多个 INSERT 语句与具有多个 VALUES 的单个 INSERT [英] Multiple INSERT statements vs. single INSERT with multiple VALUES

问题描述

我正在对使用 1000 个 INSERT 语句的性能进行比较:

INSERT INTO T_TESTS (TestId, FirstName, LastName, Age)值 ('6f3f7257-a3d8-4a78-b2e1-c9b767cfe1c1', '第一个 0', '最后一个 0', 0)INSERT INTO T_TESTS (TestId, FirstName, LastName, Age)值 ('32023304-2e55-4768-8e52-1ba589b82c8b', 'First 1', 'Last 1', 1)...INSERT INTO T_TESTS (TestId, FirstName, LastName, Age)值('f34d95a7-90b1-4558-be10-6ceacd53e4c4'、'第一个 999'、'最后一个 999'、999)

..与使用具有 1000 个值的单个 INSERT 语句相比:

INSERT INTO T_TESTS (TestId, FirstName, LastName, Age)价值观('db72b358-e9b5-4101-8d11-7d7ea3a0ae7d', '第一个 0', '最后一个 0', 0),('6a4874ab-b6a3-4aa4-8ed4-a167ab21dd3d', '第一个 1', '最后一个', 1),...('9d7f2a58-7e57-4ed4-ba54-5e9e335fb56c', '第一个 999', '最后一个 999', 999)

令我大吃一惊的是，结果与我的想法相反:

• 1000 条 INSERT 语句:290 毫秒.
• 1 个包含 1000 个值的 INSERT 语句:2800 毫秒.

该测试直接在 MSSQL Management Studio 中执行，SQL Server Profiler 用于测量(我使用 SqlClient 从 C# 代码运行它得到了类似的结果，考虑到所有 DAL 层往返，这更令人惊讶)

这是否合理或以某种方式解释?为什么，一个据称更快的方法会导致 10 倍 (!)更差的性能?

谢谢.

附加两者的执行计划:

解决方案

补充: SQL Server 2012 在这方面的性能有所提高，但似乎没有解决下面提到的具体问题.这应该 表明DeriveNormalizedGroupProperties 与过去称为

SELECT *FROM (VALUES ('Lieven1', 1),('Lieven2', 2),('Lieven3', 3)) 测试(姓名，ID)按名称排序，1/(ID - ID)

因为在编译时它可以确定 Name 列没有重复项，所以它会在运行时跳过辅助 1/(ID - ID) 表达式的排序(计划中的排序只有一个 ORDER BY 列)并且不会引发除以零错误.如果将重复项添加到表中，则排序运算符按列显示两个顺序，并引发预期错误.

I'm running a performance comparison between using 1000 INSERT statements:

INSERT INTO T_TESTS (TestId, FirstName, LastName, Age) 
   VALUES ('6f3f7257-a3d8-4a78-b2e1-c9b767cfe1c1', 'First 0', 'Last 0', 0)
INSERT INTO T_TESTS (TestId, FirstName, LastName, Age) 
   VALUES ('32023304-2e55-4768-8e52-1ba589b82c8b', 'First 1', 'Last 1', 1)
...
INSERT INTO T_TESTS (TestId, FirstName, LastName, Age) 
   VALUES ('f34d95a7-90b1-4558-be10-6ceacd53e4c4', 'First 999', 'Last 999', 999)

..versus using single INSERT statement with 1000 values:

INSERT INTO T_TESTS (TestId, FirstName, LastName, Age) 
VALUES 
('db72b358-e9b5-4101-8d11-7d7ea3a0ae7d', 'First 0', 'Last 0', 0),
('6a4874ab-b6a3-4aa4-8ed4-a167ab21dd3d', 'First 1', 'Last 1', 1),
...
('9d7f2a58-7e57-4ed4-ba54-5e9e335fb56c', 'First 999', 'Last 999', 999)

To my big surprise, the results are the opposite of what I thought:

• 1000 INSERT statements: 290 msec.
• 1 INSERT statement with 1000 VALUES: 2800 msec.

The test is executed directly in MSSQL Management Studio with SQL Server Profiler used for measurement (and I've got similar results running it from C# code using SqlClient, which is even more suprising considering all the DAL layers roundtrips)

Can this be reasonable or somehow explained? How come, a supposedly faster method results in 10 times (!) worse performance?

Thank you.

EDIT: Attaching execution plans for both:

解决方案

Addition: SQL Server 2012 shows some improved performance in this area but doesn't seem to tackle the specific issues noted below. This should apparently be fixed in the next major version after SQL Server 2012!

Your plan shows the single inserts are using parameterised procedures (possibly auto parameterised) so parse/compile time for these should be minimal.

I thought I'd look into this a bit more though so set up a loop (script) and tried adjusting the number of VALUES clauses and recording the compile time.

I then divided the compile time by the number of rows to get the average compile time per clause. The results are below

Up until 250 VALUES clauses present the compile time / number of clauses has a slight upward trend but nothing too dramatic.

But then there is a sudden change.

That section of the data is shown below.

