString]
    ADD CONSTRAINT [FK_DCString_DCDistributionBox] 
    FOREIGN KEY([DCDistributionBoxID]) REFERENCES [dbo].[DCDistributionBox] ([ID])

CREATE TABLE [dbo].[StringData]
(
    [DCStringID] [bigint] NOT NULL,
    [TimeStamp] [datetime] NOT NULL,
    [DCCurrent] [decimal](18, 2) NULL,
    CONSTRAINT [PrimaryKey4] PRIMARY KEY CLUSTERED ( [TimeStamp] DESC, [DCStringID] ASC)
)

CREATE NONCLUSTERED INDEX [TimeStamp_DCCurrent-NonClusteredIndex] 
ON [dbo].[StringData] ([DCStringID] ASC, [TimeStamp] ASC)
INCLUDE ([DCCurrent])

DECLARE @p__linq__4 DATETIME = 0;
DECLARE @p__linq__3 DATETIME = 0;
DECLARE @p__linq__5 INT = 15;
DECLARE @p__linq__6 INT = 15;
DECLARE @p__linq__0 BIGINT = 20827;
DECLARE @p__linq__1 DATETIME = '06.02.2016 00:00:00';
DECLARE @p__linq__2 DATETIME = '07.02.2016 00:00:00';

SELECT 
1 AS [C1], 
[GroupBy1].[K1] AS [C2], 
[GroupBy1].[A1] AS [C3], 
[GroupBy1].[A2] AS [C4], 
[GroupBy1].[A3] AS [C5], 
[GroupBy1].[A4] AS [C6]
FROM ( SELECT 
    [Project1].[K1] AS [K1], 
    MIN([Project1].[A1]) AS [A1], 
    MAX([Project1].[A2]) AS [A2], 
    AVG([Project1].[A3]) AS [A3], 
    STDEVP([Project1].[A4]) AS [A4]
    FROM ( SELECT 
        DATEADD (minute, ((DATEDIFF (minute, @p__linq__4, [Project1].[TimeStamp])) / @p__linq__5) * @p__linq__6, @p__linq__3) AS [K1], 
        [Project1].[C1] AS [A1], 
        [Project1].[C1] AS [A2], 
        [Project1].[C1] AS [A3], 
        [Project1].[C1] AS [A4]
        FROM ( SELECT 
            [Extent1].[TimeStamp] AS [TimeStamp], 
            [Extent1].[DCCurrent] / [Extent2].[CurrentMPP] AS [C1]
            FROM    [dbo].[StringData] AS [Extent1]
            INNER JOIN [dbo].[DCString] AS [Extent2] ON [Extent1].[DCStringID] = [Extent2].[ID]
            INNER JOIN [dbo].[DCDistributionBox] AS [Extent3] ON [Extent2].[DCDistributionBoxID] = [Extent3].[ID]
            INNER JOIN [dbo].[DataLogger] AS [Extent4] ON [Extent3].[DataLoggerID] = [Extent4].[ID]
            WHERE (([Extent4].[ProjectID] = @p__linq__0) OR (([Extent4].[ProjectID] IS NULL) AND (@p__linq__0 IS NULL))) AND ([Extent1].[TimeStamp] >= @p__linq__1) AND ([Extent1].[TimeStamp] < @p__linq__2)
        )  AS [Project1]
    )  AS [Project1]
    GROUP BY [K1]
)  AS [GroupBy1]

modelContext.Configuration.UseDatabaseNullSemantics = true;

外键上也存在标准索引（出于空间原因，我不想将它们全部列出）

[StringData]

表as具有以下存储统计信息：

• 数据空间：26901.86 MB
• 行数：131827749
• 分区：正确
• 分区计数：62

用法：

现在，我想对

[StringData]

表中的数据进行分组，并进行一些聚合

我创建了一个实体框架查询（可以找到查询的详细信息）：

问题：

为什么实体框架查询执行如此缓慢？结果行数非常低，原始SQL查询显示了非常快的性能

更新1：

我注意到这不是元上下文或模型创建延迟。之前在同一个模型实例上执行了一些其他查询，性能良好

更新2（与@x0007me的答案相关）：

感谢您的提示，但可以通过如下更改模型设置来消除此问题：

CREATE TABLE [dbo].[DataLogger]
(
    [ID] [bigint] IDENTITY(1,1) NOT NULL,
    [ProjectID] [bigint] NULL,
    CONSTRAINT [PrimaryKey1] PRIMARY KEY CLUSTERED ( [ID] ASC )
)

