The Zend_Search_Lucene_Analysis_Analyzer class is used by the indexer to tokenize document text fields.

The Zend_Search_Lucene_Analysis_Analyzer::getDefault() and Zend_Search_Lucene_Analysis_Analyzer::setDefault() methods are used to get and set the default analyzer.

You can assign your own text analyzer or choose it from the set of predefined analyzers: Zend_Search_Lucene_Analysis_Analyzer_Common_Text and Zend_Search_Lucene_Analysis_Analyzer_Common_Text_CaseInsensitive (default). Both of them interpret tokens as sequences of letters. Zend_Search_Lucene_Analysis_Analyzer_Common_Text_CaseInsensitive converts all tokens to lower case.

To switch between analyzers:

The Zend_Search_Lucene_Analysis_Analyzer_Common class is designed to be an ancestor of all user defined analyzers. User should only define the reset() and nextToken() methods, which takes its string from the $_input member and returns tokens one by one (a NULL value indicates the end of the stream).

The nextToken() method should call the normalize() method on each token. This will allow you to use token filters with your analyzer.

Here is an example of a custom analyzer, which accepts words with digits as terms:

The Zend_Search_Lucene_Analysis_Analyzer_Common analyzer also offers a token filtering mechanism.

The Zend_Search_Lucene_Analysis_TokenFilter class provides an abstract interface for such filters. Your own filters should extend this class either directly or indirectly.

Any custom filter must implement the normalize() method which may transform input token or signal that the current token should be skipped.

There are three filters already defined in the analysis subpackage:

• Zend_Search_Lucene_Analysis_TokenFilter_LowerCase

• Zend_Search_Lucene_Analysis_TokenFilter_ShortWords

• Zend_Search_Lucene_Analysis_TokenFilter_StopWords

The LowerCase filter is already used for Zend_Search_Lucene_Analysis_Analyzer_Common_Text_CaseInsensitive analyzer by default.

The ShortWords and StopWords filters may be used with pre-defined or custom analyzers like this:

The Zend_Search_Lucene_Analysis_TokenFilter_StopWords constructor takes an array of stop-words as an input. But stop-words may be also loaded from a file:

This file should be a common text file with one word in each line. The '#' character marks a line as a comment.

The Zend_Search_Lucene_Analysis_TokenFilter_ShortWords constructor has one optional argument. This is the word length limit, set by default to 2.

The score of a document d for a query q is defined as follows:

score(q,d) = sum( tf(t in d) * idf(t) * getBoost(t.field in d) * lengthNorm(t.field in d) ) * coord(q,d) * queryNorm(q)

tf(t in d) - Zend_Search_Lucene_Search_Similarity::tf($freq) - a score factor based on the frequency of a term or phrase in a document.

idf(t) - Zend_Search_Lucene_Search_Similarity::idf($input, $reader) - a score factor for a simple term with the specified index.

getBoost(t.field in d) - the boost factor for the term field.

lengthNorm($term) - the normalization value for a field given the total number of terms contained in a field. This value is stored within the index. These values, together with field boosts, are stored in an index and multiplied into scores for hits on each field by the search code.

Matches in longer fields are less precise, so implementations of this method usually return smaller values when numTokens is large, and larger values when numTokens is small.

coord(q,d) - Zend_Search_Lucene_Search_Similarity::coord($overlap, $maxOverlap) - a score factor based on the fraction of all query terms that a document contains.

The presence of a large portion of the query terms indicates a better match with the query, so implementations of this method usually return larger values when the ratio between these parameters is large and smaller values when the ratio between them is small.

queryNorm(q) - the normalization value for a query given the sum of the squared weights of each of the query terms. This value is then multiplied into the weight of each query term.

This does not affect ranking, but rather just attempts to make scores from different queries comparable.

The scoring algorithm can be customized by defining your own Similarity class. To do this extend the Zend_Search_Lucene_Search_Similarity class as defined below, then use the Zend_Search_Lucene_Search_Similarity::setDefault($similarity); method to set it as default.

The abstract class Zend_Search_Lucene_Storage_Directory defines directory functionality.

The Zend_Search_Lucene constructor uses either a string or a Zend_Search_Lucene_Storage_Directory object as an input.

The Zend_Search_Lucene_Storage_Directory_Filesystem class implements directory functionality for a file system.

If a string is used as an input for the Zend_Search_Lucene constructor, then the index reader (Zend_Search_Lucene object) treats it as a file system path and instantiates the Zend_Search_Lucene_Storage_Directory_Filesystem object.

You can define your own directory implementation by extending the Zend_Search_Lucene_Storage_Directory class.

Zend_Search_Lucene_Storage_Directory methods:

The getFileObject($filename) method of a Zend_Search_Lucene_Storage_Directory instance returns a Zend_Search_Lucene_Storage_File object.

The Zend_Search_Lucene_Storage_File abstract class implements file abstraction and index file reading primitives.

You must also extend Zend_Search_Lucene_Storage_File for your directory implementation.

Only two methods of Zend_Search_Lucene_Storage_File must be overridden in your implementation: