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我在一個asp.net mvc核心1.1.0項目中使用EF核心，並有一個相當複雜的查詢。EF核心多個左連接
_context
.Profiles
.Include(p => p.Blog)
.ThenInclude(b => b.Network)
.Include(p => p.Blog)
.ThenInclude(i => i.AgeDistributions)
.ThenInclude(i => i.AgeRange)
.Include(p => p.Blog)
.ThenInclude(b => b.GenderDistributions)
.Include(p => p.Instagram)
.ThenInclude(i => i.Network)
.Include(p => p.Instagram)
.ThenInclude(i => i.AgeDistributions)
.ThenInclude(i => i.AgeRange)
.Include(p => p.Instagram)
.ThenInclude(b => b.GenderDistributions)
.Include(p => p.Youtube)
.ThenInclude(y => y.Network)
.Include(p => p.Youtube)
.ThenInclude(i => i.AgeDistributions)
.ThenInclude(i => i.AgeRange)
.Include(p => p.Youtube)
.ThenInclude(b => b.GenderDistributions)
.Include(p => p.Snapchat)
.ThenInclude(s => s.Network)
.Include(p => p.Musically)
.Include(p => p.ProfileCategories)
.ThenInclude(pc => pc.Category)
.Include(p => p.Tags)
.ThenInclude(tag => tag.Tag)
.Where(p => !p.Deleted);
每個社交平臺都可以有任何種類的統計。例如，使用具有PlatformId的基類對AgeDistributions進行建模，並且每個派生的{Platform}AgeDistribution指定導航屬性，以正確設置外鍵。
public class AgeInterval {
public int Id { get; set; }
// At most five length. -18, 18-24, ..., 65-
public string Interval { get; set; }
}
public class PlatformAgeStatistics {
public int PlatformId { get; set; }
public int IntervalId { get; set; }
public AgeInterval Interval { get; set; }
public decimal Distribution { get; set; }
}
public class InstagramAgeStatistics : PlatformAgeStatistics {
[ForeignKey("PlatformId")]
public Instagram Platform { get; set; } //
}
上面的查詢有時很長的時間（30秒後，DB執行超時），並檢查SQL讓我覺得要麼我有一個造型問題是EF不能正確判斷或EF只是次優生成SQL。結果集使用skip和take進行分頁，並且當前取10條記錄需要時間。
這是執行
SELECT -- Emitted
FROM [Profiles] AS [p]
LEFT JOIN [BlogChannels] AS [b] ON [b].[ProfileId] = [p].[Id]
LEFT JOIN [InstagramChannels] AS [i] ON [i].[ProfileId] = [p].[Id]
LEFT JOIN [YoutubeChannels] AS [y] ON [y].[ProfileId] = [p].[Id]
LEFT JOIN [BlogChannels] AS [b2] ON [b2].[ProfileId] = [p].[Id]
LEFT JOIN [InstagramChannels] AS [i2] ON [i2].[ProfileId] = [p].[Id]
LEFT JOIN [YoutubeChannels] AS [y2] ON [y2].[ProfileId] = [p].[Id]
LEFT JOIN [BlogChannels] AS [b4] ON [b4].[ProfileId] = [p].[Id]
LEFT JOIN [Networks] AS [n] ON [b4].[NetworkId] = [n].[Id]
LEFT JOIN [InstagramChannels] AS [i4] ON [i4].[ProfileId] = [p].[Id]
LEFT JOIN [Networks] AS [n0] ON [i4].[NetworkId] = [n0].[Id]
LEFT JOIN [YoutubeChannels] AS [y4] ON [y4].[ProfileId] = [p].[Id]
LEFT JOIN [Networks] AS [n1] ON [y4].[NetworkId] = [n1].[Id]
LEFT JOIN [SnapchatChannels] AS [s] ON [s].[ProfileId] = [p].[Id]
LEFT JOIN [Networks] AS [n2] ON [s].[NetworkId] = [n2].[Id]
LEFT JOIN [MusicallyChannels] AS [m] ON [m].[ProfileId] = [p].[Id]
