非聚集索引在堆上的性能与聚集索引的性能 [英] Performance of Non Clustered Indexes on Heaps vs Clustered Indexes
问题描述
这份2007年白皮书比较了单个select/insert的性能/delete/update和range select语句在作为聚簇索引组织的表上与在与CI表相同的键列上具有非聚簇索引的堆组织的表上相比.
This 2007 White Paper compares the performance for individual select/insert/delete/update and range select statements on a table organized as a clustered index vs that on a table organized as a heap with a non clustered index on the same key columns as the CI table.
通常，聚集索引选项在测试中表现更好，因为只需要维护一种结构，并且因为不需要书签查找.
Generally the clustered index option performed better in the tests as there is only one structure to maintain and because there is no need for bookmark lookups.
本文未涉及的一个潜在有趣案例是将堆上的非聚簇索引与聚簇索引上的非聚簇索引进行比较.在那种情况下，我希望堆甚至可以在NCI叶级别上表现更好，因为SQL Server具有直接遵循的RID，而不需要遍历聚集索引.
One potentially interesting case not covered by the paper would have been a comparison between a non clustered index on a heap vs a non clustered index on a clustered index. In that instance I would have expected the heap might even perform better as once at the NCI leaf level SQL Server has a RID to follow directly rather than needing to traverse the clustered index.
有人知道在这一领域进行过类似的正式测试吗?如果是，结果是什么?
Is anyone aware of similar formal testing that has been carried out in this area and if so what were the results?
推荐答案
要检查您的请求，我按照以下方案创建了2个表:
To check your request I created 2 tables following this scheme:
-
表示余额信息的
- 790万条记录.
- 从1到790万的身份字段
- 一个数字字段，将记录分为约50万个组.
- 7.9 million records representing balance information.
- an identity field counting from 1 to 7.9 million
- a number field grouping the records in about 500k groups.
第一个称为heap的表在字段group上获得了非聚集索引.第二个表clust在顺序字段key上有一个聚集索引，在字段group
The first table called heap got a non clustered index on the field group. The second table called clust got a clustered index on the sequential field called key and a nonclustered index on the field group
测试在具有2个超线程内核，4Gb内存和64位Windows 7的I5 M540处理器上运行.
The tests were run on an I5 M540 processor with 2 hyperthreaded cores, 4Gb memory and 64-bit windows 7.
Microsoft SQL Server 2008 R2 (RTM) - 10.50.1600.1 (X64)
Apr 2 2010 15:48:46
Developer Edition (64-bit) on Windows NT 6.1 <X64> (Build 7601: Service Pack 1)
2011年3月9日更新:我通过运行以下.net代码并在Sql Server Profiler中记录了持续时间，CPU，读取，写入和行计数，做了第二次更广泛的基准测试. (使用的CommandText将在结果中提及.)
Update on 9 Mar 2011: I did a second more extensive benchmark by running the following .net code and logging Duration, CPU, Reads, Writes and RowCounts in Sql Server Profiler. (The CommandText used will be mentioned in the results.)
注意: CPU和持续时间以毫秒为单位
NOTE: CPU and Duration are expressed in milliseconds
- 1000个查询 从结果中消除
- 零CPU查询 从结果中删除
- 0条受影响的行
- 1000 queries
- zero CPU queries are eliminated from the results
- 0 rows affected are eliminated from the results
int[] idList = new int[] { 6816588, 7086702, 6498815 ... }; // 1000 values here.
using (var conn = new SqlConnection(@"Data Source=myserver;Initial Catalog=mydb;Integrated Security=SSPI;"))
{
conn.Open();
using (var cmd = new SqlCommand())
{
cmd.Connection = conn;
cmd.CommandType = CommandType.Text;
cmd.CommandText = "select * from heap where common_key between @id and @id+1000";
cmd.Parameters.Add("@id", SqlDbType.Int);
cmd.Prepare();
foreach (int id in idList)
{
cmd.Parameters[0].Value = id;
using (var reader = cmd.ExecuteReader())
{
int count = 0;
while (reader.Read())
{
count++;
}
Console.WriteLine(String.Format("key: {0} => {1} rows", id, count));
}
}
}
}
更新结束于2011年3月9日.
