I originally published this post on my blog. It's part of a content collaboration with Alachisoft, NCache creators.
I bet you have used the SQL LIKE operator to find a keyword in a text field. For large amounts of text, that would be slow. Let's learn how to implement a full-text search with Lucene and NCache.
What is Full-Text Search?
Full-text search is a technique to search not only exact matches of a keyword in some text but for patterns of text, synonyms, or close words in large amounts of text.
To support large amounts of text, searching is divided into two phases: indexing and searching. In the indexing phase, an analyzer processes text to create indexes based on the rules of a spoken language like English to remove stop words and record synonyms and inflections of words. Then, the searching phase only uses the indexes instead of the original text source.
Full-Text Search with Lucene and NCache
1. Why Lucene and NCache?
From its official page, "Apache Lucene.NET is a high performance search library for .NET." It's a C# port of Java-based Apache Lucene, an "extremely powerful" and fast search library optimized for full-text search.
NCache gives distributed capabilities to Lucene by implementing the Lucene API on top of its In-Memory Distributed cache. This way, NCache makes Lucene a linearly scalable full-text searching solution for .NET. For more features of Distributed Lucene, check NCache Distributed Lucene page.
2. Create a Lucene Cache in NCache
We have already installed and used NCache as a IDistributedCache provider. This time, let's use NCache version 5.3 to find movies by title or director name using Lucene's full-text search.
Lucene stores data in immutable "segments," which consist of multiple files. We can store these segments in our local file system or in RAM. But, since we're using Lucene with NCache, we're storing these segments in NCache.
Before indexing and searching anything, first, we need to create a Distributed Lucene Cache. Let's navigate to http://localhost:8251 to fire NCache Web Manager and add a New Distributed Cache.
Let's select "Distributed Lucene" in the Store Type and give it a name. Then, let's add our own machine and a second node. For write operations, we need at least two nodes. We can stick to the defaults for the other options.
By default, NCache stores Lucene indexes in C:\ProgramData\ncache\lucene-index.
For more details about these installation options, check NCache official docs.
3. Index Some Movies
After creating the Distributed Lucene cache, let's populate our Lucene indexes with some movies from a Console app. Later, we will search them from another Console app.
First, let's create a Console app to load some movies to the Lucene Cache. Also, let's install the Lucene.Net.NCache NuGet package.
In the Program.cs file, we could load all movies we want to index from a database or another store. For example, let's use a list of movies from IMDb. Something like this,
using SearchMovies.Shared;
using SearchMovies.Shared.Entities;
using SearchMovies.Shared.Services;
var searchService = new SearchService(Config.CacheName);
searchService.LoadMovies(SomeMoviesFromImdb());
Console.WriteLine("Press any key to continue...");
Console.ReadKey();
// This list of movies was taken from IMDb dump
// See: https://www.imdb.com/interfaces/
static IEnumerable<Movie> SomeMoviesFromImdb()
{
return new List<Movie>
{
new Movie("Caged Fury", 1983, 3.8f, 89, new Director("Maurizio Angeloni", 1959), new []{ Genre.Crime,Genre.Drama }),
new Movie("Bad Posture", 2011, 6.5f, 93, new Director("Jack Smith", 1932), new []{ Genre.Drama,Genre.Romance }),
new Movie("My Flying Wife", 1991, 5.5f, 91, new Director("Franz Bi", 1899), new []{ Genre.Action,Genre.Comedy,Genre.Fantasy }),
new Movie("Modern Love", 1990, 5.2f, 105, new Director("Sophie Carlhian", 1962), new []{ Genre.Comedy }),
new Movie("Sins", 2012, 2.3f, 84, new Director("Pierre Huyghe", 1962), new []{ Genre.Action, Genre.Thriller })
// Some other movies here...
};
}
Notice we used a SearchService to handle the index creation in a method called LoadMovies(). Let's take a look at it.
using Lucene.Net.Analysis.Standard;
using Lucene.Net.Index;
using Lucene.Net.Store;
using Lucene.Net.Util;
using SearchMovies.Shared.Entities;
using SearchMovies.Shared.Extensions;
namespace SearchMovies.Shared.Services;
public class SearchService
{
private const string IndexName = "movies";
private const LuceneVersion luceneVersion = LuceneVersion.LUCENE_48;
private readonly string _cacheName;
public SearchService(string cacheName)
{
_cacheName = cacheName;
}
public void LoadMovies(IEnumerable<Movie> movies)
{
using var indexDirectory = NCacheDirectory.Open(_cacheName, IndexName);
// 1. Opening directory ^^^
var standardAnalyzer = new StandardAnalyzer(luceneVersion);
var indexConfig = new IndexWriterConfig(luceneVersion, standardAnalyzer)
{
OpenMode = OpenMode.CREATE
};
using var writer = new IndexWriter(indexDirectory, indexConfig);
// 2. Creating a writer ^^^
foreach (var movie in movies)
{
var doc = movie.MapToLuceneDocument();
writer.AddDocument(doc);
// 3. Adding a document
}
writer.Commit();
// 4. Writing documents
}
}
A bit of background first, Lucene uses documents as the unit of search and index. Documents can have many fields, and we don't need a schema to store them.