CREATE TABLE [dbo].[DCDistributionBox]
(
    [ID] [bigint] IDENTITY(1,1) NOT NULL,
    [DataLoggerID] [bigint] NOT NULL,
    CONSTRAINT [PrimaryKey2] PRIMARY KEY CLUSTERED ( [ID] ASC )
)

ALTER TABLE [dbo].[DCDistributionBox]
    ADD CONSTRAINT [FK_DCDistributionBox_DataLogger] 
    FOREIGN KEY([DataLoggerID]) REFERENCES [dbo].[DataLogger] ([ID])

CREATE TABLE [dbo].[DCString] 
(
    [ID] [bigint] IDENTITY(1,1) NOT NULL,
    [DCDistributionBoxID] [bigint] NOT NULL,
    [CurrentMPP] [decimal](18, 2) NULL,
    CONSTRAINT [PrimaryKey3] PRIMARY KEY CLUSTERED ( [ID] ASC )
)

ALTER TABLE [dbo].[DCString]
    ADD CONSTRAINT [FK_DCString_DCDistributionBox] 
    FOREIGN KEY([DCDistributionBoxID]) REFERENCES [dbo].[DCDistributionBox] ([ID])

CREATE TABLE [dbo].[StringData]
(
    [DCStringID] [bigint] NOT NULL,
    [TimeStamp] [datetime] NOT NULL,
    [DCCurrent] [decimal](18, 2) NULL,
    CONSTRAINT [PrimaryKey4] PRIMARY KEY CLUSTERED ( [TimeStamp] DESC, [DCStringID] ASC)
)

CREATE NONCLUSTERED INDEX [TimeStamp_DCCurrent-NonClusteredIndex] 
ON [dbo].[StringData] ([DCStringID] ASC, [TimeStamp] ASC)
INCLUDE ([DCCurrent])

DECLARE @p__linq__4 DATETIME = 0;
DECLARE @p__linq__3 DATETIME = 0;
DECLARE @p__linq__5 INT = 15;
DECLARE @p__linq__6 INT = 15;
DECLARE @p__linq__0 BIGINT = 20827;
DECLARE @p__linq__1 DATETIME = '06.02.2016 00:00:00';
DECLARE @p__linq__2 DATETIME = '07.02.2016 00:00:00';

SELECT 
1 AS [C1], 
[GroupBy1].[K1] AS [C2], 
[GroupBy1].[A1] AS [C3], 
[GroupBy1].[A2] AS [C4], 
[GroupBy1].[A3] AS [C5], 
[GroupBy1].[A4] AS [C6]
FROM ( SELECT 
    [Project1].[K1] AS [K1], 
    MIN([Project1].[A1]) AS [A1], 
    MAX([Project1].[A2]) AS [A2], 
    AVG([Project1].[A3]) AS [A3], 
    STDEVP([Project1].[A4]) AS [A4]
    FROM ( SELECT 
        DATEADD (minute, ((DATEDIFF (minute, @p__linq__4, [Project1].[TimeStamp])) / @p__linq__5) * @p__linq__6, @p__linq__3) AS [K1], 
        [Project1].[C1] AS [A1], 
        [Project1].[C1] AS [A2], 
        [Project1].[C1] AS [A3], 
        [Project1].[C1] AS [A4]
        FROM ( SELECT 
            [Extent1].[TimeStamp] AS [TimeStamp], 
            [Extent1].[DCCurrent] / [Extent2].[CurrentMPP] AS [C1]
            FROM    [dbo].[StringData] AS [Extent1]
            INNER JOIN [dbo].[DCString] AS [Extent2] ON [Extent1].[DCStringID] = [Extent2].[ID]
            INNER JOIN [dbo].[DCDistributionBox] AS [Extent3] ON [Extent2].[DCDistributionBoxID] = [Extent3].[ID]
            INNER JOIN [dbo].[DataLogger] AS [Extent4] ON [Extent3].[DataLoggerID] = [Extent4].[ID]
            WHERE (([Extent4].[ProjectID] = @p__linq__0) OR (([Extent4].[ProjectID] IS NULL) AND (@p__linq__0 IS NULL))) AND ([Extent1].[TimeStamp] >= @p__linq__1) AND ([Extent1].[TimeStamp] < @p__linq__2)
        )  AS [Project1]
    )  AS [Project1]
    GROUP BY [K1]
)  AS [GroupBy1]

modelContext.Configuration.UseDatabaseNullSemantics = true;

