Bri*_*ohl 16 sql-server sql-server-2008-r2
这是 SQL Server 2008 R2 SP2。我有2张桌子。两者都是相同的(数据和索引),除了第一个表有一个 VALUE 列 asnvarchar(max)和第二个有相同的列 as nvarchar(800)。此列包含在非聚集索引中。我还在两个表上创建了聚集索引。我还重建了索引。此列中的最大字符串长度为 650。
如果我对两个nvarchar(800)表运行相同的查询,则始终会更快,速度是原来的两倍。当然,这似乎违背了“varchar”的目的。表包含 800,000+ 行。查询应该查看大约 110,000 行(这是计划估计的)。
根据 io 统计数据,没有 lob 读取,所以一切似乎都在行中。执行计划是相同的,除了两个表之间的成本百分比略有不同,并且估计的行大小更大nvarchar(max)(91 字节 vs 63 字节)。读取次数也几乎相同。
为什么会有差异?
====== 架构 ======
CREATE TABLE [dbo].[table1](
[ID] [bigint] IDENTITY(1,1) NOT NULL,
[ProductID] [bigint] NOT NULL,
[ProductSkeletonID] [bigint] NOT NULL,
[Value] [nvarchar](max) NOT NULL,
[IsKeywordSearchable] [bit] NULL,
[ValueInteger] [bigint] NULL,
[ValueDecimal] [decimal](18, 2) NULL,
[ValueDate] [datetime] NULL,
[TypeOfData] [nvarchar](20) NOT NULL,
CONSTRAINT [PK_table1] PRIMARY KEY CLUSTERED
(
[ID] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY] TEXTIMAGE_ON [PRIMARY]
CREATE NONCLUSTERED INDEX [IX_table1_productskeletonid] ON [dbo].[table1]
(
[ProductSkeletonID] ASC
)
INCLUDE ( [ProductID],
[Value]) WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
CREATE TABLE [dbo].[table2](
[ID] [bigint] IDENTITY(1,1) NOT NULL,
[ProductID] [bigint] NOT NULL,
[ProductSkeletonID] [bigint] NOT NULL,
[Value] [nvarchar](800) NOT NULL,
[IsKeywordSearchable] [bit] NULL,
[ValueInteger] [bigint] NULL,
[ValueDecimal] [decimal](18, 2) NULL,
[ValueDate] [datetime] NULL,
[TypeOfData] [nvarchar](20) NOT NULL,
CONSTRAINT [PK_table2] PRIMARY KEY CLUSTERED
(
[ID] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY]
CREATE NONCLUSTERED INDEX [IX_table2_productskeletonid] ON [dbo].[table2]
(
[ProductSkeletonID] ASC
)
INCLUDE ( [ProductID],
[Value]) WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
CREATE TABLE [dbo].[table_results](
[SearchID] [bigint] NOT NULL,
[RowNbr] [int] NOT NULL,
[ProductID] [bigint] NOT NULL,
[PermissionList] [varchar](250) NULL,
[SearchWeight] [int] NULL,
CONSTRAINT [PK_table_results] PRIMARY KEY NONCLUSTERED
(
[SearchID] ASC,
[RowNbr] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY]
CREATE NONCLUSTERED INDEX [IX_table_results_SearchID] ON [dbo].[cart_product_searches_results]
(
[SearchID] ASC
)
INCLUDE ( [ProductID]) WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
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====== Table1查询======
SELECT cppev.ProductSkeletonID, cppev.Value, COUNT(*) AS Value FROM table1 cppev
JOIN search_results cpsr ON cppev.ProductID = cpsr.ProductID AND cpsr.SearchID = 227568
WHERE cppev.ProductSkeletonID in (3191, 3160, 3158, 3201)
GROUP BY cppev.ProductSkeletonID, cppev.Value
Table 'Worktable'. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
Table 'table1'. Scan count 4, logical reads 582, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
Table 'table_results'. Scan count 1, logical reads 82, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
SQL Server Execution Times:
CPU time = 1373 ms, elapsed time = 1576 ms.
