blocks|key|206664|text|让我们来看看(没有特定的顺序)|type|unstyled|depth|inlineStyleRanges|entityRanges|data|206665|206666|Cursors|ordered-list-item|206667|non-sargable+where+clauses|206668|failure用于索引外键字段|206669|无法索引where+clause|206670|correlated+subqueries|206671|accidental交叉连接中常用的字段导致需要区分结果集|206672|来自or+|206673|代码的代码表现不佳，导致多次读取或在不需要时被多次调用(我见过一些应用程序在不需要时或每次页面为opened)|206674|network管道时多次发送相同的代码联合定义的函数导致逐行processing|206675|Parameter嗅探所有过期的statistics|206676|Union而不是|206677|206678|206679|entityMap^0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|13|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|14|8|@]|9|@]|A|$]]|$1|C|3|D|5|E|7|15|8|@]|9|@]|A|$]]|$1|F|3|G|5|E|7|16|8|@]|9|@]|A|$]]|$1|H|3|I|5|E|7|17|8|@]|9|@]|A|$]]|$1|J|3|K|5|E|7|18|8|@]|9|@]|A|$]]|$1|L|3|M|5|E|7|19|8|@]|9|@]|A|$]]|$1|N|3|O|5|E|7|1A|8|@]|9|@]|A|$]]|$1|P|3|Q|5|E|7|1B|8|@]|9|@]|A|$]]|$1|R|3|S|5|E|7|1C|8|@]|9|@]|A|$]]|$1|T|3|U|5|E|7|1D|8|@]|9|@]|A|$]]|$1|V|3|W|5|E|7|1E|8|@]|9|@]|A|$]]|$1|X|3|Y|5|E|7|1F|8|@]|9|@]|A|$]]|$1|Z|3|-4|5|E|7|1G|8|@]|9|@]|A|$]]|$1|10|3|-4|5|6|7|1H|8|@]|9|@]|A|$]]|$1|11|3|-4|5|6|7|1I|8|@]|9|@]|A|$]]]|12|$]]

Let's see (in no particular order)

<ol>
<li>Cursors</li>
<li>non-sargable where clauses</li>
<li>failure to index foreign key fields</li>
<li>failure to index fields commonly used in the where clause</li>
<li>correlated subqueries</li>
<li>accidental cross joins causing the need to distinct the result set</li>
<li>Badly performing code coming from ORMs</li>
<li>Code that causes too many reads or is called more than once when it didn't need to be (I've seen applications that send the same code many times when they didn't need to or every time a page is opened)</li>
<li>network pipe overloaded</li>
<li>User defined functions causing row-by-row processing</li>
<li>Parameter sniffing</li>
<li>out of date statistics</li>
<li>Union instead of union all</li>
</ol>

blocks|key|206635|text|表扫描，因为：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|206636|206637|索引不存在where子句中过期的|unordered-list-item|206638|统计信息|206639|函数防止使用|206640|206641|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|N|8|@]|9|@]|A|$]]|$1|C|3|D|5|E|7|O|8|@]|9|@]|A|$]]|$1|F|3|G|5|E|7|P|8|@]|9|@]|A|$]]|$1|H|3|I|5|E|7|Q|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|R|8|@]|9|@]|A|$]]|$1|K|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|L|$]]

table scan because:

<ul>
<li>index does not exist</li>
<li>stats out of date</li>
<li>functions in where clause prevent usage</li>
</ul>

blocks|key|1285581|text|类似|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1285582|服务器的内存和存储类型。|ordered-list-item|1285583|网络-延迟和带宽issues.|1285584|Indexing+-不确定是否考虑此数据库structure|1285585|Queries+-具有可能导致全表扫描的联接问题的错误查询。|1285586|1285587|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|O|8|@]|9|@]|A|$]]|$1|E|3|F|5|D|7|P|8|@]|9|@]|A|$]]|$1|G|3|H|5|D|7|Q|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|R|8|@]|9|@]|A|$]]|$1|K|3|-4|5|6|7|S|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|M|$]]