EF生成的SQL现在是：

SELECT 
1 AS [C1], 
[GroupBy1].[K1] AS [C2], 
[GroupBy1].[A1] AS [C3], 
[GroupBy1].[A2] AS [C4], 
[GroupBy1].[A3] AS [C5], 
[GroupBy1].[A4] AS [C6]
FROM ( SELECT 
    [Project1].[K1] AS [K1], 
    MIN([Project1].[A1]) AS [A1], 
    MAX([Project1].[A2]) AS [A2], 
    AVG([Project1].[A3]) AS [A3], 
    STDEVP([Project1].[A4]) AS [A4]
    FROM ( SELECT 
        DATEADD (minute, ((DATEDIFF (minute, @p__linq__4, [Project1].[TimeStamp])) / @p__linq__5) * @p__linq__6, @p__linq__3) AS [K1], 
        [Project1].[C1] AS [A1], 
        [Project1].[C1] AS [A2], 
        [Project1].[C1] AS [A3], 
        [Project1].[C1] AS [A4]
        FROM ( SELECT 
            [Extent1].[TimeStamp] AS [TimeStamp], 
            [Extent1].[DCCurrent] / [Extent2].[CurrentMPP] AS [C1]
            FROM    [dbo].[StringData] AS [Extent1]
            INNER JOIN [dbo].[DCString] AS [Extent2] ON [Extent1].[DCStringID] = [Extent2].[ID]
            INNER JOIN [dbo].[DCDistributionBox] AS [Extent3] ON [Extent2].[DCDistributionBoxID] = [Extent3].[ID]
            INNER JOIN [dbo].[DataLogger] AS [Extent4] ON [Extent3].[DataLoggerID] = [Extent4].[ID]
            WHERE ([Extent4].[ProjectID] = @p__linq__0) AND ([Extent1].[TimeStamp] >= @p__linq__1) AND ([Extent1].[TimeStamp] < @p__linq__2)
        )  AS [Project1]
    )  AS [Project1]
    GROUP BY [K1]
)  AS [GroupBy1]

因此，两个查询的执行时间相同

更新4（与@bubi的答案相关）：

我尝试运行由EF生成的查询，如您所述：

int result = model.Database.ExecuteSqlCommand(@"SELECT 
    1 AS [C1], 
    [GroupBy1].[K1] AS [C2], 
    [GroupBy1].[A1] AS [C3], 
    [GroupBy1].[A2] AS [C4], 
    [GroupBy1].[A3] AS [C5], 
    [GroupBy1].[A4] AS [C6]
    FROM ( SELECT 
        [Project1].[K1] AS [K1], 
        MIN([Project1].[A1]) AS [A1], 
        MAX([Project1].[A2]) AS [A2], 
        AVG([Project1].[A3]) AS [A3], 
        STDEVP([Project1].[A4]) AS [A4]
        FROM ( SELECT 
            DATEADD (minute, ((DATEDIFF (minute, 0, [Project1].[TimeStamp])) / @p__linq__5) * @p__linq__6, 0) AS [K1], 
            [Project1].[C1] AS [A1], 
            [Project1].[C1] AS [A2], 
            [Project1].[C1] AS [A3], 
            [Project1].[C1] AS [A4]
            FROM ( SELECT 
                [Extent1].[TimeStamp] AS [TimeStamp], 
                [Extent1].[DCCurrent] / [Extent2].[CurrentMPP] AS [C1]
                FROM    [dbo].[StringData] AS [Extent1]
                INNER JOIN [dbo].[DCString] AS [Extent2] ON [Extent1].[DCStringID] = [Extent2].[ID]
                INNER JOIN [dbo].[DCDistributionBox] AS [Extent3] ON [Extent2].[DCDistributionBoxID] = [Extent3].[ID]
                INNER JOIN [dbo].[DataLogger] AS [Extent4] ON [Extent3].[DataLoggerID] = [Extent4].[ID]
                WHERE ([Extent4].[ProjectID] = @p__linq__0) AND ([Extent1].[TimeStamp] >= @p__linq__1) AND ([Extent1].[TimeStamp] < @p__linq__2)
            )  AS [Project1]
        )  AS [Project1]
        GROUP BY [K1]
    )  AS [GroupBy1]",
    new SqlParameter("p__linq__0", 20827),
    new SqlParameter("p__linq__1", fromDate),
    new SqlParameter("p__linq__2", tillDate),
    new SqlParameter("p__linq__5", 15),
    new SqlParameter("p__linq__6", 15));

