![]() ![]() I will discuss about how to Index data to make it searchable and how to search Lucene indexed data in subsequent posts. The below image demonstrates various stages/phases in building an application using Lucene. Steps to build an Application using Apache Lucene: Allows searching and indexing simultaneously.Uses a file-based locking mechanism to prevent concurrent index modifications.Allows users to extend the searching behavior using custom sorting, filtering, and query expression parsing.Supports parsing of human-entered rich query expressions.Supports many powerful query types, such as PhraseQuery, WildcardQuery, RangeQuery, FuzzyQuery, BooleanQuery, and more.Calculates a score for each document that matches a given query and returns the most relevant documents ranked by the scores.Has powerful, accurate, and efficient search algorithms.Web sites like Wikipedia, LinkedIn have been powered by Lucene. It can be used to build search capabilities for applications such as e-mail clients, mailing lists, Web searches, database search, etc. Lucene is an open source, highly scalable text search-engine library available from the Apache Software Foundation. Lucene’s powerful APIs focus mainly on text indexing and searching. Package Text Search using Apache Lucene (Part-I) Here is how we would do the indexing using above created code: The plugin also allows for fuzzy searches which allows users to find products they are looking for even if search terms are not spelled correctly. This plugin allows you override the default search and autocomplete functionality. Later we would create the Indexer object and invoke createIndex method to create the index. Increase the effectiveness of nopCommerce search by using Apache Lucene.NET full-text search engine. I have added only one TextField to keep the example simple. Each Document consist of multiple fields. The Document is Lucene provided class, we create Document objects and pass to indexWriter object. The createIndex method actually creates the index using indexWriter and data (given in the form to Document objects). So StandardAnalyzer is very helpful for common search cases. So keyword identification is required before the indexing process.Īpache Lucene provide different type of Analyzers and mechanism to plug custom Analyzers, StandardAnalyzer extract tokens out of the text, lower case the tokens, eliminates common words and punctuations, etc. For example, if you see a index at the end of a book, its contains keywords used in the book. Without Analyzer, IndexWriter can't create the index. Analyzer helps to create right tokens or keywords from given text. The constructor instantiate IndexWriter object that is used to create index. Public Indexer(String indexerDirectoryPath) throws Exception ĭocument.add(new TextField("title", title, Store.YES)) So lets first create an index of some data: Then we run the search operation on that index. To search something using Apache Lucene, we need to create an index of data. ![]() In this article we want to achieve same functioanlity using Lucene search engine library. In result Google has highlighted these terms in URL and description. Lucene provides a number of advanced capabilities out of the box, and can be extended to accomodate special needs. Notice, there are three query terms: java, inheritance and bitspedia. The Lucene text search engine library (from the Apache Jakarta project) provides fast and flexible search capabilities that can be easily integrated into many kinds of applications. ![]()
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