WHERE [p].[Deleted] = 0
ORDER BY [p].[FullName], [p].[Id], [b].[Id], [i].[Id], [y].[Id], [b2].[Id], [i2].[Id], [y2].[Id]
OFFSET @__p_0 ROWS FETCH NEXT @__p_1 ROWS ONLY
第一SQL然後接着更多的查詢看起來不完全正確
SELECT [y3].[Gender], [y3].[ChannelId], [y3].[Distribution]
FROM [YoutubeGenderDistribution] AS [y3]
INNER JOIN (
SELECT DISTINCT [t7].*
FROM (
SELECT [p].[FullName], [p].[Id], [b].[Id] AS [Id0], [i].[Id] AS [Id1], [y].[Id] AS [Id2], [b2].[Id] AS [Id3], [i2].[Id] AS [Id4], [y2].[Id] AS [Id5]
FROM [Profiles] AS [p]
LEFT JOIN [BlogChannels] AS [b] ON [b].[ProfileId] = [p].[Id]
LEFT JOIN [InstagramChannels] AS [i] ON [i].[ProfileId] = [p].[Id]
LEFT JOIN [YoutubeChannels] AS [y] ON [y].[ProfileId] = [p].[Id]
LEFT JOIN [BlogChannels] AS [b2] ON [b2].[ProfileId] = [p].[Id]
LEFT JOIN [InstagramChannels] AS [i2] ON [i2].[ProfileId] = [p].[Id]
LEFT JOIN [YoutubeChannels] AS [y2] ON [y2].[ProfileId] = [p].[Id]
WHERE [p].[Deleted] = 0
ORDER BY [p].[FullName], [p].[Id], [b].[Id], [i].[Id], [y].[Id], [b2].[Id], [i2].[Id], [y2].[Id]
OFFSET @__p_0 ROWS FETCH NEXT @__p_1 ROWS ONLY
) AS [t7]
) AS [y20] ON [y3].[ChannelId] = [y20].[Id5]
ORDER BY [y20].[FullName], [y20].[Id], [y20].[Id0], [y20].[Id1], [y20].[Id2], [y20].[Id3], [y20].[Id4], [y20].[Id5]
另外一個 「看起來」 更正確
SELECT [b0].[AgeRangeId], [b0].[ChannelId], [b0].[Distribution], [a].[Id], [a].[Range]
FROM [BlogAgeDistribution] AS [b0]
INNER JOIN (
SELECT DISTINCT [t2].*
FROM (
SELECT [p].[FullName], [p].[Id], [b].[Id] AS [Id0]
FROM [Profiles] AS [p]
LEFT JOIN [BlogChannels] AS [b] ON [b].[ProfileId] = [p].[Id]
WHERE [p].[Deleted] = 0
ORDER BY [p].[FullName], [p].[Id], [b].[Id]
OFFSET @__p_0 ROWS FETCH NEXT @__p_1 ROWS ONLY
) AS [t2]
) AS [b1] ON [b0].[ChannelId] = [b1].[Id0]
LEFT JOIN [AgeRanges] AS [a] ON [b0].[AgeRangeId] = [a].[Id]
ORDER BY [b1].[FullName], [b1].[Id], [b1].[Id0]
任何想法爲什麼EF在請求統計信息時加入所有其他平臺Instagram。
謝謝！
編輯：
有趣的Age第一查詢生成與所有三個
SELECT [y0].[AgeRangeId], [y0].[ChannelId], [y0].[Distribution], [a1].[Id], [a1].[Range]
FROM [YoutubeAgeDistribution] AS [y0]
INNER JOIN (
SELECT DISTINCT [t4].*
FROM (
SELECT [p].[FullName], [p].[Id], [b].[Id] AS [Id0], [i].[Id] AS [Id1], [y].[Id] AS [Id2]
FROM [Profiles] AS [p]
LEFT JOIN [BlogChannels] AS [b] ON [b].[ProfileId] = [p].[Id]
LEFT JOIN [InstagramChannels] AS [i] ON [i].[ProfileId] = [p].[Id]
LEFT JOIN [YoutubeChannels] AS [y] ON [y].[ProfileId] = [p].[Id]
WHERE [p].[Deleted] = 0
ORDER BY [p].[FullName], [p].[Id], [b].[Id], [i].[Id], [y].[Id]
OFFSET @__p_0 ROWS FETCH NEXT @__p_1 ROWS ONLY
) AS [t4]
) AS [y1] ON [y0].[ChannelId] = [y1].[Id2]
LEFT JOIN [AgeRanges] AS [a1] ON [y0].[AgeRangeId] = [a1].[Id]
ORDER BY [y1].[FullName], [y1].[Id], [y1].[Id0], [y1].[Id1], [y1].[Id2]