第0次运行纯EF:00:00:12.6460624

第1次运行纯EF:00:00:11.0258393

第2次运行纯EF:00:00:08.4171044

我现在使用EF生成的SQL作为SQL查询：

for (int i = 0; i < 3; i++)
{
    DateTime begin = DateTime.UtcNow;
    int result = model.Database.ExecuteSqlCommand(@"SELECT 
        1 AS [C1], 
        [GroupBy1].[K1] AS [TimeStamp15Minutes], 
        [GroupBy1].[A1] AS [C2], 
        [GroupBy1].[A2] AS [C3], 
        [GroupBy1].[A3] AS [C4], 
        [GroupBy1].[A4] AS [C5]
        FROM ( SELECT 
            [Project1].[TimeStamp15Minutes] AS [K1], 
            MIN([Project1].[C1]) AS [A1], 
            MAX([Project1].[C1]) AS [A2], 
            AVG([Project1].[C1]) AS [A3], 
            STDEVP([Project1].[C1]) AS [A4]
            FROM ( SELECT 
                [Extent1].[TimeStamp15Minutes] AS [TimeStamp15Minutes], 
                [Extent1].[DCCurrent] / [Extent2].[CurrentMPP] AS [C1]
                FROM    [dbo].[StringData] AS [Extent1]
                INNER JOIN [dbo].[DCString] AS [Extent2] ON [Extent1].[DCStringID] = [Extent2].[ID]
                INNER JOIN [dbo].[DCDistributionBox] AS [Extent3] ON [Extent2].[DCDistributionBoxID] = [Extent3].[ID]
                INNER JOIN [dbo].[DataLogger] AS [Extent4] ON [Extent3].[DataLoggerID] = [Extent4].[ID]
                WHERE ([Extent4].[ProjectID] = @p__linq__0) AND ([Extent1].[TimeStamp15Minutes] >= @p__linq__1) AND ([Extent1].[TimeStamp15Minutes] < @p__linq__2)
            )  AS [Project1]
            GROUP BY [Project1].[TimeStamp15Minutes]
        )  AS [GroupBy1];",
    new SqlParameter("p__linq__0", 20827),
    new SqlParameter("p__linq__1", fromDate),
    new SqlParameter("p__linq__2", tillDate));

    TimeSpan excecutionTimeSpan = DateTime.UtcNow - begin;
    Debug.WriteLine("{0}th run: {1}", i, excecutionTimeSpan.ToString());
}

第0次重新编译运行：00:00:00.8260932

第1次重新编译运行：00:00:00.9139730

2重新编译后运行：00:00:01.0680665

SSMS中未执行相同的SQL查询（无需重新编译）：

00:00:01.105

SSMS中执行了相同的SQL查询（重新编译）：

00:00:00.902

---

我希望这些都是您需要的值。

数据库引擎根据调用方式确定每个查询的计划。在EF Linq查询的情况下，计划是以这样一种方式准备的，即每个输入参数都被视为未知参数（因为您不知道接下来会发生什么）。在实际查询中，所有参数都作为查询的一部分，因此它将在不同于参数化计划的计划下运行。我立即看到的一个受影响的部分是

…（@p__linq__0为空）

这是错误的，因为p_linq_0=20827并且不是空的，所以您的WHERE的前半部分是错误的，不需要再查看。在LINQ查询的情况下，DB不知道会发生什么，所以无论如何都会对所有内容进行评估

