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tantivy/examples/html/simple_search.html
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<h1>simple_search.rs</h1>
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<div class="content"><div class='highlight'><pre><span class="hljs-keyword">extern</span> <span class="hljs-keyword">crate</span> rustc_serialize;
<span class="hljs-keyword">extern</span> <span class="hljs-keyword">crate</span> tantivy;
<span class="hljs-keyword">extern</span> <span class="hljs-keyword">crate</span> tempdir;
<span class="hljs-keyword">use</span> std::path::Path;
<span class="hljs-keyword">use</span> tempdir::TempDir;
<span class="hljs-keyword">use</span> tantivy::Index;
<span class="hljs-keyword">use</span> tantivy::schema::*;
<span class="hljs-keyword">use</span> tantivy::collector::TopCollector;
<span class="hljs-keyword">use</span> tantivy::query::QueryParser;
<span class="hljs-function"><span class="hljs-keyword">fn</span> <span class="hljs-title">main</span></span>() {</pre></div></div>
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<p>Lets create a temporary directory for the
sake of this example</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">if</span> <span class="hljs-keyword">let</span> <span class="hljs-literal">Ok</span>(dir) = TempDir::new(<span class="hljs-string">"tantivy_example_dir"</span>) {
run_example(dir.path()).unwrap();
dir.close().unwrap();
}
}
<span class="hljs-function"><span class="hljs-keyword">fn</span> <span class="hljs-title">run_example</span></span>(index_path: &amp;Path) -&gt; tantivy::<span class="hljs-built_in">Result</span>&lt;()&gt; {</pre></div></div>
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<h1 id="defining-the-schema">Defining the schema</h1>
<p>The Tantivy index requires a very strict schema.
The schema declares which fields are in the index,
and for each field, its type and “the way it should
be indexed”.</p>
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<p>first we need to define a schema …</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> <span class="hljs-keyword">mut</span> schema_builder = SchemaBuilder::<span class="hljs-keyword">default</span>();</pre></div></div>
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<p>Our first field is title.
We want full-text search for it, and we want to be able
to retrieve the document after the search.</p>
<p>TEXT | STORED is some syntactic sugar to describe
that.</p>
<p><code>TEXT</code> means the field should be tokenized and indexed,
along with its term frequency and term positions.</p>
<p><code>STORED</code> means that the field will also be saved
in a compressed, row-oriented key-value store.
This store is useful to reconstruct the
documents that were selected during the search phase.</p>
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<div class="content"><div class='highlight'><pre> schema_builder.add_text_field(<span class="hljs-string">"title"</span>, TEXT | STORED);</pre></div></div>
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<p>Our first field is body.
We want full-text search for it, and we want to be able
to retrieve the body after the search.</p>
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<div class="content"><div class='highlight'><pre> schema_builder.add_text_field(<span class="hljs-string">"body"</span>, TEXT);
<span class="hljs-keyword">let</span> schema = schema_builder.build();</pre></div></div>
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<h1 id="indexing-documents">Indexing documents</h1>
<p>Lets create a brand new index.</p>
<p>This will actually just save a meta.json
with our schema in the directory.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> index = <span class="hljs-built_in">try!</span>(Index::create(index_path, schema.clone()));</pre></div></div>
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<p>To insert document we need an index writer.
There must be only one writer at a time.
This single <code>IndexWriter</code> is already
multithreaded.</p>
<p>Here we use a buffer of 50MB per thread. Using a bigger
heap for the indexer can increase its throughput.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> <span class="hljs-keyword">mut</span> index_writer = <span class="hljs-built_in">try!</span>(index.writer(<span class="hljs-number">50_000_000</span>));</pre></div></div>
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<p>Lets index our documents!
We first need a handle on the title and the body field.</p>
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<h3 id="create-a-document-manually-">Create a document “manually”.</h3>
<p>We can create a document manually, by setting the fields
one by one in a Document object.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> title = schema.get_field(<span class="hljs-string">"title"</span>).unwrap();
<span class="hljs-keyword">let</span> body = schema.get_field(<span class="hljs-string">"body"</span>).unwrap();
<span class="hljs-keyword">let</span> <span class="hljs-keyword">mut</span> old_man_doc = Document::<span class="hljs-keyword">default</span>();
old_man_doc.add_text(title, <span class="hljs-string">"The Old Man and the Sea"</span>);
old_man_doc.add_text(body,
<span class="hljs-string">"He was an old man who fished alone in a skiff in the Gulf Stream and \
he had gone eighty-four days now without taking a fish."</span>);</pre></div></div>
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<p>… and add it to the <code>IndexWriter</code>.</p>
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<div class="content"><div class='highlight'><pre> index_writer.add_document(old_man_doc);</pre></div></div>
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<h3 id="create-a-document-directly-from-json-">Create a document directly from json.</h3>
<p>Alternatively, we can use our schema to parse
a document object directly from json.</p>
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<span class="hljs-keyword">let</span> mice_and_men_doc = <span class="hljs-built_in">try!</span>(schema.parse_document(r#<span class="hljs-string">"{
"</span>title<span class="hljs-string">": "</span>Of Mice and Men<span class="hljs-string">",
"</span>body<span class="hljs-string">": "</span>few miles south of Soledad, the Salinas River drops <span class="hljs-keyword">in</span> close to the hillside bank and runs deep and green. The water is warm too, <span class="hljs-keyword">for</span> it has slipped twinkling over the yellow sands <span class="hljs-keyword">in</span> the sunlight before reaching the narrow pool. On one side of the river the golden foothill slopes curve up to the strong and rocky Gabilan Mountains, but on the valley side the water is lined with trees—willows fresh and green with every spring, carrying <span class="hljs-keyword">in</span> their lower leaf junctures the debris of the winters flooding; and sycamores with mottled, white,recumbent limbs and branches that arch over the pool<span class="hljs-string">"
}"</span>#));
index_writer.add_document(mice_and_men_doc);</pre></div></div>
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<p>Multi-valued field are allowed, they are
expressed in JSON by an array.
