Filter Descriptions

This filter converts alphabetic, numeric, and symbolic Unicode characters which are not in the Basic Latin Unicode block (the first 127 ASCII characters) to their ASCII equivalents, if one exists. This filter converts characters from the following Unicode blocks:

Factory class: solr.ASCIIFoldingFilterFactory

Arguments:

Example:

In: "á" (Unicode character 00E1)

Out: "a" (ASCII character 97)

Implements the Beider-Morse Phonetic Matching (BMPM) algorithm, which allows identification of similar names, even if they are spelled differently or in different languages. More information about how this works is available in the section on Phonetic Matching.

Factory class: solr.BeiderMorseFilterFactory

Arguments:

Example:

This filter takes the output of the Classic Tokenizer and strips periods from acronyms and "'s" from possessives.

Factory class: solr.ClassicFilterFactory

Arguments: None

Example:

In: "I.B.M. cat’s can’t"

Tokenizer to Filter: "I.B.M", "cat’s", "can’t"

Out: "IBM", "cat", "can’t"

This filter creates word shingles by combining common tokens such as stop words with regular tokens. This is useful for creating phrase queries containing common words, such as "the cat." Solr normally ignores stop words in queried phrases, so searching for "the cat" would return all matches for the word "cat."

Factory class: solr.CommonGramsFilterFactory

Arguments:

Example:

In: "the Cat"

Tokenizer to Filter: "the", "Cat"

Out: "the_cat"

Collation allows sorting of text in a language-sensitive way. It is usually used for sorting, but can also be used with advanced searches. We’ve covered this in much more detail in the section on Unicode Collation.

Implements the Daitch-Mokotoff Soundex algorithm, which allows identification of similar names, even if they are spelled differently. More information about how this works is available in the section on Phonetic Matching.

Factory class: solr.DaitchMokotoffSoundexFilterFactory

Arguments:

Example:

This filter creates tokens using the DoubleMetaphone encoding algorithm from commons-codec. For more information, see the Phonetic Matching section.

Factory class: solr.DoubleMetaphoneFilterFactory

Arguments:

Example:

Default behavior for inject (true): keep the original token and add phonetic token(s) at the same position.

In: "four score and Kuczewski"

Tokenizer to Filter: "four"(1), "score"(2), "and"(3), "Kuczewski"(4)

Out: "four"(1), "FR"(1), "score"(2), "SKR"(2), "and"(3), "ANT"(3), "Kuczewski"(4), "KSSK"(4), "KXFS"(4)

The phonetic tokens have a position increment of 0, which indicates that they are at the same position as the token they were derived from (immediately preceding). Note that "Kuczewski" has two encodings, which are added at the same position.

Example:

Discard original token (inject="false").

In: "four score and Kuczewski"

Tokenizer to Filter: "four"(1), "score"(2), "and"(3), "Kuczewski"(4)

Out: "FR"(1), "SKR"(2), "ANT"(3), "KSSK"(4), "KXFS"(4)

Note that "Kuczewski" has two encodings, which are added at the same position.

This filter generates edge n-gram tokens of sizes within the given range.

Factory class: solr.EdgeNGramFilterFactory

Arguments:

Example:

Default behavior.

In: "four score and twenty"

Tokenizer to Filter: "four", "score", "and", "twenty"

Out: "f", "s", "a", "t"

Example:

A range of 1 to 4.

In: "four score"

Tokenizer to Filter: "four", "score"

Out: "f", "fo", "fou", "four", "s", "sc", "sco", "scor"

Example:

A range of 4 to 6.

In: "four score and twenty"

Tokenizer to Filter: "four", "score", "and", "twenty"

Out: "four", "scor", "score", "twen", "twent", "twenty"

This filter stems plural English words to their singular form.

Factory class: solr.EnglishMinimalStemFilterFactory

Arguments: None

Example:

In: "dogs cats"

Tokenizer to Filter: "dogs", "cats"

Out: "dog", "cat"

This filter removes singular possessives (trailing 's) from words. Note that plural possessives, e.g., the s' in "divers' snorkels", are not removed by this filter.