|--Compute Scalar(DEFINE:([Expr1005]=CONVERT_IMPLICIT(int,[Expr1008],0)))
|--Stream Aggregate(GROUP BY:([cppev].[Value], [cppev].[ProductSkeletonID]) DEFINE:([Expr1008]=Count(*)))
|--Sort(ORDER BY:([cppev].[Value] ASC, [cppev].[ProductSkeletonID] ASC))
|--Hash Match(Inner Join, HASH:([cpsr].[ProductID])=([cppev].[ProductID]), RESIDUAL:([dbo].[table1].[ProductID] as [cppev].[ProductID]=[dbo].[table_results].[ProductID] as [cpsr].[ProductID]))
|--Index Seek(OBJECT:([dbo].[table_results].[IX_table_results_SearchID] AS [cpsr]), SEEK:([cpsr].[SearchID]=(227568)) ORDERED FORWARD)
|--Index Seek(OBJECT:([dbo].[table1].[IX_table1_productskeletonid] AS [cppev]), SEEK:([cppev].[ProductSkeletonID]=(3158) OR [cppev].[ProductSkeletonID]=(3160) OR [cppev].[ProductSkeletonID]=(3191) OR [cppev].[ProductSkeletonID]=(3201)) ORDERED FORWARD)
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====== Table2查询======
SELECT cppev.ProductSkeletonID, cppev.Value, COUNT(*) AS Value FROM table2 cppev
JOIN table_results cpsr ON cppev.ProductID = cpsr.ProductID AND cpsr.SearchID = 227568
WHERE cppev.ProductSkeletonID in (3191, 3160, 3158, 3201)
GROUP BY cppev.ProductSkeletonID, cppev.Value
Table 'Worktable'. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
Table 'table2'. Scan count 4, logical reads 584, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
Table 'table_results'. Scan count 1, logical reads 82, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
SQL Server Execution Times:
CPU time = 484 ms, elapsed time = 796 ms.
|--Compute Scalar(DEFINE:([Expr1005]=CONVERT_IMPLICIT(int,[Expr1008],0)))
|--Stream Aggregate(GROUP BY:([cppev].[Value], [cppev].[ProductSkeletonID]) DEFINE:([Expr1008]=Count(*)))
|--Sort(ORDER BY:([cppev].[Value] ASC, [cppev].[ProductSkeletonID] ASC))
|--Hash Match(Inner Join, HASH:([cpsr].[ProductID])=([cppev].[ProductID]), RESIDUAL:([auctori_core_v40_D].[dbo].[table2].[ProductID] as [cppev].[ProductID]= [dbo].[table2].[ProductID] as [cpsr].[ProductID]))
|--Index Seek(OBJECT:([dbo].[table_results].[IX_table_results_SearchID] AS [cpsr]), SEEK:([cpsr].[SearchID]=(227568)) ORDERED FORWARD)
|--Index Seek(OBJECT:([dbo].[table2].[IX_table2_productskeletonid] AS [cppev]), SEEK:([cppev].[ProductSkeletonID]=(3158) OR [cppev].[ProductSkeletonID]=(3160) OR [cppev].[ProductSkeletonID]=(3191) OR [cppev].[ProductSkeletonID]=(3201)) ORDERED FORWARD)
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Mar*_*ith 14
您会看到使用MAX类型的成本开销。
虽然NVARCHAR(MAX)与NVARCHAR(n)TSQL 中的相同并且可以存储在行中,但它由存储引擎单独处理,因为它可以被推送到行外。当离行时,它是一个LOB_DATA分配单元,而不是ROW_OVERFLOW_DATA分配单元,我们可以从您的观察中假设这会带来开销。
您可以看到这两种类型的内部存储方式不同,只需稍加DBCC PAGE 探索即可。Mark Rasmussen发布了示例页面转储,显示了Varchar、Varbinary 等 (MAX) 类型的 LOB 指针的大小是多少?
我们可以假设GROUP BY是MAX列上导致您的情况出现性能差异。我没有测试过某种MAX类型的其他操作,但这样做可能会很有趣,看看是否会看到类似的结果。