[[query-dsl-term-query]] === Term Query The `term` query finds documents that contain the *exact* term specified in the inverted index. For instance: [source,js] -------------------------------------------------- POST _search { "query": { "term" : { "user" : "Kimchy" } <1> } } -------------------------------------------------- // CONSOLE <1> Finds documents which contain the exact term `Kimchy` in the inverted index of the `user` field. A `boost` parameter can be specified to give this `term` query a higher relevance score than another query, for instance: [source,js] -------------------------------------------------- GET _search { "query": { "bool": { "should": [ { "term": { "status": { "value": "urgent", "boost": 2.0 <1> } } }, { "term": { "status": "normal" <2> } } ] } } } -------------------------------------------------- // CONSOLE <1> The `urgent` query clause has a boost of `2.0`, meaning it is twice as important as the query clause for `normal`. <2> The `normal` clause has the default neutral boost of `1.0`. .Why doesn't the `term` query match my document? ************************************************** String fields can be of type `text` (treated as full text, like the body of an email), or `keyword` (treated as exact values, like an email address or a zip code). Exact values (like numbers, dates, and keywords) have the exact value specified in the field added to the inverted index in order to make them searchable. However, `text` fields are `analyzed`. This means that their values are first passed through an <> to produce a list of terms, which are then added to the inverted index. There are many ways to analyze text: the default <> drops most punctuation, breaks up text into individual words, and lower cases them. For instance, the `standard` analyzer would turn the string ``Quick Brown Fox!'' into the terms [`quick`, `brown`, `fox`]. This analysis process makes it possible to search for individual words within a big block of full text. The `term` query looks for the *exact* term in the field's inverted index -- it doesn't know anything about the field's analyzer. This makes it useful for looking up values in keyword fields, or in numeric or date fields. When querying full text fields, use the <> instead, which understands how the field has been analyzed. To demonstrate, try out the example below. First, create an index, specifying the field mappings, and index a document: [source,js] -------------------------------------------------- PUT my_index { "mappings": { "my_type": { "properties": { "full_text": { "type": "text" <1> }, "exact_value": { "type": "keyword" <2> } } } } } PUT my_index/my_type/1 { "full_text": "Quick Foxes!", <3> "exact_value": "Quick Foxes!" <4> } -------------------------------------------------- // CONSOLE <1> The `full_text` field is of type `text` and will be analyzed. <2> The `exact_value` field is of type `keyword` and will NOT be analyzed. <3> The `full_text` inverted index will contain the terms: [`quick`, `foxes`]. <4> The `exact_value` inverted index will contain the exact term: [`Quick Foxes!`]. Now, compare the results for the `term` query and the `match` query: [source,js] -------------------------------------------------- GET my_index/my_type/_search { "query": { "term": { "exact_value": "Quick Foxes!" <1> } } } GET my_index/my_type/_search { "query": { "term": { "full_text": "Quick Foxes!" <2> } } } GET my_index/my_type/_search { "query": { "term": { "full_text": "foxes" <3> } } } GET my_index/my_type/_search { "query": { "match": { "full_text": "Quick Foxes!" <4> } } } -------------------------------------------------- // CONSOLE // TEST[continued] <1> This query matches because the `exact_value` field contains the exact term `Quick Foxes!`. <2> This query does not match, because the `full_text` field only contains the terms `quick` and `foxes`. It does not contain the exact term `Quick Foxes!`. <3> A `term` query for the term `foxes` matches the `full_text` field. <4> This `match` query on the `full_text` field first analyzes the query string, then looks for documents containing `quick` or `foxes` or both. **************************************************