cts:field-word-query throws an exception. A field
is a named object that specified elements to include and exclude
from a search, and can include score weights for any included elements.
You create fields at the database level using the Admin Interface. For
details on fields, see the chapter on "Fields Database Settings" in the
Administrator's Guide.
Options include:
- "case-sensitive"
- A case-sensitive query.
- "case-insensitive"
- A case-insensitive query.
- "diacritic-sensitive"
- A diacritic-sensitive query.
- "diacritic-insensitive"
- A diacritic-insensitive query.
- "punctuation-sensitive"
- A punctuation-sensitive query.
- "punctuation-insensitive"
- A punctuation-insensitive query.
- "whitespace-sensitive"
- A whitespace-sensitive query.
- "whitespace-insensitive"
- A whitespace-insensitive query.
- "stemmed"
- A stemmed query.
- "unstemmed"
- An unstemmed query.
- "wildcarded"
- A wildcarded query.
- "unwildcarded"
- An unwildcarded query.
- "exact"
- An exact match query. Shorthand for "case-sensitive", "diacritic-sensitive", "punctuation-sensitive", "whitespace-sensitive", "unstemmed", and "unwildcarded".
- "lang=iso639code"
- Specifies the language of the query. The iso639code code portion is case-insensitive, and uses the languages specified by ISO 639. The default is specified in the database configuration.
- "distance-weight=number"
- A weight applied based on the minimum distance between matches of this query. Higher weights add to the importance of proximity (as opposed to term matches) when the relevance order is calculated. The default value is 0.0 (no impact of proximity). The weight should be between 64 and -16. Weights greater than 64 will have the same effect as a weight of 64. This parameter has no effect if the
word positionsindex is not enabled. This parameter has no effect on searches that use score-simple, score-random, or score-zero (because those scoring algorithms do not consider term frequency, proximity is irrelevant).- "min-occurs=number"
- Specifies the minimum number of occurrences required. If fewer that this number of words occur, the fragment does not match. The default is 1.
- "max-occurs=number"
- Specifies the maximum number of occurrences required. If more than this number of words occur, the fragment does not match. The default is unbounded.
- "synonym"
- Specifies that all of the terms in the $text parameter are considered synonyms for scoring purposes. The result is that occurrences of more than one of the synonyms are scored as if there are more occurrences of the same term (as opposed to having a separate term that contributes to score).
- "lexicon-expand=value"
- The value is one of
full,prefix-postfix,off, orheuristic(the default isheuristic). An option with a value oflexicon-expand=fullspecifies that wildcards are resolved by expanding the pattern to words in a lexicon (if there is one available), and turning into a series ofcts:word-queries, even if this takes a long time to evaluate. An option with a value oflexicon-expand=prefix-postfixspecifies that wildcards are resolved by expanding the pattern to the pre- and postfixes of the words in the word lexicon (if there is one), and turning the query into a series of character queries, even if it takes a long time to evaluate. An option with a value oflexicon-expand=offspecifies that wildcards are only resolved by looking up character patterns in the search pattern index, not in the lexicon. A option with a value oflexicon-expand=heuristic, which is the default, specifies that wildcards are resolved by using a series of internal rules, such as estimating the number of lexicon entries that need to be scanned, seeing if the estimate crosses certain thresholds, and (if appropriate), using another way besides lexicon expansion to resolve the query.
If you use cts:near-query with
cts:field-word-query, the distance supplied in the near query
applies to the whole document, not just to the field. For example, if
you specify a near query with a distance of 3, it will return matches
when the words or phrases are within 3 words in the whole document,
even if some of those words are not in the specified field. For a code
example illustrating this, see the
second example
below.
Phrases are determined based on words being next to each other (word positions with a distance of 1) and words being in the same instance of the field. Because field word positions are determined based on the fragment, not on the field, field phrases cannot span excluded elements (this is because MarkLogic Server breaks out of the field when it encounters the excluded element and start a new field when it encounters the next included element). Similarly, field phrases will not span included sibling elements. The second code example below illustrates this.
Field phrases will automatically phrase-through all child elements of
an included element, until it encounters an explicitly excluded
element. The
third example
below illustrates this.
An example of when this automatic phrase-through behavior might be
convenient is if you create a field that includes only the element
ABSTRACT. Then all child elements of ABSTRACT
are included in the field, and phrases would span all of the child
elements (that is, phrases would "phrase-through" all the child elements).
Negative "min-occurs" or "max-occurs" values will be treated as 0 and non-integral values will be rounded down. An error will be raised if the "min-occurs" value is greater than the "max-occurs" value.
cts.search(cts.fieldWordQuery("myField", "my phrase"));
=> a list of documents that contain the phrase
"my phrase" in the field "myField". The field
must exist in the database against which this query
is evaluated.
// Assume the database has a field named
// "buzz" with the element "buzz"
// included and the element "baz" excluded.
var x = xdmp.unquote(
'<hello>word1 word2 word3\n\
<buzz>word4 word5</buzz>\n\
<baz>word6 word7 word8</baz>\n\
<buzz>word9 word10</buzz>\n\
</hello>').next().value;
var res = new Array();
res.push(cts.contains(x, cts.nearQuery(
[cts.fieldWordQuery("buzz", "word5"),
cts.fieldWordQuery("buzz", "word9")], 3)));
res.push(cts.contains(x, cts.nearQuery(
[cts.fieldWordQuery("buzz", "word5"),
cts.fieldWordQuery("buzz", "word9")], 4)));
res.push(cts.contains(x,
cts.fieldWordQuery("buzz", "word5 word9")));
res;
// Returns the array [false, true, false].
// The first part does not match because
// the distance between "word5" and "word9"
// is 4. This is because the distance is
// calculated based on the whole node (if the
// document was in a database, based on the
// fragment), not based on the field. The
// second part specifies a distance of 4, and
// therefore matches and returns true. The third
// part does not match because the phrase is
// based on the entire node, not on the field,
// and there are words between "word5" and "word9"
// in the node (even though not in the field).
// Assume the database has a field named
// "buzz" with the element "buzz"
// included and the element "baz" excluded.
var x = xdmp.unquote(
'<hello>\n\
<buzz>word1 word2\n\
<gads>word3 word4 word5</gads>\n\
<zukes>word6 word7 word8</zukes>\n\
word9 word10\n\
</buzz>\n\
</hello>').next().value;
cts.contains(x,
cts.fieldWordQuery("buzz", "word2 word3"));
// Returns "true" because the children of
// "buzz" are not excluded, and are therefore
// automatically phrased through.