+------+----------------+-------------+---------------+---------------+
| Rows | CachedPlanSize | CompileTime | CompileMemory | Duration/Rows |
+------+----------------+-------------+---------------+---------------+
|  245 |            528 |          41 |          2400 | 0.167346939   |
|  246 |            528 |          40 |          2416 | 0.162601626   |
|  247 |            528 |          38 |          2416 | 0.153846154   |
|  248 |            528 |          39 |          2432 | 0.157258065   |
|  249 |            528 |          39 |          2432 | 0.156626506   |
|  250 |            528 |          40 |          2448 | 0.16          |
|  251 |            400 |         273 |          3488 | 1.087649402   |
|  252 |            400 |         274 |          3496 | 1.087301587   |
|  253 |            400 |         282 |          3520 | 1.114624506   |
|  254 |            408 |         279 |          3544 | 1.098425197   |
|  255 |            408 |         290 |          3552 | 1.137254902   |
+------+----------------+-------------+---------------+---------------+

The cached plan size which had been growing linearly suddenly drops but CompileTime increases 7 fold and CompileMemory shoots up. This is the cut off point between the plan being an auto parametrized one (with 1,000 parameters) to a non parametrized one. Thereafter it seems to get linearly less efficient (in terms of number of value clauses processed in a given time).

Not sure why this should be. Presumably when it is compiling a plan for specific literal values it must perform some activity that does not scale linearly (such as sorting).

It doesn't seem to affect the size of the cached query plan when I tried a query consisting entirely of duplicate rows and neither affects the order of the output of the table of the constants (and as you are inserting into a heap time spent sorting would be pointless anyway even if it did).

Moreover if a clustered index is added to the table the plan still shows an explicit sort step so it doesn't seem to be sorting at compile time to avoid a sort at run time.

I tried to look at this in a debugger but the public symbols for my version of SQL Server 2008 don't seem to be available so instead I had to look at the equivalent UNION ALL construction in SQL Server 2005.

A typical stack trace is below

sqlservr.exe!FastDBCSToUnicode()  + 0xac bytes  
sqlservr.exe!nls_sqlhilo()  + 0x35 bytes    
sqlservr.exe!CXVariant::CmpCompareStr()  + 0x2b bytes   
sqlservr.exe!CXVariantPerformCompare<167,167>::Compare()  + 0x18 bytes  
sqlservr.exe!CXVariant::CmpCompare()  + 0x11f67d bytes  
sqlservr.exe!CConstraintItvl::PcnstrItvlUnion()  + 0xe2 bytes   
sqlservr.exe!CConstraintProp::PcnstrUnion()  + 0x35e bytes  
sqlservr.exe!CLogOp_BaseSetOp::PcnstrDerive()  + 0x11a bytes    
sqlservr.exe!CLogOpArg::PcnstrDeriveHandler()  + 0x18f bytes    
sqlservr.exe!CLogOpArg::DeriveGroupProperties()  + 0xa9 bytes   
sqlservr.exe!COpArg::DeriveNormalizedGroupProperties()  + 0x40 bytes    
sqlservr.exe!COptExpr::DeriveGroupProperties()  + 0x18a bytes   
sqlservr.exe!COptExpr::DeriveGroupProperties()  + 0x146 bytes   
sqlservr.exe!COptExpr::DeriveGroupProperties()  + 0x146 bytes   
sqlservr.exe!COptExpr::DeriveGroupProperties()  + 0x146 bytes   
sqlservr.exe!CQuery::PqoBuild()  + 0x3cb bytes  
sqlservr.exe!CStmtQuery::InitQuery()  + 0x167 bytes 
sqlservr.exe!CStmtDML::InitNormal()  + 0xf0 bytes   
sqlservr.exe!CStmtDML::Init()  + 0x1b bytes 
sqlservr.exe!CCompPlan::FCompileStep()  + 0x176 bytes   
sqlservr.exe!CSQLSource::FCompile()  + 0x741 bytes  
sqlservr.exe!CSQLSource::FCompWrapper()  + 0x922be bytes    
sqlservr.exe!CSQLSource::Transform()  + 0x120431 bytes  
sqlservr.exe!CSQLSource::Compile()  + 0x2ff bytes   

So going off the names in the stack trace it appears to spend a lot of time comparing strings.

This KB article indicates that DeriveNormalizedGroupProperties is associated with what used to be called the normalization stage of query processing

This stage is now called binding or algebrizing and it takes the expression parse tree output from the previous parse stage and outputs an algebrized expression tree (query processor tree) to go forward to optimization (trivial plan optimization in this case) [ref].

I tried one more experiment (Script) which was to re-run the original test but looking at three different cases.

1. First Name and Last Name Strings of length 10 characters with no duplicates.
2. First Name and Last Name Strings of length 50 characters with no duplicates.
3. First Name and Last Name Strings of length 10 characters with all duplicates.

It can clearly be seen that the longer the strings the worse things get and that conversely the more duplicates the better things get. As previously mentioned duplicates don't affect the cached plan size so I presume that there must be a process of duplicate identification when constructing the algebrized expression tree itself.

Edit

One place where this information is leveraged is shown by @Lieven here

SELECT * 
FROM (VALUES ('Lieven1', 1),
             ('Lieven2', 2),
             ('Lieven3', 3))Test (name, ID)
ORDER BY name, 1/ (ID - ID) 

Because at compile time it can determine that the Name column has no duplicates it skips ordering by the secondary 1/ (ID - ID) expression at run time (the sort in the plan only has one ORDER BY column) and no divide by zero error is raised. If duplicates are added to the table then the sort operator shows two order by columns and the expected error is raised.

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