#APACHE LUCENE ARCHITECTURE HOW TO#
#APACHE LUCENE ARCHITECTURE CODE#

The query parser has three layers and its core is what we call the QueryNode tree. It allows to write a parser with a new syntax, while reusing the underlying semantics, as quickly as possible.

#APACHE LUCENE ARCHITECTURE HOW TO#

whether and how to tokenize/lemmatize/normalize the different terms or which Query objects to create for the terms. It distinguishes the semantics of the different query components, e.g. 'a AND b', '+a +b', 'AND(a,b)' could be different syntaxes for the same query. The new query parser goal is to separate syntax and semantics of a query.

#APACHE LUCENE ARCHITECTURE CODE#

This code is much more flexible and extensible than the Lucene query parser in 2.4.X. This new query parser was designed to have very generic architecture, so that it can be easily used for different products with varying query syntaxes. QueryNode tree's can be converted to a lucene 2.4 syntax string, using ToQueryString() Supported conversion is using a 2.4 compatible logic Standard Builders - convert QueryNode's into several lucene Processors Pipelines - Select your favorite ProcessorĪnd build a processor pipeline, to implement the features you needĬonfig Interfaces - Allow the consumer of the Query Parser to implementĪ diff Config Handler Objects to suite their needs. QueryNode Processors - Optimize, validate, rewrite the That can be converted into similar syntax QueryNode trees.

QueryNode Trees - support for several syntaxes,

.Standard: it contains the current Lucene query parser implementation using the new query parser API.įull support for boolean logic (not enabled).

.Core: it contains the query parser API classes, which should be extended by query parser implementations.

It's currently divided in 2 main namespaces:

This project contains the new Lucene query parser implementation, which matches the syntax of the core QueryParser but offers a more modular architecture to enable customization. QueryParser which permits complex phrase query syntax eg '(john jon jonathan~) peters*' ExtendableĮxtendable QueryParser provides a simple and flexible extension mechanism by overloading query field names. QueryParser that passes Fuzzy-, Prefix-, Range-, and WildcardQuerys through the given analyzer. The Lucene query language allows the user to specify which field(s) to search on, which fields to give more weight to (boosting), the ability to perform boolean queries (AND, OR, NOT) and other functionality.This module provides a number of queryparsers:Ī Simple Lucene QueryParser implemented with JavaCC. Lucene has its own mini-language for performing searches. It involves creating a Query (usually via a QueryParser) and handing this Query to an IndexSearcher, which returns a list of Hits. Searching requires an index to have already been built. Indexing in Lucene thus involves creating Documents comprising of one or more Fields, and adding these Documents to an IndexWriter. In the case of a title Field, the field name is title and the value is the title of that content item. For example, a Field commonly found in applications is title. For example, if you're creating a Lucene index of a database table of users, then each user would be represented in the index as a Lucene Document.Ī Document consists of one or more Fields. Indexing involves adding Documents to an IndexWriter, and searching involves retrieving Documents from an index via an IndexSearcher.Ī Lucene Document doesn't necessarily have to be a document in the common English usage of the word. In Lucene, a Document is the unit of search and index.Īn index consists of one or more Documents. This type of index is called an inverted index, because it inverts a page-centric data structure (page->words) to a keyword-centric data structure (word->pages). This would be the equivalent of retrieving pages in a book related to a keyword by searching the index at the back of a book, as opposed to searching the words in each page of the book. Lucene is able to achieve fast search responses because, instead of searching the text directly, it searches an index instead. The content you add to Lucene can be from various sources, like a SQL/NoSQL database, a filesystem, or even from websites. It then allows you to perform queries on this index, returning results ranked by either the relevance to the query or sorted by an arbitrary field such as a document's last modified date. It does so by adding content to a full-text index. Lucene is a full-text search library in Java which makes it easy to add search functionality to an application or website.

Apache lucene architecture