Factory class: solr.EnglishPossessiveFilterFactory

Arguments: None

Example:

In: "Man’s dog bites dogs' man"

Tokenizer to Filter: "Man’s", "dog", "bites", "dogs'", "man"

Out: "Man", "dog", "bites", "dogs'", "man"

This filter outputs a single token which is a concatenation of the sorted and de-duplicated set of input tokens. This can be useful for clustering/linking use cases.

Factory class: solr.FingerprintFilterFactory

Arguments:

Example:

In: "the quick brown fox jumped over the lazy dog"

Tokenizer to Filter: "the", "quick", "brown", "fox", "jumped", "over", "the", "lazy", "dog"

Out: "brown_dog_fox_jumped_lazy_over_quick_the"

This filter must be included on index-time analyzer specifications that include at least one graph-aware filter, including Synonym Graph Filter and Word Delimiter Graph Filter.

Factory class: solr.FlattenGraphFilterFactory

Arguments: None

See the examples below for Synonym Graph Filter and Word Delimiter Graph Filter.

The Hunspell Stem Filter provides support for several languages. You must provide the dictionary (.dic) and rules (.aff) files for each language you wish to use with the Hunspell Stem Filter. You can download those language files here.

Be aware that your results will vary widely based on the quality of the provided dictionary and rules files. For example, some languages have only a minimal word list with no morphological information. On the other hand, for languages that have no stemmer but do have an extensive dictionary file, the Hunspell stemmer may be a good choice.

Factory class: solr.HunspellStemFilterFactory

Arguments:

Example:

In: "jump jumping jumped"

Tokenizer to Filter: "jump", "jumping", "jumped"

Out: "jump", "jump", "jump"

This filter reconstructs hyphenated words that have been tokenized as two tokens because of a line break or other intervening whitespace in the field test. If a token ends with a hyphen, it is joined with the following token and the hyphen is discarded.

Note that for this filter to work properly, the upstream tokenizer must not remove trailing hyphen characters. This filter is generally only useful at index time.

Factory class: solr.HyphenatedWordsFilterFactory

Arguments: None

Example:

In: "A hyphen- ated word"

Tokenizer to Filter: "A", "hyphen-", "ated", "word"

Out: "A", "hyphenated", "word"

This filter is a custom Unicode normalization form that applies the foldings specified in Unicode TR #30: Character Foldings in addition to the NFKC_Casefold normalization form as described in ICU Normalizer 2 Filter. This filter is a better substitute for the combined behavior of the ASCII Folding Filter, Lower Case Filter, and ICU Normalizer 2 Filter.

To use this filter, you must add additional .jars to Solr’s classpath (as described in the section Resources and Plugins on the Filesystem). See solr/contrib/analysis-extras/README.txt for instructions on which jars you need to add.

Factory class: solr.ICUFoldingFilterFactory

Arguments:

Example without a filter:

Example with a filter to exclude Swedish/Finnish characters:

For detailed information on this normalization form, see Unicode TR #30: Character Foldings.

This filter factory normalizes text according to one of five Unicode Normalization Forms as described in Unicode Standard Annex #15:

Factory class: solr.ICUNormalizer2FilterFactory

Arguments:

Example with NFKC_Casefold:

Example with a filter to exclude Swedish/Finnish characters:

For detailed information about these normalization forms, see Unicode Normalization Forms.

To use this filter, you must add additional .jars to Solr’s classpath (as described in the section Resources and Plugins on the Filesystem). See solr/contrib/analysis-extras/README.txt for instructions on which jars you need to add.

This filter applies ICU Tranforms to text. This filter supports only ICU System Transforms. Custom rule sets are not supported.

Factory class: solr.ICUTransformFilterFactory

Arguments:

Example:

For detailed information about ICU Transforms, see http://userguide.icu-project.org/transforms/general.

To use this filter, you must add additional .jars to Solr’s classpath (as described in the section Resources and Plugins on the Filesystem). See solr/contrib/analysis-extras/README.txt for instructions on which jars you need to add.

