wiki:TracQuery
Last modified 15 years ago

Trac Ticket Queries

Table of Contents

In addition to reports, Trac provides support for custom ticket queries, used to display lists of tickets meeting a specified set of criteria.

To configure and execute a custom query, switch to the View Tickets module from the navigation bar, and select the Custom Query link.

Filters

When you first go to the query page the default filter will display tickets relevant to you:

  • If logged in then all open tickets it will display open tickets assigned to you.
  • If not logged in but you have specified a name or email address in the preferences then it will display all open tickets where your email (or name if email not defined) is in the CC list.
  • If not logged and no name/email defined in the preferences then all open issues are displayed.

Current filters can be removed by clicking the button to the left with the minus sign on the label. New filters are added from the pulldown lists at the bottom corners of the filters box ('And' conditions on the left, 'Or' conditions on the right). Filters with either a text box or a pulldown menu of options can be added multiple times to perform an or of the criteria.

You can use the fields just below the filters box to group the results based on a field, or display the full description for each ticket.

Once you've edited your filters click the Update button to refresh your results.

Clicking on one of the query results will take you to that ticket. You can navigate through the results by clicking the Next Ticket or Previous Ticket links just below the main menu bar, or click the Back to Query link to return to the query page.

You can safely edit any of the tickets and continue to navigate through the results using the Next/Previous/Back to Query links after saving your results. When you return to the query any tickets which were edited will be displayed with italicized text. If one of the tickets was edited such that it no longer matches the query criteria the text will also be greyed. Lastly, if a new ticket matching the query criteria has been created, it will be shown in bold.

The query results can be refreshed and cleared of these status indicators by clicking the Update button again.

Saving Queries

Trac allows you to save the query as a named query accessible from the reports module. To save a query ensure that you have Updated the view and then click the Save query button displayed beneath the results. You can also save references to queries in Wiki content, as described below.

Note: one way to easily build queries like the ones below, you can build and test the queries in the Custom report module and when ready - click Save query. This will build the query string for you. All you need to do is remove the extra line breaks.

You may want to save some queries so that you can come back to them later. You can do this by making a link to the query from any Wiki page. 

[query:status=new|assigned|reopened&version=1.0 Active tickets against 1.0]

Which is displayed as:

Active tickets against 1.0

This uses a very simple query language to specify the criteria (see Query Language).

Alternatively, you can copy the query string of a query and paste that into the Wiki link, including the leading ? character: 

[query:?status=new&status=assigned&status=reopened&group=owner Assigned tickets by owner]

Which is displayed as:

Assigned tickets by owner

Using the [[TicketQuery]] Macro

The  TicketQuery macro lets you display lists of tickets matching certain criteria anywhere you can use WikiFormatting.

Example: 

[[TicketQuery(version=0.6|0.7&resolution=duplicate)]]

This is displayed as:

No results

Just like the query: wiki links, the parameter of this macro expects a query string formatted according to the rules of the simple ticket query language.

A more compact representation without the ticket summaries is also available: 

[[TicketQuery(version=0.6|0.7&resolution=duplicate, compact)]]

This is displayed as:

No results

Finally, if you wish to receive only the number of defects that match the query, use the count parameter. 

[[TicketQuery(version=0.6|0.7&resolution=duplicate, count)]]

This is displayed as:

0

Customizing the table format

You can also customize the columns displayed in the table format (format=table) by using col=<field> - you can specify multiple fields and what order they are displayed by placing pipes (|) between the columns like below: 

[[TicketQuery(max=3,status=closed,order=id,desc=1,format=table,col=resolution|summary|owner|reporter)]]

This is displayed as:

Results (1 - 3 of 80)

Ticket Resolution Summary Owner Reporter
#120 fixed JPA对象查询及原生SQL查询效率对比 huangjianhua huangjianhua
#119 fixed 一些页面套缓存标签或多层缓存的几点建议 huangjianhua huangjianhua
#118 fixed 商城6.1版出现的慢语句 huangzhong

Full rows

In table format you can also have full rows by using rows=<field> like below: 

[[TicketQuery(max=3,status=closed,order=id,desc=1,format=table,col=resolution|summary|owner|reporter,rows=description)]]

This is displayed as:

Results (1 - 3 of 80)

Ticket Resolution Summary Owner Reporter
#120 fixed JPA对象查询及原生SQL查询效率对比 huangjianhua huangjianhua

Reported by huangjianhua, 13 years ago.
Description

JPA对象查询: 

select c.id from CompanyProduct c where ....

写查询语句非常简单,简单明了~ 在遍历商品的时候也是比较清楚的,代码也非常清晰,一看就知道什么意思了 如: 

for(CompanyProduct c : list){
     long product_id = c.getProduct().getId();
     ......
}

但是从上面的long product_id = c.getProduct().getId(); 这一行代码中,JPA隐藏又去做了并表查询,每执行一次就关联表查询一次,在做接口测试中,list的数据只有700多条,结果,执行的效率非常慢,大约用了3分多钟甚至更久;

简单总结一下: 采用JPA关联表查询,代码是清晰了,但是效率极大下降了;

原生SQL查询: 

select c.id, c.title,c.product_id,p.short_name 
from ent_product c, v_pdl_product p where c.product_id = p.id .......

