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The following page has been changed by Lance Norskog: http://wiki.apache.org/solr/SchemaDesign ------------------------------------------------------------------------------ }}} There may be performance differences with this technique v.s. the Lucene sorting algorithm. = Multiple Text Search Field types = - The "text" field type in the example schema.xml provides basic text search for English text. But, it has a surprise: the actual text given to this field is not indexed as-is, and therefore searching for the raw text may not work. If you store "To Be Or Not To Be" in a "text" field, none of these words will found this document, nor will the phrase in quotes. The above words are all ''stopwords'' and are stripped from the input text. Another transform is ''stemming'', which stores both 'change' and 'changing' into 'chang'. + The "text" field type in the example schema.xml provides basic text search for English text. But, it has a surprise: the actual text given to this field is not indexed as-is, and therefore searching for the raw text may not work. If you store "To Be Or Not To Be" in a "text" field, none of these words will found this document, nor will the phrase in quotes. The above words are all ''stopwords'' and are stripped from the input text. Another transform is ''stemming'', which stores both 'change' and 'changing' as the word 'chang'. == Phrase search == - If you want to have any phrase search work as well as individual words, you need to have two fields. Both should be processed similarly, but the phrase search field should not use stemming or stopword". + If you want to have any phrase search work as well as individual words, you need to have two fields. Both should be processed similarly, but the phrase search field should not use stemming or stopwords. == Phonemes == Programmers are perfect spellers and expect the same of their users. A ''phoneme'' represents (roughly) the sound of one syllable. Phoneme-based searching can give users a better search experience. To support misspelled search words phoneme filters cause the index to store phoneme-base representations of the text instead of the input. This only finds misspellings which sound like the original word.