<ol>
<li>Server - Like memory and storage
types.</li>
<li>Network - Latency and bandwidth
issues.</li>
<li>Indexing - not sure if you consider
this database structure</li>
<li>Queries - Bad queries with join
issues that may cause full table
scans.</li>
</ol>

blocks|key|1285625|text|身体..。内存耗尽，必须转到磁盘。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1285626|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

Physical.... Running out of memory and having to go to disk.

blocks|key|4501723|text|将标量函数应用于结果集中的每一行|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4501724|SELECT+fn_EveluateSomeValue([ColumnName])+FROM+LargeTable|code-block|syntax|javascript|4501725|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

The Applying scalar function to each row in the result set 

<pre><code>SELECT fn_EveluateSomeValue([ColumnName]) FROM LargeTable
</code></pre>

blocks|key|1285612|text|使用游标。适用于任何数据库。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1285613|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

blocks|key|4502031|text|使用表格数据，一次一行，而不是一次一个表格(即游标)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4502032|不必要的(或设计糟糕的)锁。|4502033|日志记录不需要记录的内容(从表中删除而不是截断表，等等)|4502034|对批量加载数据的时间有限制。严重减慢了镶嵌的速度。关闭它们，加载数据，然后重新打开它们。|4502035|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

Using table data one row at a time instead of one table at a time (i.e. cursors).

Unnecessary (or badly designed) locks.

Logs logging things that don't need to be logged (Delete from table instead of Truncate table, etc.)

Having constraints on when bulk loading data. Seriously slows down the insert. Turn them off, load the data, then turn them back on.

blocks|key|1285809|text|同样引用游标，也是写得很糟糕的客户端应用程序，它们得到一个巨大的记录集，然后自己处理它，因为开发人员不知道sql只是一个用来保存数据的巨大堆。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1285810|尝试在一个巨大的查询中做所有的事情，而不是把它分解成合理的步骤。有时，这不会给SQL一个机会来正确地减少索引量(希望如此!)它必须查看的页面。与此相关，不了解如何在更新大型索引表之前使用临时表传递操作。|1285811|没有连接或常用查询字段的索引。|1285812|当您总是查找和返回相同的值(例如，使用EmployeeID查找时，员工的格式化姓名)时，不会在索引中包含字段，这会导致两个操作而不是一个操作。|1285813|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

Ditto ref cursors, also badly written client apps that get a huge recordset back then process it themselves because the developer didn't understand that sql was anything but a huge heap to hold data in.

Trying to do everything in one huge query instead of breaking it down into sensible steps.
Sometimes this will not give SQL a chance to correctly reduce the amount of index (hopefully !) pages that it has to look at.
Related to this, not understanding how to use temp tables to hand off manipulations prior to updating large indexed tables.

Not having indexes on joins or commonly queried fields.

Not including fields in indexes when you are always seeking and return the same value (for instance formatted name for an employee when you look up using EmployeeID) causing two actions instead of one.

blocks|key|4502132|text|一些容易摘到的果实：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4502133|当游标为necessary时，|4502134|标量UDF|unordered-list-item|4502135|省略索引中的text()+XPath+UDF列(导致键查找)|offset|length|style|CODE|4502136|使用游标|4502137|不使用fast_forward|4502138|4502139|4502140|​|4502141|使用JOIN测试APPLY，反之亦然(测试！)|4502142|entityMap^0|0|0|0|6|6|0|1|1|0|0|0|2|4|8|5|0^^$0|@$1|2|3|4|5|6|7|Y|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|Z|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|10|8|@]|9|@]|A|$]]|$1|G|3|H|5|F|7|11|8|@$I|12|J|13|K|L]]|9|@]|A|$]]|$1|M|3|N|5|F|7|14|8|@]|9|@]|A|$]]|$1|O|3|P|5|F|7|15|8|@]|9|@]|A|$]]|$1|Q|3|-4|5|6|7|16|8|@]|9|@]|A|$]]|$1|R|3|-4|5|6|7|17|8|@]|9|@]|A|$]]|$1|S|3|T|5|6|7|18|8|@]|9|@]|A|$]]|$1|U|3|V|5|6|7|19|8|@$I|1A|J|1B|K|L]|$I|1C|J|1D|K|L]]|9|@]|A|$]]|$1|W|3|-4|5|6|7|1E|8|@]|9|@]|A|$]]]|X|$]]