We can search documents using any field. Lucene will only return those with that field and matching data. For more details on some Lucene internals, check its Lucene Quick Start guide.
Notice we started our LoadMovies by opening an NCache directory. We needed the same cache name we configured before and an index name. Then we created an IndexWriter with our directory and some configurations, like a Lucene version, an analyzer, and an open mode.
Then, we looped through our movies and created a Lucene document for each one using the MapToLuceneDocument() extension method. Here it is,
using Lucene.Net.Documents;
using SearchMovies.Shared.Entities;
namespace SearchMovies.Shared.Extensions;
public static class MoviesExtensions
{
public static Document MapToLuceneDocument(this Movie self)
{
return new Document
{
new TextField("name", self.Name, Field.Store.YES),
new TextField("directorName", self.Director.Name, Field.Store.YES)
};
}
}
To create Lucene documents, we used two fields of type TextField: movie name and director name. For each field, we need a name and a value to index. We will use the field names later to create a response object from search results.
There are two basic field types for Lucene documents: TextField and StringField. The first one has support for Full-Text search and the second one supports searching for exact matches.
Once we called the Commit() method, NCache stored our movies in a distributed index.
4. Full-Text Searching Movies
Now that we populated our index with some movies, to search them, let's create another Console app to read a Lucene query.
Again, let's use the same SearchService, this time with a SearchByNames() method passing a Lucene query.
using Lucene.Net.Analysis.Standard;
using Lucene.Net.Index;
using Lucene.Net.QueryParsers.Classic;
using Lucene.Net.Search;
using Lucene.Net.Store;
using Lucene.Net.Util;
using SearchMovies.Shared.Entities;
using SearchMovies.Shared.Extensions;
using SearchMovies.Shared.Responses;
namespace SearchMovies.Shared.Services;
public class SearchService
{
// Same SearchService as before...
public IEnumerable<MovieResponse> SearchByNames(string searchQuery)
{
using var indexDirectory = NCacheDirectory.Open(_cacheName, IndexName);
using var reader = DirectoryReader.Open(indexDirectory);
// ^^^^^^^^^^^^^^^
// 1. Creating a reader
var searcher = new IndexSearcher(reader);
var analyzer = new StandardAnalyzer(luceneVersion);
var parser = new QueryParser(luceneVersion, "name", analyzer);
var query = parser.Parse(searchQuery);
// ^^^^^^
// 2. Parsing a Lucene query
var documents = searcher.Search(query, 10);
// 3. Searching documents
var result = new List<MovieResponse>();
for (int i = 0; i < documents.TotalHits; i++)
{
var document = searcher.Doc(documents.ScoreDocs[i].Doc);
result.Add(document.MapToMovieResponse());
// 4. Populating a result object
}
return result;
}
}
This time, instead of creating an IndexWriter, we used a DirectoryReader and a query parser with the same Lucene version and analyzer. Then, we used the Search() method with the parsed query and a result count. The next step was to loop through the results and create a response object.
To create a response object from a Lucene document, we used the MapToMovieResponse(). Here it is,
public static MovieResponse MapToMovieResponse(this Document self)
{
return new MovieResponse(self.Get("name"), self.Get("directorName"));
}
This time, we used the Get() method with the same field names as before to retrieve fields from documents.
For example, let's find all movies whose director's name contains "ca", with the query directorName:ca*,
Of course, there are more keywords in Lucene Query Syntaxt.
Voilà! That's how to use Distributed Lucene with NCache. If we already have an implementation with Lucene.NET, we would need few code changes to migrate it to Lucene with NCache. Also, notice that NCache doesn't implement all Lucene methods.
To follow along with the code we wrote in this post, check my Ncache Demo repository over on GitHub.
To read more content, check my post Working with ASP.NET Core IDistributedCache Provider for NCache to learn about caching with NCache and ASP.NET Core.
Happy coding!
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