写SQL语句变得复杂,记得DBA说过,我们写Sql语句的时候,尽量写到我们要什么数据就出什么数据,不要把整个对象查出来,或者是 "c.*"这么去写,因为这影响效率;

在执行遍历的时候: 

for(int i=0; i< list.size(); i++){
    Object[] objArray = (Object[])list.get(i);
    long productId    = objArray[2];
    long id           = objArray[0];
    .......

}

在页面输出内容的时候,代码的清晰度就变得没有用JPA对象查询的那么人性化了,如果要知道ojbArray[2]中是什么内容,还得到回去查看SQL语句中是怎么写的,尽管这个比较麻烦,但是在这里执行效率上面,采用原生SQL查询数据的效率远远快于采用JPA对象查询的速度.

简单总结一下: 原生SQL的方法,代码的可读性比较差,但运行的效率是非常快的.

总结:以后在写接口的时候,有关联表查询的,如:在for循环中又有: "long product_id = c.getProduct().getId();"又对效率的要求比较高的话,尽量采用原生SQL的写法,这样子可以减少for循环减1次的数据库连接.如果对效率要求不高,或者数据不多的情况下还是可以采用Jpa对象查询的.

这个现象和v6.1上线时的情况是同一类，这个机制的优劣也是要看情况的，本身jpa就有lazy load的属性，用的时候再去查不是一个错误，看用在什么场合，打个比方说，v6.1上线时那三个图片属性，如果是设成lazyload，那情况会怎么样呢，大家不妨手动试一下。

#119 fixed 一些页面套缓存标签或多层缓存的几点建议 huangjianhua huangjianhua

Reported by huangjianhua, 13 years ago.
Description

1.指定缓存标签的缓存时间是多长; 如: 

<memcached:cache time='3600' key='product_detail.jsp?${param.name}_${param.id}_${param.pid}_${param.buy}' refresh='${refreshFlag}'>

time='3600',指定1小时的MC缓存时间

2.显式在标签中加refresh参数,指定传刷新的参数;

3.套页面缓存中,切记禁用缓存块内再套另一块缓存,除非是业务特殊需求.

如: 在A页面已经套了缓存标签了,然后在A页面引用的B页面再套一层缓存标签,这时就需要注意了,B页面中的变量是否也在A页面中使用到,如果有使用到,或者是不确定是否被共享使用到了,这时候就禁用在B页面加缓存标签,因为在A,B页面同时加两层缓存标签,正常的情况下,意味着这个页面有2层缓存;异常情况下会导致变量共享的失败,数据混乱,页面出现的内容跟预想的不一致.

#118 fixed 商城6.1版出现的慢语句 huangzhong

Reported by huangzhong, 13 years ago.
Description
  • 现象

dba监测到一条慢语句，18万条数据，耗时20多秒 

select n.* 
from ent_news n ,ent_company ec 
where n.status!=2 
  and ec.status>=0 
  and n.user_id = ec.id  
  and n.product_id is not null  
  and  n.city ='北京' 
  order by n.last_update_date desc

这是经销商库中的商情列表，拿北京地区的商情按时间倒序，然后分页显示

  • 解决方案

此处的商情中只过滤了被否决的，其实从业务角度上来说，过期的商情也是没意义的，加上过期商情限制的话，数据量会少很多，这样做排序和分页会快很多，把n.status!=2改为 n.status<2，改完之后时间小于1秒

Query Language

query: TracLinks and the [[TicketQuery]] macro both use a mini “query language” for specifying query filters. Basically, the filters are separated by ampersands (&). Each filter then consists of the ticket field name, an operator, and one or more values. More than one value are separated by a pipe (|), meaning that the filter matches any of the values. To include a literal & or | in a value, escape the character with a backslash (\).

The available operators are:

= the field content exactly matches one of the values
~= the field content contains one or more of the values
^= the field content starts with one of the values
$= the field content ends with one of the values

All of these operators can also be negated:

!= the field content matches none of the values
!~= the field content does not contain any of the values
!^= the field content does not start with any of the values
!$= the field content does not end with any of the values

The date fields created and modified can be constrained by using the = operator and specifying a value containing two dates separated by two dots (..). Either end of the date range can be left empty, meaning that the corresponding end of the range is open. The date parser understands a few natural date specifications like "3 weeks ago", "last month" and "now", as well as Bugzilla-style date specifications like "1d", "2w", "3m" or "4y" for 1 day, 2 weeks, 3 months and 4 years, respectively. Spaces in date specifications can be left out to avoid having to quote the query string.

created=2007-01-01..2008-01-01 query tickets created in 2007
created=lastmonth..thismonth query tickets created during the previous month
modified=1weekago.. query tickets that have been modified in the last week
modified=..30daysago query tickets that have been inactive for the last 30 days

See also: TracTickets, TracReports, TracGuide