Some low-hanging fruit:

<ul>
<li>Scalar UDFs </li>
<li>omitting <code>text()</code> in XPath queries</li>
<li>missing columns in indices (causing key lookups)</li>
<li>using cursors
<ul>
<li>not using fast_forward when possible when cursors are necessary</li>
</ul></li>
<li>using <code>JOIN</code> when <code>APPLY</code> will do, or vice versa (test!)</li>
</ul>

blocks|key|206595|text|在处理大量命令时，触发器可能是一个巨大的瓶颈(也是令人头疼的问题)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|206596|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

Triggers can be a HUGE bottleneck (and headache) when you are processing large batches of commands.

blocks|key|1285711|text|如果服务器中的I/O系统无法完成任务，您可能会遇到tempdb上的闩锁争用，而这反过来又会导致严重的性能问题。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1285712|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

If the I/O system in the server isn't up to the job, you can get latch contention on tempdb and this in turn can cause serious performance problems.

blocks|key|206477|text|我倾向于遇到以下瓶颈(按频率顺序)：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|206478|206479|缺少索引或索引不正确(导致表扫描)|ordered-list-item|206480|写得不好的查询|206481|I/O+contention|206482|206483|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|N|8|@]|9|@]|A|$]]|$1|C|3|D|5|E|7|O|8|@]|9|@]|A|$]]|$1|F|3|G|5|E|7|P|8|@]|9|@]|A|$]]|$1|H|3|I|5|E|7|Q|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|R|8|@]|9|@]|A|$]]|$1|K|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|L|$]]

I tend to run into the following bottlenecks (in order of frequency):

<ol>
<li>Missing or incorrect indices (resulting in table scans)</li>
<li>Poorly written queries</li>
<li>I/O contention</li>
</ol>

blocks|key|1506578|text|即使有正确的数据库设计和索引，糟糕的my.cnf配置也会杀死服务器。阅读：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1506579|http://www.mysqlperformanceblog.com/2006/09/29/what-to-tune-in-mysql-server-after-installation/+http://www.mysqlperformanceblog.com/2007/11/01/innodb-performance-optimization-basics/+http://www.mysqlperformanceblog.com/2007/11/03/choosing-innodb_buffer_pool_size/|offset|length|1506580|http://www.mysqlperformanceblog.com/2007/08/18/how-fast-can-you-sort-data-with-mysql/+http://www.mysqlperformanceblog.com/2007/09/17/mysql-what-read_buffer_size-value-is-optimal/|1506581|http://dev.mysql.com/doc/refman/5.1/en/server-system-variables.html|1506582|有用的my.cnf分析工具：http://www.day32.com/MySQL/tuning-primer.sh|1506583|entityMap|0|LINK|mutability|MUTABLE|url|http://www.mysqlperformanceblog.com/2006/09/29/what-to-tune-in-mysql-server-after-installation/|1|http://www.mysqlperformanceblog.com/2007/11/01/innodb-performance-optimization-basics/|2|http://www.mysqlperformanceblog.com/2007/11/03/choosing-innodb_buffer_pool_size/|3|http://www.mysqlperformanceblog.com/2007/08/18/how-fast-can-you-sort-data-with-mysql/|4|http://www.mysqlperformanceblog.com/2007/09/17/mysql-what-read_buffer_size-value-is-optimal/|5|6|http://www.day32.com/MySQL/tuning-primer.sh^0|0|0|2N|0|2O|2E|1|53|28|2|0|0|2D|3|2E|2K|4|0|0|1V|5|0|E|17|6|0^^$0|@$1|2|3|4|5|6|7|14|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|15|8|@]|9|@$D|16|E|17|1|18]|$D|19|E|1A|1|1B]|$D|1C|E|1D|1|1E]]|A|$]]|$1|F|3|G|5|6|7|1F|8|@]|9|@$D|1G|E|1H|1|1I]|$D|1J|E|1K|1|1L]]|A|$]]|$1|H|3|I|5|6|7|1M|8|@]|9|@$D|1N|E|1O|1|1P]]|A|$]]|$1|J|3|K|5|6|7|1Q|8|@]|9|@$D|1R|E|1S|1|1T]]|A|$]]|$1|L|3|-4|5|6|7|1U|8|@]|9|@]|A|$]]]|M|$N|$5|O|P|Q|A|$R|S]]|T|$5|O|P|Q|A|$R|U]]|V|$5|O|P|Q|A|$R|W]]|X|$5|O|P|Q|A|$R|Y]]|Z|$5|O|P|Q|A|$R|10]]|11|$5|O|P|Q|A|$R|I]]|12|$5|O|P|Q|A|$R|13]]]]