The following document has two titles.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> frankenstein_doc = <span class="hljs-built_in">try!</span>(schema.parse_document(r#<span class="hljs-string">"{
"</span>title<span class="hljs-string">": ["</span>Frankenstein<span class="hljs-string">", "</span>The Modern Promotheus<span class="hljs-string">"],
"</span>body<span class="hljs-string">": "</span>You will rejoice to hear that no disaster has accompanied the commencement of an enterprise which you have regarded with such evil forebodings. I arrived here yesterday, and my first task is to assure my dear sister of my welfare and increasing confidence <span class="hljs-keyword">in</span> the success of my undertaking.<span class="hljs-string">"
}"</span>#));
index_writer.add_document(frankenstein_doc);</pre></div></div>
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<p>This is an example, so we will only index 3 documents
here. You can check out tantivys tutorial to index
the English wikipedia. Tantivys indexing is rather fast.
Indexing 5 million articles of the English wikipedia takes
around 4 minutes on my computer!</p>
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<h3 id="committing">Committing</h3>
<p>At this point our documents are not searchable.</p>
<p>We need to call .commit() explicitly to force the
index_writer to finish processing the documents in the queue,
flush the current index to the disk, and advertise
the existence of new documents.</p>
<p>This call is blocking.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-built_in">try!</span>(index_writer.commit());</pre></div></div>
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<p>If <code>.commit()</code> returns correctly, then all of the
documents that have been added are guaranteed to be
persistently indexed.</p>
<p>In the scenario of a crash or a power failure,
tantivy behaves as if has rolled back to its last
commit.</p>
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<h1 id="searching">Searching</h1>
<p>Lets search our index. Start by reloading
searchers in the index. This should be done
after every commit().</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-built_in">try!</span>(index.load_searchers());</pre></div></div>
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<p>Afterwards create one (or more) searchers.</p>
<p>You should create a searcher
every time you start a “search query”.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> searcher = index.searcher();</pre></div></div>
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<p>The query parser can interpret human queries.
Here, if the user does not specify which
field they want to search, tantivy will search
in both title and body.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> query_parser = QueryParser::new(index.schema(), <span class="hljs-built_in">vec!</span>[title, body]);</pre></div></div>
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<p>QueryParser may fail if the query is not in the right
format. For user facing applications, this can be a problem.
A ticket has been opened regarding this problem.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> query = <span class="hljs-built_in">try!</span>(query_parser.parse_query(<span class="hljs-string">"sea whale"</span>));</pre></div></div>
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<p>A query defines a set of documents, as
well as the way they should be scored.</p>
<p>A query created by the query parser is scored according
to a metric called Tf-Idf, and will consider
any document matching at least one of our terms.</p>
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<h3 id="collectors">Collectors</h3>
<p>We are not interested in all of the documents but
only in the top 10. Keeping track of our top 10 best documents
is the role of the TopCollector.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> <span class="hljs-keyword">mut</span> top_collector = TopCollector::with_limit(<span class="hljs-number">10</span>);</pre></div></div>
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<p>We can now perform our query.</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-built_in">try!</span>(searcher.search(&amp;*query, &amp;<span class="hljs-keyword">mut</span> top_collector));</pre></div></div>
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<p>Our top collector now contains the 10
most relevant doc ids…</p>
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<div class="content"><div class='highlight'><pre> <span class="hljs-keyword">let</span> doc_addresses = top_collector.docs();</pre></div></div>
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<p>The actual documents still need to be
retrieved from Tantivys store.</p>
<p>Since the body field was not configured as stored,
the document returned will only contain
a title.</p>
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<span class="hljs-keyword">for</span> doc_address <span class="hljs-keyword">in</span> doc_addresses {
<span class="hljs-keyword">let</span> retrieved_doc = <span class="hljs-built_in">try!</span>(searcher.doc(&amp;doc_address));
<span class="hljs-built_in">println!</span>(<span class="hljs-string">"{}"</span>, schema.to_json(&amp;retrieved_doc));
}
<span class="hljs-literal">Ok</span>(())
}</pre></div></div>
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