Tag: lucene

In my previous post (Lucene.Net Object Mapping) I introduced the Lucene.Net.ObjectMapping NuGet package. The post describes how the package can be used to map virtually any .Net object to a Lucene.Net Document and how to reconstruct the object from that same Document later. Now it’s time to look at the search aspect of it, so how can you search mapped objects in Lucene.Net?

You already know Searcher

The Searcher class in Lucene.Net can be used to run queries on an index and retrieve documents matching that query. The Lucene.Net.ObjectMapping library comes with additional extensions to the Searcher class which help you search for Documents. There’s a variety of different extensions, some which just return a TopDocs object with the number of results you’ve specified, and some which allow sorting, but more powerful are the ones which require you to specify a Collector to gather the results. Using a Collector makes it very easy to support paging over all the results for a specific query, and after all that’s usually what you’d do today if you want to show search results. So let’s look at an example of searching for Documents that contain mapped .Net objects using a Collector. Let’s assume we’re building a blog engine, for which we want to index the posts.

public class BlogPost
{
    public Guid Id { get; set; }
    public DateTime Created { get; set; }
    public string Title { get; set; }
    public string Body { get; set; }
    public string[] Tags { get; set; }
}

// ... as before, you'd store your BlogPost objects like this:
luceneIndexWriter.AddDocument(thePost.ToDocument());

Use a Collector for Paging

Creating an paged index of all your blog posts is very easy, really. You’ll need a Searcher, a Collector (the TopFieldCollector will do for now) and that’s about it. Let’s look at some code.

private const int PageSize = 10;

public BlogPost[] GetPostsForPage(int page)
{
    // Sanitize the 'page' before doing anything with it.
    if (page < 0)
    {
        page = 0;
    }

    int start = page * PageSize;
    int end = start + PageSize;

    using (Searcher searcher = new IndexSearcher(myIndexReader))
    {
        TopFieldCollector collector = TopFieldCollector.Create(
            // Let's sort descending by create date.
            new Sort(new SortField("Created", SortField.LONG, true)),
            end, // Need to get the hits until 'end'.
            false,
            false,
            false,
            false);

        // Let's use the object mapping extensions for Search! This will
        // filter results to only those Documents which hold a BlogPost.
        searcher.Search<BlogPost>(new MatchAllDocsQuery(), collector);

        // At this point we know how many hits there are in total. So
        // let's check that the requested page is within range.
        if (start >= collector.TotalHits)
        {
            page = (collector.TotalHits - 1) / PageSize;
            start = page.Value * PageSize;
            end = start + PageSize;
        }

        TopDocs docs = collector.TopDocs(start, PageSize);
        List<BlogPost> posts = new List<BlogPost>();

        foreach (ScoreDoc scoreDoc in docs.ScoreDocs)
        {
            Document doc = searcher.Doc(scoreDoc.Doc);

            posts.Add(doc.ToObject<BlogPost>());
        }

        return posts.ToArray();
    }
}

That’s it, no magic, no tricks. One thing you could do, instead of just returning a plain array with the results is to return an object which holds some more meta information, like for instance the number of total hits, or the actual page you’re returning results for. But the core logic remains the same. You can play around with different ways to sort the results. Keep in mind though that tokenized/analyzed fields in Lucene.Net are sorted based on the tokens, not based on the actual string value. To help address this, I’m thinking about extending the object mappers to allow to specify not only to analyze a field (because you want to search it), but also to add a non-analyzed copy of the field for sorting purposes. That way, you have the advantage of being able to search and sort on the same logical field in the end. Keep in mind though that the index will grow since the data is indexed twice: once tokenized/analyzed, once as-is.

Today I finally took some time to turn a little library I’ve used for a while now into a NuGet package, called Lucene.Net.ObjectMapping. At the same time, I also uploaded the code to GitHub. But let’s look at Lucene.Net Object Mapping in more detail.

How To Install

Since this is a NuGet package, installation is as simple as running the following command in the Package Manager Console

Install-Package Lucene.Net.ObjectMapping

Alternatively, you can just search for Lucene.Net.ObjectMapping in the package manager and you should find it.