Having a poor my.cnf configuration can kill a server even with proper database design and indexing. Read:

<a href="http://www.mysqlperformanceblog.com/2006/09/29/what-to-tune-in-mysql-server-after-installation/" rel="nofollow noreferrer">http://www.mysqlperformanceblog.com/2006/09/29/what-to-tune-in-mysql-server-after-installation/</a>
<a href="http://www.mysqlperformanceblog.com/2007/11/01/innodb-performance-optimization-basics/" rel="nofollow noreferrer">http://www.mysqlperformanceblog.com/2007/11/01/innodb-performance-optimization-basics/</a>
<a href="http://www.mysqlperformanceblog.com/2007/11/03/choosing-innodb_buffer_pool_size/" rel="nofollow noreferrer">http://www.mysqlperformanceblog.com/2007/11/03/choosing-innodb_buffer_pool_size/</a>

<a href="http://www.mysqlperformanceblog.com/2007/08/18/how-fast-can-you-sort-data-with-mysql/" rel="nofollow noreferrer">http://www.mysqlperformanceblog.com/2007/08/18/how-fast-can-you-sort-data-with-mysql/</a>
<a href="http://www.mysqlperformanceblog.com/2007/09/17/mysql-what-read_buffer_size-value-is-optimal/" rel="nofollow noreferrer">http://www.mysqlperformanceblog.com/2007/09/17/mysql-what-read_buffer_size-value-is-optimal/</a>

<a href="http://dev.mysql.com/doc/refman/5.1/en/server-system-variables.html" rel="nofollow noreferrer">http://dev.mysql.com/doc/refman/5.1/en/server-system-variables.html</a>

Helpful my.cnf analytical tool:
<a href="http://www.day32.com/MySQL/tuning-primer.sh" rel="nofollow noreferrer">http://www.day32.com/MySQL/tuning-primer.sh</a>

blocks|key|1506622|text|我从来没有找到过关于分解大型查询的有用信息，在Oracle中，您似乎建议更多地将所有内容放在一个查询中，而不是使用临时表。如果临时表保存了大量数据，也可能会出现重做日志问题。我想了解更多/获取一些链接？|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1506623|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

I've never managed to find much useful information on breaking up large queries, in Oracle it seems your advised more to keep everything together in one query rather than use temp tables. You can also get redo log issues if your temp table is holding a lot of data.
I'd like to know more/get some links?

blocks|key|206801|text|硬件故障。我曾经有一台服务器，它的硬盘驱动器有一些扇区难以读取，我们更换它后，性能有了显着的提高。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|206802|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

faulty hardware. I had a server once where the hard drive had some sectors that it was having difficulty reading and we replacing it had a noticeable performance increase.