SELECT性能
要检查性能编号，我在堆表上一次在集群表上执行了以下查询:
SELECT performance
To check performanc numbers I performed the following queries once on the heap table and once on the clust table:
select * from heap/clust where group between 5678910 and 5679410
select * from heap/clust where group between 6234567 and 6234967
select * from heap/clust where group between 6455429 and 6455729
select * from heap/clust where group between 6655429 and 6655729
select * from heap/clust where group between 6955429 and 6955729
select * from heap/clust where group between 7195542 and 7155729
此基准测试的结果适用于heap:
rows reads CPU Elapsed
----- ----- ----- --------
1503 1510 31ms 309ms
401 405 15ms 283ms
2700 2709 0ms 472ms
0 3 0ms 30ms
2953 2962 32ms 257ms
0 0 0ms 0ms
2011年3月9日更新:
cmd.CommandText = "select * from heap where group between @id and @id+1000";
- 721行的CPU> 0，并且影响超过0行
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 1001 69788 6368 -
Cpu 15 374 37 0.00754
Reads 1069 91459 7682 1.20155
Writes 0 0 0 0.00000
Duration 0.3716 282.4850 10.3672 0.00180
更新结束于2011年3月9日.
表clust的结果是:
for the table clust the results are:
rows reads CPU Elapsed
----- ----- ----- --------
1503 4827 31ms 327ms
401 1241 0ms 242ms
2700 8372 0ms 410ms
0 3 0ms 0ms
2953 9060 47ms 213ms
0 0 0ms 0ms
2011年3月9日更新:
cmd.CommandText = "select * from clust where group between @id and @id+1000";
- 721行的CPU> 0，并且影响超过0行
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 1001 69788 6056 -
Cpu 15 468 38 0.00782
Reads 3194 227018 20457 3.37618
Writes 0 0 0 0.0
Duration 0.3949 159.6223 11.5699 0.00214
更新结束于2011年3月9日.
SELECT JOIN性能
cmd.CommandText = "select * from heap/clust h join keys k on h.group = k.group where h.group between @id and @id+1000";
SELECT WITH JOIN performance
cmd.CommandText = "select * from heap/clust h join keys k on h.group = k.group where h.group between @id and @id+1000";
此基准测试的结果适用于heap:
The results of this benchmark are for the heap:
873行的CPU> 0，并且影响超过0行
873 Rows have > 0 CPU and affect more than 0 rows
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 1009 4170 1683 -
Cpu 15 47 18 0.01175
Reads 2145 5518 2867 1.79246
Writes 0 0 0 0.00000
Duration 0.8215 131.9583 1.9095 0.00123
此基准测试的结果适用于clust:
865行具有> 0 CPU，并且影响超过0行
865 Rows have > 0 CPU and affect more than 0 rows
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 1000 4143 1685 -
Cpu 15 47 18 0.01193
Reads 5320 18690 8237 4.97813
Writes 0 0 0 0.00000
Duration 0.9699 20.3217 1.7934 0.00109
更新性能
第二批查询是更新语句:
UPDATE performance
The second batch of queries are update statements:
update heap/clust set amount = amount + 0 where group between 5678910 and 5679410
update heap/clust set amount = amount + 0 where group between 6234567 and 6234967
update heap/clust set amount = amount + 0 where group between 6455429 and 6455729
update heap/clust set amount = amount + 0 where group between 6655429 and 6655729
update heap/clust set amount = amount + 0 where group between 6955429 and 6955729
update heap/clust set amount = amount + 0 where group between 7195542 and 7155729
该基准测试的结果heap:
rows reads CPU Elapsed
----- ----- ----- --------
1503 3013 31ms 175ms
401 806 0ms 22ms
2700 5409 47ms 100ms
0 3 0ms 0ms
2953 5915 31ms 88ms
0 0 0ms 0ms
2011年3月9日更新:
cmd.CommandText = "update heap set amount = amount + @id where group between @id and @id+1000";
- 811行的CPU> 0，并且影响超过0行
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 1001 69788 5598 811
Cpu 15 873 56 0.01199
Reads 2080 167593 11809 2.11217
Writes 0 1687 121 0.02170
Duration 0.6705 514.5347 17.2041 0.00344
更新结束于2011年3月9日.
