Jena / ARQ：模型，图形和数据集之间的差异 [英] Jena/ARQ: Difference between Model, Graph and DataSet

问题描述

我开始使用Jena Engine，我想我已经掌握了语义是什么。
但是我很难理解在Jena和ARQ中代表一堆三元组的不同方式：

I'm starting to work with the Jena Engine and I think I got a grasp of what semantics are. However I'm having a hard time understanding the different ways to represent a bunch of triples in Jena and ARQ:

• 你开始时偶然发现的第一件事是 Model ，文档说明它的Jenas名称为RDF图。


• 但是还有 Graph 这似乎是我想查询模型联合的必要工具，但它似乎与 Model ，虽然可以从模型中获得 Graph


• 然后在ARQ中有 DataSet ，它似乎也是某种三元组的集合。

• The first thing you stumble upon when starting is Model and the documentation says its Jenas name for RDF graphs.
• However there is also Graph which seemed to be the necessary tool when I want to query a union of models, however it does not seem to share a common interface with Model, although one can get the Graph out of a Model
• Then there is DataSet in ARQ, which also seems to be a collection of triples of some sort.

当然，有些人在API中查找，我找到了以某种方式从一个转换为另一个的方法。但是我怀疑它有3个不同的界面可以用于同样的事情。

Sure, afer some looking around in the API, I found ways to somehow convert from one into another. However I suspect there is more to it than 3 different interfaces for the same thing.

所以，问题是：这三者之间的关键设计差异是什么？我什么时候应该使用哪一个？特别是：当我想要保持单个三元组但是将它们视为一大堆（联合）时，我应该使用哪些数据结构（以及为什么）？
另外，当我从一个转换到另一个时，我松散任何东西（例如 model.getGraph（）包含的信息少于 model ）？

So, question is: What are the key design differences between these three? When should I use which one ? Especially: When I want to hold individual bunches of triples but query them as one big bunch (union), which of these datastructures should I use (and why)? Also, do I "loose" anything when "converting" from one into another (e.g. does model.getGraph() contain less information in some way than model)?

推荐答案

Jena分为API，面向应用程序开发人员，以及用于系统开发人员的SPI，例如制作存储引擎，reasoners等的人。

Jena is divided into an API, for application developers, and an SPI for systems developers, such as people making storage engines, reasoners etc.

DataSet ，型号，声明，资源和 Literal 是API接口，为应用程序开发人员提供了许多便利。

DataSet, Model, Statement, Resource and Literal are API interfaces and provide many conveniences for application developers.

DataSetGraph ， Graph ， Triple ， Node 是SPI接口。它们非常简洁，易于实现（如果你必须实现这些东西，你希望如此）。

DataSetGraph, Graph, Triple, Node are SPI interfaces. They're pretty spartan and simple to implement (as you'd hope if you've got to implement the things).

各种各样的API操作都解决了到SPI电话。举例来说， Model interface 有四种不同的包含方法。每个内部都会产生一个调用：

The wide variety of API operations all resolve down to SPI calls. To give an example the Model interface has four different contains methods. Internally each results in a call:

Graph#contains(Node, Node, Node)

例如

graph.contains(nodeS, nodeP, nodeO); // model.contains(s, p, o) or model.contains(statement)
graph.contains(nodeS, nodeP, Node.ANY); // model.contains(s, p)

关于丢失信息的问题，模型和图形你没有（据我记得）。更有趣的情况是资源与节点。 资源知道它们属于哪个模型，这样你就可以（在api中）写 resource.addProperty（...）最终成为 Graph #add 。 节点没有这样的便利，并且与特定的 Graph 无关。因此资源#asNode 是有损的。

Concerning your question about losing information, with Model and Graph you don't (as far as I recall). The more interesting case is Resource versus Node. Resources know which model they belong to, so you can (in the api) write resource.addProperty(...) which becomes a Graph#add eventually. Node has no such convenience, and is not associated with a particular Graph. Hence Resource#asNode is lossy.

最后：

当我想要保存单个三元组但是将它们作为一大堆（联合）查询时，我应该使用哪些数据结构（以及为什么）？

When I want to hold individual bunches of triples but query them as one big bunch (union), which of these datastructures should I use (and why)?

您显然是普通用户，因此您需要API。您想存储三元组，因此请使用模型。现在您要将模型作为一个联合查询：您可以：

You're clearly a normal user, so you want the API. You want to store triples, so use Model. Now you want to query the models as one union: You could:

• Model＃union（）所有内容，它会将所有三元组复制到一个新模型中。


• ModelFactory.createUnion（）所有内容，创建动态联合（即不复制）。


• 将模型作为命名模型存储在TDB或SDB数据集存储中，并使用 unionDefaultGraph 选项。

• Model#union() everything, which will copy all the triples into a new model.
• ModelFactory.createUnion() everything, which will create a dynamic union (i.e. no copying).
• Store your models as named models in a TDB or SDB dataset store, and use the unionDefaultGraph option.

这些最后一个适用于大量模型和大型模型，但更多涉及到设置。

The last of these works best for large numbers of models, and large model, but is a little more involved to set up.

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