blocks|key|206825|text|对我们来说，调整CPU设置和电源计划设置可以将CPU密集型查询(搜索，持续时间约为5秒)的速度提高2倍左右。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|206826|1)+BIOS设置从“性能功耗比优化(DAPC)”更改为“性能”或“性能功耗比优化(OS)”。这两个选项似乎执行类似，但“操作系统”控制的一个不会连续运行风扇的最大。|206827|2)+Windows电源计划从“平衡”更改为“高性能”。|206828|这是在升级CPU后发现的，几乎没有任何改进。|206829|从SQLServerCentral检查CPU速度的命令|offset|length|206830|PS>+gwmi+-class+win32_Processor+%7C+SELECT+CurrentClockSpeed,+MaxClockSpeed|code-block|syntax|javascript|206831|2017年6月13日更新:警告:该数字可能会报告当前=最大值，但任务管理器可能会显示一个不同的(低得多的)数字。此外，BIOS模式“性能功耗比优化(OS)”突然停止为我们工作后，一些硬件变化。CPU被锁定在50%25的最大频率，无论负载只有“性能”模式(大风扇模式)仍然达到最大CPU。我们一定是缺少固件/软件补丁。|206832|entityMap|0|LINK|mutability|MUTABLE|url|http://www.sqlservercentral.com/scripts/CPU/72156/^0|0|0|0|0|1|G|0|0|0|0^^$0|@$1|2|3|4|5|6|7|10|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|11|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|12|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|13|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|14|8|@]|9|@$J|15|K|16|1|17]]|A|$]]|$1|L|3|M|5|N|7|18|8|@]|9|@]|A|$O|P]]|$1|Q|3|R|5|6|7|19|8|@]|9|@]|A|$]]|$1|S|3|-4|5|6|7|1A|8|@]|9|@]|A|$]]]|T|$U|$5|V|W|X|A|$Y|Z]]]]

For us, adjusting the BIOS Settings and Power Plan settings resulted in solid ~2X faster times for queries that were CPU intensive (searching, duration about 5s).

1) BIOS Settings changed from "Performance Per Watt Optimized (DAPC)" to either "Performance" or "Performance Per Watt Optimized (OS)". Both options seemed to perform similarly however the "OS" controlled one did not run the fan at max continuously. 

2) The Windows power plan was changed from "Balanced” to “High performance”.

This was discovered after upgrading the CPUs and seeing almost no improvement.

Command to check CPU speed from <a href="http://www.sqlservercentral.com/scripts/CPU/72156/" rel="nofollow noreferrer">SQLServerCentral</a>:

<pre><code>PS&gt; gwmi -class win32_Processor | SELECT CurrentClockSpeed, MaxClockSpeed
</code></pre>

Update 6/13/2017: Warning: That number may report Current = Max however Task Manager may show a a different (much lower) number. Also the BIOS mode "Performance Per Watt Optimized (OS)" suddenly stopped working for us after some hardware changes. The CPU was locked at 50% max frequency, regardless of load Only "Performance" mode (loud fan mode) still achieved max CPU. We must be missing a firmware/software patch.

blocks|key|1508232|text|要避免的子句(如果可能)：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1508233|1508234|DISTINCT+/+UNIQUE|unordered-list-item|1508235|UNION|1508236|GROUP+BY|1508237|ORDER+BY|1508238|1508239|entityMap^0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|P|8|@]|9|@]|A|$]]|$1|C|3|D|5|E|7|Q|8|@]|9|@]|A|$]]|$1|F|3|G|5|E|7|R|8|@]|9|@]|A|$]]|$1|H|3|I|5|E|7|S|8|@]|9|@]|A|$]]|$1|J|3|K|5|E|7|T|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|U|8|@]|9|@]|A|$]]|$1|M|3|-4|5|6|7|V|8|@]|9|@]|A|$]]]|N|$]]

Clauses to avoid (if possible) :

<ul>
<li>DISTINCT / UNIQUE</li>
<li>UNION</li>
<li>GROUP BY</li>
<li>ORDER BY</li>
</ul>

What is the most common performance bottleneck that is not caused by the database structure?

Top 10 SQL Server performance bottlenecks

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符。

功能5描述100个字符功能5描述100个字符功能5描述100个字符功能5描述100个字符功能5描述100个字符功能5描述100个字符

功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符

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