clust的基准测试结果:
the results of this benchmark for the clust:
rows reads CPU Elapsed
----- ----- ----- --------
1503 9126 16ms 35ms
401 2444 0ms 4ms
2700 16385 31ms 54ms
0 3 0ms 0ms
2953 17919 31ms 35ms
0 0 0ms 0ms
2011年3月9日更新:
cmd.CommandText = "update clust set amount = amount + @id where group between @id and @id+1000";
- 853行具有> 0 CPU，影响多于0行
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 1001 69788 5420 -
Cpu 15 594 50 0.01073
Reads 6226 432237 33597 6.20450
Writes 0 1730 110 0.01971
Duration 0.9134 193.7685 8.2919 0.00155
更新结束于2011年3月9日.
删除基准
我运行的第三批查询是删除语句
DELETE benchmarks
the third batch of queries I ran are delete statements
delete heap/clust where group between 5678910 and 5679410
delete heap/clust where group between 6234567 and 6234967
delete heap/clust where group between 6455429 and 6455729
delete heap/clust where group between 6655429 and 6655729
delete heap/clust where group between 6955429 and 6955729
delete heap/clust where group between 7195542 and 7155729
heap的基准测试结果:
The result of this benchmark for the heap:
rows reads CPU Elapsed
----- ----- ----- --------
1503 10630 62ms 179ms
401 2838 0ms 26ms
2700 19077 47ms 87ms
0 4 0ms 0ms
2953 20865 62ms 196ms
0 4 0ms 9ms
2011年3月9日更新:
cmd.CommandText = "delete heap where group between @id and @id+1000";
- 724行具有> 0 CPU，影响多于0行
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 192 69788 4781 -
Cpu 15 499 45 0.01247
Reads 841 307958 20987 4.37880
Writes 2 1819 127 0.02648
Duration 0.3775 1534.3383 17.2412 0.00349
更新结束于2011年3月9日.
clust的基准测试结果:
the result of this benchmark for the clust:
rows reads CPU Elapsed
----- ----- ----- --------
1503 9228 16ms 55ms
401 3681 0ms 50ms
2700 24644 46ms 79ms
0 3 0ms 0ms
2953 26955 47ms 92ms
0 3 0ms 0ms
2011年3月9日更新:
cmd.CommandText = "delete clust where group between @id and @id+1000";
- 751行具有> 0 CPU，影响多于0行
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 144 69788 4648 -
Cpu 15 764 56 0.01538
Reads 989 458467 30207 6.48490
Writes 2 1830 127 0.02694
Duration 0.2938 2512.1968 24.3714 0.00555
更新结束于2011年3月9日.
INSERT基准测试
基准测试的最后一部分是执行插入语句.
INSERT benchmarks
The last part of the benchmark is the execution of insert statements.