How To Use It?

Using object mapping is as simple as calling two methods: ToDocument to convert an object into a document and ToObject to convert a Document (that was created with the ToDocument method) into the original object.

MyObject obj = ...;
Document doc = obj.ToDocument();
// Save the document to your Lucene.Net Index

// Later, load the document from the index again
Document docFromIndex = ...;
MyObject objFromDoc = docFromIndex.ToObject<MyObject>();

How does it work?

Under the covers, the library is JSON-serializing the object and stores the JSON in the actual Lucene.Net document. In addition, it stores some metadata like the actual and the static types of the object you stored, as well as the timestamp (ticks) of when the document was created. The type information is used when you search for documents that were created for a specific type. The static type is the type you pass in as the type parameter to ToDocument, whereas the actual type is the actual (dynamic) type of the object you’re passing in. Since all this information is stored in the document too, there are no issues re-creating objects from an class hierarchy too.
In addition to storing the object information itself, the library also indexes the individual properties of the object you’re storing, including nested properties. By default, it uses a mapper which works as follows.

• Public properties/fields of objects are mapped to Lucene.Net fields with the same name; e.g. a property called “Id” is mapped to a field called “Id”.
• Properties/fields that are arrays are mapped to multiple Lucene.Net fields, all with the same name (the name of the property that holds the array).
• Nested properties/fields, i.e. objects from properties/fields, use the name of the property as a prefix for the properties/fields of the object.

Each field is created with the following mapping of field types:

• Boolean properties are mapped to a numeric field (Int) with a value of 1 for true and 0 for false.
• DateTime properties are mapped to a numeric field (Long) with the value being the Ticks property of the DateTime.
• Float properties are mapped to a numeric field (Float) with the value being the float value.
• Double and Decimal properties are mapped to a numeric field (Double) with the value being the double value.
• Guid properties are mapped to string fields which are NOT_ANALYZED, i.e. you can search for the GUID as is.
• Integer (also Long, Short, and Byte as well as their unsigned/signed counterparts) properties are mapped to a numeric field (Long) with the value being the integer value.
• Null values are not mapped at all; thus, the absence of a field implies the corresponding property is null.
• String properties are mapped to string fields which are ANALYZED.
• TimeSpan properties are mapped to a numeric field (Long) with the value being the Ticks property of the TimeSpan.
• Uri properties are mapped to string fields which are ANALYZED.

Example Mapping

Let’s look at a simple example of an object and its mapping to a Lucene.Net Document. Consider the following object model.

public class MyObject
{
    public int Id { get; set; }
    public string Name { get; set; }
    public ObjectMeta Meta { get; set; }
}

public class ObjectMeta
{
    public DateTime LastModified { get; set; }
    public string ModifiedBy { get; set; }
    public string[] Modifications { get; set; }
}

// Create an instance of MyObject
MyObject obj = new MyObject()
{
    Id = 1234,
    Name = "My Lucene.Net mapped Object",
    Meta = new ObjectMeta()
    {
        LastModified = DateTime.UtcNow,
        ModifiedBy = "the dude",
        Modifications = new string[] { "changed a", "removed b", "added c" },
    },
};

Document doc = obj.ToDocument();

The mapping rules called out above will add the following fields for searching to the document. Please note that I’m not calling out the fields needed for the internal workings of the Lucene.Net.ObjectMapping library.

The mapper is by no means complete. Ideas to extend it in the future exist, including functionality to

• specify attributes on string properties (or properties mapped to string fields) to specify how to index the string (NO vs ANALYZED vs NOT_ANALYZED vs NOT_ANALYZED_NO_NORMS vs ANALYZED_NO_NORMS).
• specify attributes on any properties to define how to map the field, e.g. by specifying a class which can map the field

I’ll talk a little more on how to use this all when searching for documents in your Lucene.Net index. But as a sneak preview: the library also provides extension methods to the Searcher class from Lucene.Net that you can use to specify an object type to filter your documents on.