blocks|key|1605243|text|在Java中，您可以使用RDF库以流的方式进行读/写，并执行一些基本的过滤。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1605244|例如，使用RDF4J的Rio解析器，您可以创建一个简单的SubjectFilter类，该类检查任何具有所需主题的三元组：|offset|length|style|CODE|1605245|public+class+SubjectFilter+extends+RDFHandlerWrapper+{

++++@Override
++++public+void+handleStatement(Statement+st)+throws+RDFHandlerException+{
+++++++//+only+write+the+statement+if+it+has+a+subject+we+want
+++++++if+(myListOfSubjects.contains(statement.getSubject())+{
++++++++++super.handleStatement(st);
+++++++}+
++++}
}|code-block|syntax|javascript|1605246|然后将解析器连接到编写器，编写器输出过滤后的内容，如下所示：|1605247|RDFParser+rdfParser+=+Rio.createParser(RDFFormat.TURTLE);
RDFWriter+rdfWriter+=+Rio.createWriter(RDFFormat.TURTLE,
+++++++++++++++new+FileOutputStream("/path/to/example-output.ttl"));

//+link+our+parser+to+our+writer,+wrapping+the+writer+in+our+subject+filter
rdfParser.setRDFHandler(new+SubjectFilter(rdfWriter));

//+start+processing
rdfParser.parse(new+FileInputStream("/path/to/input-file.ttl"),+"");+|1605248|有关如何使用RDF4J和Rio解析器的更多详细信息，请参阅documentation。|1605249|顺便说一句:虽然这可能比使用grep和awk之类的东西做一些命令行魔术的工作要多，但它的优点是它在语义上是健壮的:您将解释数据的哪一位是三元组的主题留给理解RDF的处理器，而不是通过regex进行有根据的猜测(“它可能是每行的第一个URL”)，这在输入文件使用稍微不同的语法变化的情况下可能会中断。|1605250|(披露:我在RDF4J开发团队)|1605251|entityMap|0|LINK|mutability|MUTABLE|url|http://rdf4j.org/|1|http://docs.rdf4j.org/^0|0|S|D|5|5|0|0|0|0|0|T|D|1|0|0|0^^$0|@$1|2|3|4|5|6|7|16|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|17|8|@$D|18|E|19|F|G]]|9|@$D|1A|E|1B|1|1C]]|A|$]]|$1|H|3|I|5|J|7|1D|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|1E|8|@]|9|@]|A|$]]|$1|O|3|P|5|J|7|1F|8|@]|9|@]|A|$K|L]]|$1|Q|3|R|5|6|7|1G|8|@]|9|@$D|1H|E|1I|1|1J]]|A|$]]|$1|S|3|T|5|6|7|1K|8|@]|9|@]|A|$]]|$1|U|3|V|5|6|7|1L|8|@]|9|@]|A|$]]|$1|W|3|-4|5|6|7|1M|8|@]|9|@]|A|$]]]|X|$Y|$5|Z|10|11|A|$12|13]]|14|$5|Z|10|11|A|$12|15]]]]

In Java, you could use an RDF library to read/write in streaming fashion and do some basic filtering.

For example, using <a href="http://rdf4j.org/" rel="nofollow noreferrer">RDF4J</a>'s Rio parser you could create a simple <code>SubjectFilter</code> class that checks for any triple if it has the required subject:

<pre class="lang-java prettyprint-override"><code>public class SubjectFilter extends RDFHandlerWrapper {

 @Override
 public void handleStatement(Statement st) throws RDFHandlerException {
 // only write the statement if it has a subject we want
 if (myListOfSubjects.contains(statement.getSubject()) {
 super.handleStatement(st);
 } 
 }
}
</code></pre>

And then connect a parser to a writer that spits out the filtered content, something along these lines:

<pre class="lang-java prettyprint-override"><code>RDFParser rdfParser = Rio.createParser(RDFFormat.TURTLE);
RDFWriter rdfWriter = Rio.createWriter(RDFFormat.TURTLE,
 new FileOutputStream("/path/to/example-output.ttl"));

// link our parser to our writer, wrapping the writer in our subject filter
rdfParser.setRDFHandler(new SubjectFilter(rdfWriter));

// start processing
rdfParser.parse(new FileInputStream("/path/to/input-file.ttl"), ""); 
</code></pre>

For more details on how to use RDF4J and the Rio parsers, see the <a href="http://docs.rdf4j.org/" rel="nofollow noreferrer">documentation</a>. 

As an aside: although this is perhaps more work than doing some command line magic with things like grep and awk, the advantage is that this is semantically robust: you leave interpretation of which bit of your data is the triple's subject to a processor that understands RDF, rather than taking an educated guess through regex ("it's probably the first URL on each line"), which may break in cases where the input file use a slightly different syntax variation. 

(disclosure: I am on the RDF4J development team)

I have a file containing triple RDF (subject-predicate-object) in the turtle syntax (.ttl), and I have another file in which I only have some subjects.

For example:

<pre><code>&lt;http://dbpedia.org/resource/AlbaniaHistory&gt; &lt;http://www.w3.org/2000/01/rdf-schema#label&gt; "AlbaniaHistory"@en .
&lt;http://dbpedia.org/resource/AsWeMayThink&gt; &lt;http://www.w3.org/2000/01/rdf-schema#label&gt; "AsWeMayThink"@en .
&lt;http://dbpedia.org/resource/AlbaniaEconomy&gt; &lt;http://www.w3.org/2000/01/rdf-schema#label&gt; "AlbaniaEconomy"@en .
&lt;http://dbpedia.org/resource/AlbaniaGovernment&gt; &lt;http://www.w3.org/2000/01/rdf-schema#label&gt; "AlbaniaGovernment"@en .
</code></pre>

And in the other file I have, for example:

<pre><code>&lt;http://dbpedia.org/resource/AlbaniaHistory&gt;
&lt;http://dbpedia.org/resource/AlbaniaGovernment&gt;
&lt;http://dbpedia.org/resource/Pérotin&gt;
&lt;http://dbpedia.org/resource/ArtificalLanguages&gt;
</code></pre>

I would like to get:

<pre><code>&lt;http://dbpedia.org/resource/AlbaniaHistory&gt; &lt;http://www.w3.org/2000/01/rdf-schema#label&gt; "AlbaniaHistory"@en .
&lt;http://dbpedia.org/resource/AlbaniaGovernment&gt; &lt;http://www.w3.org/2000/01/rdf-schema#label&gt; "AlbaniaGovernment"@en .
</code></pre>

So, I would like to remove from the first file the triples whose subjects are not in the second file. How could I get this?

I tried in java reading the contents of the second file in an arraylist and using the "contain" method to check if the subjects of each triple of the first file match any line in the second file, however it is too slow since the files are very big. How could I get this?

Thank you very much for helping

How to delete lines with specific subjects from an RDF file?

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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我有一个文件，其中包含使用turtle语法(.ttl)的三重RDF (主语-谓语-宾语)，还有一个文件，其中只有一些主语。例如：<http://dbpedia.org/resource/AlbaniaHistory> <http://www.w3.org/2000/01/rdf-schema#label> "Alban...

如何从RDF文件中删除具有特定主题的行？-腾讯云开发者社区-腾讯云

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