插入堆/集群(...) 值(...)， (...)， (...)， (...)， (...)， (...)
insert into heap/clust (...) values (...), (...), (...), (...), (...), (...)
heap的基准测试结果:
rows reads CPU Elapsed
----- ----- ----- --------
6 38 0ms 31ms
2011年3月9日更新:
string str = @"insert into heap (group, currency, year, period, domain_id, mtdAmount, mtdAmount, ytdAmount, amount, ytd_restated, restated, auditDate, auditUser)
values";
for (int x = 0; x < 999; x++)
{
str += string.Format(@"(@id + {0}, 'EUR', 2012, 2, 0, 100, 100, 1000 + @id,1000, 1000,1000, current_timestamp, 'test'), ", x);
}
str += string.Format(@"(@id, 'CAD', 2012, 2, 0, 100, 100, 1000 + @id,1000, 1000,1000, current_timestamp, 'test') ", 1000);
cmd.CommandText = str;
- 912个语句具有> 0个CPU
- 912 statements have > 0 CPU
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 1000 1000 1000 -
Cpu 15 2138 25 0.02500
Reads 5212 7069 6328 6.32837
Writes 16 34 22 0.02222
Duration 1.6336 293.2132 4.4009 0.00440
更新结束于2011年3月9日.
此基准测试对clust的结果:
The result of this benchmark for the clust:
rows reads CPU Elapsed
----- ----- ----- --------
6 50 0ms 18ms
2011年3月9日更新:
string str = @"insert into clust (group, currency, year, period, domain_id, mtdAmount, mtdAmount, ytdAmount, amount, ytd_restated, restated, auditDate, auditUser)
values";
for (int x = 0; x < 999; x++)
{
str += string.Format(@"(@id + {0}, 'EUR', 2012, 2, 0, 100, 100, 1000 + @id,1000, 1000,1000, current_timestamp, 'test'), ", x);
}
str += string.Format(@"(@id, 'CAD', 2012, 2, 0, 100, 100, 1000 + @id,1000, 1000,1000, current_timestamp, 'test') ", 1000);
cmd.CommandText = str;
- 946个语句具有> 0个CPU
- 946 statements have > 0 CPU
Counter Minimum Maximum Average Weighted
--------- ------- ---------- ------- ---------
RowCounts 1000 1000 1000 -
Cpu 15 2403 21 0.02157
Reads 6810 8997 8412 8.41223
Writes 16 25 19 0.01942
Duration 1.5375 268.2571 6.1463 0.00614
更新结束于2011年3月9日.
结论
尽管使用群集&访问表时，逻辑读操作仍在进行.非聚集索引(使用非聚集索引时)的性能结果为:
Conclusions
Although there are more logical reads going on when accessing the table with the clustered & the nonclustered index (while using the nonclustered index) the performance results are:
- SELECT语句具有可比性
- 在具有聚集索引的情况下，UPDATE语句更快
- 有了聚集索引，DELETE语句会更快
- 在具有聚集索引的情况下，INSERT语句更快
当然，我的基准测试在特定类型的表和非常有限的查询集上非常受限制，但是我认为基于这些信息，我们已经可以开始说在上面创建集群索引实际上总是更好.您的桌子.
Of course my benchmark was very limited on a specific kind of table and with a very limited set of queries, but I think that based on this information we can already start saying that it is virtually always better to create a clustered index on your table.
2011年3月9日更新:
从添加的结果中我们可以看到，有限测试的结论在每种情况下都不正确.
As we can see from the added results, the conclusions on the limited tests were not correct in every case.
现在，结果表明，从聚集索引中受益的唯一语句是更新语句.在具有聚集索引的表上，其他语句要慢大约30％.
The results now indicate that the only statements which benefit from the clustered index are the update statements. The other statements are about 30% slower on the table with clustered index.
一些其他图表，其中我绘制了每个查询对堆与集群的加权持续时间.
Some additional charts where I plotted the weighted duration per query for heap vs clust.
如您所见，insert语句的性能配置文件非常有趣.尖峰是由一些数据点导致的，这些数据点需要花费更长的时间才能完成.
As you can see the performance profile for the insert statements is quite interesting. The spikes are caused by a few data points which take a lot longer to complete.
更新结束于2011年3月9日.
这篇关于非聚集索引在堆上的性能与聚集索引的性能的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