---

您需要查看是否可以使用索引或其他技术来加快运行速度。

当EF运行查询时，它会将其包装并使用sp_executesql运行，这意味着执行计划将缓存在存储过程执行计划缓存中。由于原始sql语句与SP版本的执行计划构建方式不同（参数嗅探等），两者可能有所不同

在运行EF（sp包装）版本时，SQL server很可能使用更通用的执行计划，该计划覆盖的时间戳范围比实际传入的值更广

也就是说，为了减少SQL server尝试散列连接等“有趣”操作的机会，我首先要做的是：

1） 索引where子句和联接中使用的列

create index ix_DataLogger_ProjectID on DataLogger (ProjectID);
create index ix_DCDistributionBox_DataLoggerID on DCDistributionBox (DataLoggerID);
create index ix_DCString_DCDistributionBoxID on DCString (DCDistributionBoxID);

---

2） 在Linq查询中执行显式连接以消除或ProductID为null的部分

我知道我在这里有点晚了，但是由于我参与了相关查询的构建，我觉得有必要采取一些措施

我在LINQtoEntities查询中看到的一般问题是，我们构建它们的典型方式引入了不必要的参数，这可能会影响缓存数据库查询计划（所谓的SQLServer参数嗅探问题）

让我们通过表达式查看查询组

d => DbFunctions.AddMinutes(DateTime.MinValue, DbFunctions.DiffMinutes(DateTime.MinValue, d.TimeStamp) / minuteInterval * minuteInterval)

由于

minuteInterval

是一个变量（即非常数），因此它引入了一个参数。与

DateTime.MinValue

相同（请注意，基本类型公开了与常量s类似的内容，但对于

DateTime

、

decimal

等，它们是静态只读字段，这在表达式内部的处理方式上存在很大差异）

但不管它在CLR系统中是如何表示的，

DateTime.MinValue

在逻辑上是一个常量。那么

minuteInterval

呢，这取决于您的使用情况

我解决这个问题的尝试是消除与该表达式相关的所有参数。因为我们不能用编译器生成的表达式来实现这一点，所以我们需要使用

System.Linq.Expressions

手动构建它。后者并不直观，但幸运的是我们可以使用混合方法

首先，我们需要一个帮助器方法，它允许我们替换表达式参数：

public static class ExpressionUtils
{
    public static Expression ReplaceParemeter(this Expression expression, ParameterExpression source, Expression target)
    {
        return new ParameterReplacer { Source = source, Target = target }.Visit(expression);
    }

    class ParameterReplacer : ExpressionVisitor
    {
        public ParameterExpression Source;
        public Expression Target;
        protected override Expression VisitParameter(ParameterExpression node)
        {
            return node == Source ? Target : base.VisitParameter(node);
        }
    }
}

现在我们有了所需要的一切。让我们将逻辑封装在自定义方法中：

public static class QueryableUtils
{
    public static IQueryable<IGrouping<DateTime, T>> GroupBy<T>(this IQueryable<T> source, Expression<Func<T, DateTime>> dateSelector, int minuteInterval)
    {
        Expression<Func<DateTime, DateTime, int, DateTime>> expr = (date, baseDate, interval) =>
            DbFunctions.AddMinutes(baseDate, DbFunctions.DiffMinutes(baseDate, date) / interval).Value;
        var selector = Expression.Lambda<Func<T, DateTime>>(
            expr.Body
            .ReplaceParemeter(expr.Parameters[0], dateSelector.Body)
            .ReplaceParemeter(expr.Parameters[1], Expression.Constant(DateTime.MinValue))
            .ReplaceParemeter(expr.Parameters[2], Expression.Constant(minuteInterval))
            , dateSelector.Parameters[0]
        );
        return source.GroupBy(selector);
    }
}