This filter discards all tokens except those that are listed in the given word list. This is the inverse of the Stop Words Filter. This filter can be useful for building specialized indices for a constrained set of terms.

Factory class: solr.KeepWordFilterFactory

Arguments:

Example:

Where keepwords.txt contains:

happy funny silly

In: "Happy, sad or funny"

Tokenizer to Filter: "Happy", "sad", "or", "funny"

Out: "funny"

Example:

Same keepwords.txt, case insensitive:

In: "Happy, sad or funny"

Tokenizer to Filter: "Happy", "sad", "or", "funny"

Out: "Happy", "funny"

Example:

Using LowerCaseFilterFactory before filtering for keep words, no ignoreCase flag.

In: "Happy, sad or funny"

Tokenizer to Filter: "Happy", "sad", "or", "funny"

Filter to Filter: "happy", "sad", "or", "funny"

Out: "happy", "funny"

KStem is an alternative to the Porter Stem Filter for developers looking for a less aggressive stemmer. KStem was written by Bob Krovetz, ported to Lucene by Sergio Guzman-Lara (UMASS Amherst). This stemmer is only appropriate for English language text.

Factory class: solr.KStemFilterFactory

Arguments: None

Example:

In: "jump jumping jumped"

Tokenizer to Filter: "jump", "jumping", "jumped"

Out: "jump", "jump", "jump"

This filter passes tokens whose length falls within the min/max limit specified. All other tokens are discarded.

Factory class: solr.LengthFilterFactory

Arguments:

Example:

In: "turn right at Albuquerque"

Tokenizer to Filter: "turn", "right", "at", "Albuquerque"

Out: "turn", "right"

This filter limits the number of accepted tokens, typically useful for index analysis.

By default, this filter ignores any tokens in the wrapped TokenStream once the limit has been reached, which can result in reset() being called prior to incrementToken() returning false. For most TokenStream implementations this should be acceptable, and faster then consuming the full stream. If you are wrapping a TokenStream which requires that the full stream of tokens be exhausted in order to function properly, use the consumeAllTokens="true" option.

Factory class: solr.LimitTokenCountFilterFactory

Arguments:

Example:

In: "1 2 3 4 5 6 7 8 9 10 11 12"

Tokenizer to Filter: "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12"

Out: "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"

This filter limits tokens to those before a configured maximum start character offset. This can be useful to limit highlighting, for example.

By default, this filter ignores any tokens in the wrapped TokenStream once the limit has been reached, which can result in reset() being called prior to incrementToken() returning false. For most TokenStream implementations this should be acceptable, and faster then consuming the full stream. If you are wrapping a TokenStream which requires that the full stream of tokens be exhausted in order to function properly, use the consumeAllTokens="true" option.

Factory class: solr.LimitTokenOffsetFilterFactory

Arguments:

Example:

In: "0 2 4 6 8 A C E"

Tokenizer to Filter: "0", "2", "4", "6", "8", "A", "C", "E"

Out: "0", "2", "4", "6", "8", "A"

This filter limits tokens to those before a configured maximum token position.

By default, this filter ignores any tokens in the wrapped TokenStream once the limit has been reached, which can result in reset() being called prior to incrementToken() returning false. For most TokenStream implementations this should be acceptable, and faster then consuming the full stream. If you are wrapping a TokenStream which requires that the full stream of tokens be exhausted in order to function properly, use the consumeAllTokens="true" option.

Factory class: solr.LimitTokenPositionFilterFactory

Arguments:

Example:

In: "1 2 3 4 5"

Tokenizer to Filter: "1", "2", "3", "4", "5"

Out: "1", "2", "3"

Converts any uppercase letters in a token to the equivalent lowercase token. All other characters are left unchanged.

Factory class: solr.LowerCaseFilterFactory

Arguments: None

Example:

In: "Down With CamelCase"

Tokenizer to Filter: "Down", "With", "CamelCase"

Out: "down", "with", "camelcase"

This is specialized version of the Stop Words Filter Factory that uses a set of stop words that are managed from a REST API.

