CriteriaAPI支持使用基于对象的查询图以编程方式构建查询。
The Criteria API enables a programmatic construction of queries using an object-based query graph.
图2显示了这个查询的一个可能的计划。
图3显示的是高级查询统计的基本实现架构。
Figure 3 shows the basic implementation architecture of advanced query statistics.
这样就可以允许在执行查询的时候才把图传递给它。
This allows a graph to be passed to the query when it is executed.
这个已重写的查询现在如图10 所示。
图3演示了该查询是如何工作的。
图1显示的是高级查询统计配置界面。
Figure 1 displays the advanced query statistics configuration screen.
图13显示了此查询的输出。
她的查询将返回图8所示的内容。
已经对表中所有行的缺省查询填写了内容(图14)。
A default query for all rows in the table will already be filled in (Figure 14).
对于本文的查询样例，图12显示了索引报告，它描述了引用表的现有索引。
For the sample query in this article, Figure 12 shows the index report, which describes the existing indexes of the referenced tables.
执行该查询将返回与图8一样的结果。
Executing this query should return a result like the one in Figure 8.
在SQL查询文本框(图5)之中，输入如代码清单1所示的代码。
In the SQL query text box (Figure 5), enter the code shown in Listing 1.
在清单10中，有两个FOAF图被传递给查询。
In Listing 10, two named FOAF graphs are passed to the query.
除了后台图，SPARQL还能查询任意数量的命名图。
In addition to the background graph, SPARQL can query any number of named graphs.
图12确认查询的访问计划中使用了staff表上的新索引。
Figure 12 confirms that the new index on the STAFF table is being used in the query access plan.
图12显示了此查询的输出。
Figure 12 illustrates what the output of this query looks like.
CONSTRUCT非常重要，可以根据SPARQL查询结果构造rdf图。
Construct is quite important because it allows you to construct RDF graphs from the results of the SPARQL query.
图8显示了该查询的结果。
图8 . db 2 batch-查询执行。
点击Next，这样您可以在DepartmentManagerbean中看到所有可用的查询方法(图23)。
Click Next so that you can see all of the available query methods in the DepartmentManager bean (Figure 23).
图4展示了哪些查询从这些建议中获益最多。
Figure 4 shows which queries benefited most from the recommendations.
值得注意的是，这样的设置会影响到查询相关元素的所有操作，例如浏览图和主题图的查询。
Note that this setting will affect all operations that query for related elements, for instance queries on Browse diagrams and Topic diagrams.
不像其它的图，每次当一个主题图被打开时，它就会自动运行查询程序，并且更新这个图来反映最新的源代码。
Unlike other diagrams, each time a topic diagram is opened, it runs the query automatically and updates the diagram to reflect the latest source code.
其中包含如何通过使用查询格式化、注释、报告和访问计划图来更好地理解问题查询。
It includes how to understand the problem query better by using the visual AIDS provided by query formatting, annotation, reports, and the access plan graph.
使用命名图的示例还显示了如何使用SPARQL组合多个图来启用查询选项。
Examples using named graphs have shown you how combining multiple graphs in SPARQL opens up your querying options.
热门查询条形图：该图显示了用户输入的查询的热门度。
Popular queries bar chart: This chart shows the popularity of queries issued by users.
和浏览图一样，主题图无法编辑，但是你可以定制查询内容(这样可以更新图)。
Topic diagrams — like Browse diagrams — cannot be edited, but you can customize the query (which causes the diagram to refresh).
查询驱动图而非手动绘制图的使用，能够降低可能发生的与图相关的合并冲突的数量。
The use of query-driven diagrams instead of hand-drawn diagrams can reduce the number of diagram-related merge conflicts that might otherwise occur.
与后台图一样，命名图可以在查询内部用FROMNAMED指定，在这里，是通过uri来指定图。
As with the background graph, named graphs can be specified within the query itself, using FROM named, where URI specifies the graph.
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