与

生成的SQL查询如下所示（对于

minuteInterval=15

）：

选择
1作为[C1]，
[GroupBy1][K1]作为[C2]，
[GroupBy1][A1]作为[C3]，
[GroupBy1][A2]作为[C4]，
[GroupBy1][A3]作为[C5]，
[GroupBy1][A4]作为[C6]
从（选择
[Project1][K1]作为[K1]，
最小值（[Project1][A1]）为[A1]，
最大值（[Project1][A2]）为[A2]，
平均值（[Project1][A3]）为[A3]，
STDEVP（[Project1][A4]）作为[A4]
从（选择
DATEADD（分钟）（DATEDIFF（分钟，转换为datetime2，'0001-01-01 00:00:00.0000000'，121），[Project1]。[TimeStamp
d => DbFunctions.AddMinutes(DateTime.MinValue, DbFunctions.DiffMinutes(DateTime.MinValue, d.TimeStamp) / minuteInterval * minuteInterval)

public static class ExpressionUtils
{
    public static Expression ReplaceParemeter(this Expression expression, ParameterExpression source, Expression target)
    {
        return new ParameterReplacer { Source = source, Target = target }.Visit(expression);
    }

    class ParameterReplacer : ExpressionVisitor
    {
        public ParameterExpression Source;
        public Expression Target;
        protected override Expression VisitParameter(ParameterExpression node)
        {
            return node == Source ? Target : base.VisitParameter(node);
        }
    }
}

public static class QueryableUtils
{
    public static IQueryable<IGrouping<DateTime, T>> GroupBy<T>(this IQueryable<T> source, Expression<Func<T, DateTime>> dateSelector, int minuteInterval)
    {
        Expression<Func<DateTime, DateTime, int, DateTime>> expr = (date, baseDate, interval) =>
            DbFunctions.AddMinutes(baseDate, DbFunctions.DiffMinutes(baseDate, date) / interval).Value;
        var selector = Expression.Lambda<Func<T, DateTime>>(
            expr.Body
            .ReplaceParemeter(expr.Parameters[0], dateSelector.Body)
            .ReplaceParemeter(expr.Parameters[1], Expression.Constant(DateTime.MinValue))
            .ReplaceParemeter(expr.Parameters[2], Expression.Constant(minuteInterval))
            , dateSelector.Parameters[0]
        );
        return source.GroupBy(selector);
    }
}

.GroupBy(d => DbFunctions.AddMinutes(DateTime.MinValue, DbFunctions.DiffMinutes(DateTime.MinValue, d.TimeStamp) / minuteInterval * minuteInterval))

.GroupBy(d => d.TimeStamp, minuteInterval * minuteInterval)

SELECT 
    1 AS [C1], 
    [GroupBy1].[K1] AS [C2], 
    [GroupBy1].[A1] AS [C3], 
    [GroupBy1].[A2] AS [C4], 
    [GroupBy1].[A3] AS [C5], 
    [GroupBy1].[A4] AS [C6]
    FROM ( SELECT 
        [Project1].[K1] AS [K1], 
        MIN([Project1].[A1]) AS [A1], 
        MAX([Project1].[A2]) AS [A2], 
        AVG([Project1].[A3]) AS [A3], 
        STDEVP([Project1].[A4]) AS [A4]
        FROM ( SELECT 
            DATEADD (minute, (DATEDIFF (minute, convert(datetime2, '0001-01-01 00:00:00.0000000', 121), [Project1].[TimeStamp])) / 225, convert(datetime2, '0001-01-01 00:00:00.0000000', 121)) AS [K1], 
            [Project1].[C1] AS [A1], 
            [Project1].[C1] AS [A2], 
            [Project1].[C1] AS [A3], 
            [Project1].[C1] AS [A4]
            FROM ( SELECT 
                [Extent1].[TimeStamp] AS [TimeStamp], 
                [Extent1].[DCCurrent] / [Extent2].[CurrentMPP] AS [C1]
                FROM    [dbo].[StringDatas] AS [Extent1]
                INNER JOIN [dbo].[DCStrings] AS [Extent2] ON [Extent1].[DCStringID] = [Extent2].[ID]
                INNER JOIN [dbo].[DCDistributionBoxes] AS [Extent3] ON [Extent2].[DCDistributionBoxID] = [Extent3].[ID]
                INNER JOIN [dbo].[DataLoggers] AS [Extent4] ON [Extent3].[DataLoggerID] = [Extent4].[ID]
                WHERE ([Extent4].[ProjectID] = @p__linq__0) AND ([Extent1].[TimeStamp] >= @p__linq__1) AND ([Extent1].[TimeStamp] < @p__linq__2)
            )  AS [Project1]
        )  AS [Project1]
        GROUP BY [K1]
    )  AS [GroupBy1]