Arguments:

Example: With this configuration the set of words is named "english" and can be managed via /solr/collection_name/schema/analysis/stopwords/english

See Stop Filter for example input/output.

This is specialized version of the Synonym Filter that uses a mapping on synonyms that is managed from a REST API.

Factory class: solr.ManagedSynonymFilterFactory

For arguments and examples, see the Synonym Graph Filter below.

This is specialized version of the Synonym Graph Filter that uses a mapping on synonyms that is managed from a REST API.

This filter maps single- or multi-token synonyms, producing a fully correct graph output. This filter is a replacement for the Managed Synonym Filter, which produces incorrect graphs for multi-token synonyms.

Arguments:

Example: With this configuration the set of mappings is named "english" and can be managed via /solr/collection_name/schema/analysis/synonyms/english

See Synonym Graph Filter below for example input/output.

Generates n-gram tokens of sizes in the given range. Note that tokens are ordered by position and then by gram size.

Factory class: solr.NGramFilterFactory

Arguments:

Example:

Default behavior.

In: "four score"

Tokenizer to Filter: "four", "score"

Out: "f", "o", "u", "r", "fo", "ou", "ur", "s", "c", "o", "r", "e", "sc", "co", "or", "re"

Example:

A range of 1 to 4.

In: "four score"

Tokenizer to Filter: "four", "score"

Out: "f", "fo", "fou", "four", "o", "ou", "our", "u", "ur", "r", "s", "sc", "sco", "scor", "c", "co", "cor", "core", "o", "or", "ore", "r", "re", "e"

Example:

A range of 3 to 5.

In: "four score"

Tokenizer to Filter: "four", "score"

Out: "fou", "four", "our", "sco", "scor", "score", "cor", "core", "ore"

This filter adds a numeric floating point payload value to tokens that match a given type. Refer to the Javadoc for the org.apache.lucene.analysis.Token class for more information about token types and payloads.

Factory class: solr.NumericPayloadTokenFilterFactory

Arguments:

Example:

In: "bing bang boom"

Tokenizer to Filter: "bing", "bang", "boom"

Out: "bing"[0.75], "bang"[0.75], "boom"[0.75]

This filter applies a regular expression to each token and, for those that match, substitutes the given replacement string in place of the matched pattern. Tokens which do not match are passed though unchanged.

Factory class: solr.PatternReplaceFilterFactory

Arguments:

Example:

Simple string replace:

In: "cat concatenate catycat"

Tokenizer to Filter: "cat", "concatenate", "catycat"

Out: "dog", "condogenate", "dogydog"

Example:

String replacement, first occurrence only:

In: "cat concatenate catycat"

Tokenizer to Filter: "cat", "concatenate", "catycat"

Out: "dog", "condogenate", "dogycat"

Example:

More complex pattern with capture group reference in the replacement. Tokens that start with non-numeric characters and end with digits will have an underscore inserted before the numbers. Otherwise the token is passed through.

In: "cat foo1234 9987 blah1234foo"

Tokenizer to Filter: "cat", "foo1234", "9987", "blah1234foo"

Out: "cat", "foo_1234", "9987", "blah1234foo"

This filter creates tokens using one of the phonetic encoding algorithms in the org.apache.commons.codec.language package. For more information, see the section on Phonetic Matching.

Factory class: solr.PhoneticFilterFactory

Arguments:

Example:

Default behavior for DoubleMetaphone encoding.

In: "four score and twenty"

Tokenizer to Filter: "four"(1), "score"(2), "and"(3), "twenty"(4)

Out: "four"(1), "FR"(1), "score"(2), "SKR"(2), "and"(3), "ANT"(3), "twenty"(4), "TNT"(4)

The phonetic tokens have a position increment of 0, which indicates that they are at the same position as the token they were derived from (immediately preceding).

Example:

Discard original token.

In: "four score and twenty"

Tokenizer to Filter: "four"(1), "score"(2), "and"(3), "twenty"(4)

Out: "FR"(1), "SKR"(2), "ANT"(3), "TWNT"(4)

Example:

Default Soundex encoder.

In: "four score and twenty"

Tokenizer to Filter: "four"(1), "score"(2), "and"(3), "twenty"(4)

Out: "four"(1), "F600"(1), "score"(2), "S600"(2), "and"(3), "A530"(3), "twenty"(4), "T530"(4)

This filter applies the Porter Stemming Algorithm for English. The results are similar to using the Snowball Porter Stemmer with the language="English" argument. But this stemmer is coded directly in Java and is not based on Snowball. It does not accept a list of protected words and is only appropriate for English language text. However, it has been benchmarked as four times faster than the English Snowball stemmer, so can provide a performance enhancement.

Factory class: solr.PorterStemFilterFactory

Arguments: None

Example:

In: "jump jumping jumped"

Tokenizer to Filter: "jump", "jumping", "jumped"

Out: "jump", "jump", "jump"

This filter enables a form of conditional filtering: it only applies its wrapped filters to terms that are not contained in a protected set.

Factory class: solr.ProtectedTermFilterFactory

Arguments:

Example:

All terms except those in protectedTerms.txt are truncated at 4 characters and lowercased:

Example:

This example includes multiple same-named wrapped filters with unique -id suffixes. Note that both the filter SPI names and -id suffixes are treated case-insensitively.

For all terms except those in protectedTerms.txt, synonyms are added, terms are reversed, and then synonyms are added for the reversed terms:

The filter removes duplicate tokens in the stream. Tokens are considered to be duplicates ONLY if they have the same text and position values.

Because positions must be the same, this filter might not do what a user expects it to do based on its name. It is a very specialized filter that is only useful in very specific circumstances. It has been so named for brevity, even though it is potentially misleading.

Factory class: solr.RemoveDuplicatesTokenFilterFactory

Arguments: None

Example:

One example of where RemoveDuplicatesTokenFilterFactory is useful in situations where a synonym file is being used in conjunction with a stemmer. In these situations, both the stemmer and the synonym filter can cause completely identical terms with the same positions to end up in the stream, increasing index size with no benefit.

Consider the following entry from a synonyms.txt file:

When used in the following configuration:

In: "Watch TV"

Tokenizer to Synonym Filter: "Watch"(1) "TV"(2)

Synonym Filter to Stem Filter: "Watch"(1) "Television"(2) "Televisions"(2) "TV"(2) "TVs"(2)

Stem Filter to Remove Dups Filter: "Watch"(1) "Television"(2) "Television"(2) "TV"(2) "TV"(2)

Out: "Watch"(1) "Television"(2) "TV"(2)

This filter reverses tokens to provide faster leading wildcard and prefix queries. Tokens without wildcards are not reversed.

Factory class: solr.ReversedWildcardFilterFactory

Arguments:

Example:

In: "*foo *bar"

Tokenizer to Filter: "*foo", "*bar"

Out: "oof*", "rab*"

This filter constructs shingles, which are token n-grams, from the token stream. It combines runs of tokens into a single token.

Factory class: solr.ShingleFilterFactory

Arguments:

Example:

Default behavior.

In: "To be, or what?"

Tokenizer to Filter: "To"(1), "be"(2), "or"(3), "what"(4)

Out: "To"(1), "To be"(1), "be"(2), "be or"(2), "or"(3), "or what"(3), "what"(4)

Example:

A shingle size of four, do not include original token.

In: "To be, or not to be."

Tokenizer to Filter: "To"(1), "be"(2), "or"(3), "not"(4), "to"(5), "be"(6)

Out: "To be"(1), "To be or"(1), "To be or not"(1), "be or"(2), "be or not"(2), "be or not to"(2), "or not"(3), "or not to"(3), "or not to be"(3), "not to"(4), "not to be"(4), "to be"(5)

This filter factory instantiates a language-specific stemmer generated by Snowball. Snowball is a software package that generates pattern-based word stemmers. This type of stemmer is not as accurate as a table-based stemmer, but is faster and less complex. Table-driven stemmers are labor intensive to create and maintain and so are typically commercial products.

Solr contains Snowball stemmers for Armenian, Basque, Catalan, Danish, Dutch, English, Finnish, French, German, Hungarian, Italian, Norwegian, Portuguese, Romanian, Russian, Spanish, Swedish and Turkish. For more information on Snowball, visit http://snowball.tartarus.org/.

StopFilterFactory, CommonGramsFilterFactory, and CommonGramsQueryFilterFactory can optionally read stopwords in Snowball format (specify format="snowball" in the configuration of those FilterFactories).

Factory class: solr.SnowballPorterFilterFactory

Arguments:

Example:

Default behavior:

In: "flip flipped flipping"

Tokenizer to Filter: "flip", "flipped", "flipping"

Out: "flip", "flip", "flip"

Example:

French stemmer, English words:

In: "flip flipped flipping"

Tokenizer to Filter: "flip", "flipped", "flipping"

Out: "flip", "flipped", "flipping"

Example:

Spanish stemmer, Spanish words:

In: "cante canta"

Tokenizer to Filter: "cante", "canta"

Out: "cant", "cant"

This filter discards, or stops analysis of, tokens that are on the given stop words list. A standard stop words list is included in the Solr conf directory, named stopwords.txt, which is appropriate for typical English language text.

Factory class: solr.StopFilterFactory

Arguments:

Example:

Case-sensitive matching, capitalized words not stopped. Token positions skip stopped words.

In: "To be or what?"

Tokenizer to Filter: "To"(1), "be"(2), "or"(3), "what"(4)

Out: "To"(1), "what"(4)

Example:

In: "To be or what?"

Tokenizer to Filter: "To"(1), "be"(2), "or"(3), "what"(4)

Out: "what"(4)

Like Stop Filter, this filter discards, or stops analysis of, tokens that are on the given stop words list.

Suggest Stop Filter differs from Stop Filter in that it will not remove the last token unless it is followed by a token separator. For example, a query "find the" would preserve the 'the' since it was not followed by a space, punctuation, etc., and mark it as a KEYWORD so that following filters will not change or remove it.

By contrast, a query like “find the popsicle” would remove ‘the’ as a stopword, since it’s followed by a space. When using one of the analyzing suggesters, you would normally use the ordinary StopFilterFactory in your index analyzer and then SuggestStopFilter in your query analyzer.

Factory class: solr.SuggestStopFilterFactory

Arguments:

Example:

In: "The The"

Tokenizer to Filter: "the"(1), "the"(2)

Out: "the"(2)

This filter does synonym mapping. Each token is looked up in the list of synonyms and if a match is found, then the synonym is emitted in place of the token. The position value of the new tokens are set such they all occur at the same position as the original token.

Factory class: solr.SynonymFilterFactory

For arguments and examples, see the Synonym Graph Filter below.

This filter maps single- or multi-token synonyms, producing a fully correct graph output. This filter is a replacement for the Synonym Filter, which produces incorrect graphs for multi-token synonyms.

If you use this filter during indexing, you must follow it with a Flatten Graph Filter to squash tokens on top of one another like the Synonym Filter, because the indexer can’t directly consume a graph. To get fully correct positional queries when your synonym replacements are multiple tokens, you should instead apply synonyms using this filter at query time.

Factory class: solr.SynonymGraphFilterFactory

Arguments:

For the following examples, assume a synonyms file named mysynonyms.txt:

Example:

In: "teh small couch"

Tokenizer to Filter: "teh"(1), "small"(2), "couch"(3)

Out: "the"(1), "tiny"(2), "teeny"(2), "weeny"(2), "couch"(3), "sofa"(3), "divan"(3)

Example:

In: "teh ginormous, humungous sofa"

Tokenizer to Filter: "teh"(1), "ginormous"(2), "humungous"(3), "sofa"(4)

Out: "the"(1), "large"(2), "large"(3), "couch"(4), "sofa"(4), "divan"(4)

This filter adds the numeric character offsets of the token as a payload value for that token.

Factory class: solr.TokenOffsetPayloadTokenFilterFactory

Arguments: None

Example:

In: "bing bang boom"

Tokenizer to Filter: "bing", "bang", "boom"

Out: "bing"[0,4], "bang"[5,9], "boom"[10,14]

This filter trims leading and/or trailing whitespace from tokens. Most tokenizers break tokens at whitespace, so this filter is most often used for special situations.

Factory class: solr.TrimFilterFactory

Arguments:

Example:

The PatternTokenizerFactory configuration used here splits the input on simple commas, it does not remove whitespace.

In: "one, two , three ,four "

Tokenizer to Filter: "one", " two ", " three ", "four "

Out: "one", "two", "three", "four"

This filter adds the token’s type, as an encoded byte sequence, as its payload.

Factory class: solr.TypeAsPayloadTokenFilterFactory

Arguments: None

Example:

In: "Pay Bob’s I.O.U."

Tokenizer to Filter: "Pay", "Bob’s", "I.O.U."

Out: "Pay"[<ALPHANUM>], "Bob’s"[<APOSTROPHE>], "I.O.U."[<ACRONYM>]

This filter adds the token’s type, as a token at the same position as the token, optionally with a configurable prefix prepended.

Factory class: solr.TypeAsSynonymFilterFactory

Arguments:

Examples:

With the example below, each token’s type will be emitted verbatim at the same position:

With the example below, for a token "example.com" with type <URL>, the token emitted at the same position will be "_type_<URL>":

This filter blacklists or whitelists a specified list of token types, assuming the tokens have type metadata associated with them. For example, the UAX29 URL Email Tokenizer emits "<URL>" and "<EMAIL>" typed tokens, as well as other types. This filter would allow you to pull out only e-mail addresses from text as tokens, if you wish.

Factory class: solr.TypeTokenFilterFactory

Arguments:

Example:

This filter splits tokens at word delimiters.

Factory class: solr.WordDelimiterFilterFactory

For a full description, including arguments and examples, see the Word Delimiter Graph Filter below.

This filter splits tokens at word delimiters.

If you use this filter during indexing, you must follow it with a Flatten Graph Filter to squash tokens on top of one another like the Word Delimiter Filter, because the indexer can’t directly consume a graph. To get fully correct positional queries when tokens are split, you should instead use this filter at query time.

Note: although this filter produces correct token graphs, it cannot consume an input token graph correctly.

The rules for determining delimiters are determined as follows:

Factory class: solr.WordDelimiterGraphFilterFactory

Arguments:

Example:

Default behavior. The whitespace tokenizer is used here to preserve non-alphanumeric characters.

In: "hot-spot RoboBlaster/9000 100XL"

Tokenizer to Filter: "hot-spot", "RoboBlaster/9000", "100XL"

Out: "hot", "spot", "Robo", "Blaster", "9000", "100", "XL"

Example:

Do not split on case changes, and do not generate number parts. Note that by not generating number parts, tokens containing only numeric parts are ultimately discarded.

In: "hot-spot RoboBlaster/9000 100-42"

Tokenizer to Filter: "hot-spot", "RoboBlaster/9000", "100-42"

Out: "hot", "spot", "RoboBlaster", "9000"

Example:

Concatenate word parts and number parts, but not word and number parts that occur in the same token.

In: "hot-spot 100+42 XL40"

Tokenizer to Filter: "hot-spot"(1), "100+42"(2), "XL40"(3)

Out: "hot"(1), "spot"(2), "hotspot"(2), "100"(3), "42"(4), "10042"(4), "XL"(5), "40"(6)

Example:

Concatenate all. Word and/or number parts are joined together.

In: "XL-4000/ES"

Tokenizer to Filter: "XL-4000/ES"(1)

Out: "XL"(1), "4000"(2), "ES"(3), "XL4000ES"(3)

Example:

Using a protected words list that contains "AstroBlaster" and "XL-5000" (among others).

In: "FooBar AstroBlaster XL-5000 ==ES-34-"

Tokenizer to Filter: "FooBar", "AstroBlaster", "XL-5000", "==ES-34-"

Out: "FooBar", "FooBar", "AstroBlaster", "XL-5000", "ES", "34"