Edit: The bitset stuff below is maybe an interesting read, but the answer itself is a bit dated. Some of this functionality is changing around in 2.x. Also Slawek points out in another answer that the terms
query is an easy way to DRY up the search in this case. Refactored at the end for current best practices. —nz
You'll probably want a Bool Query (or more likely Filter alongside another query), with a should
clause.
The bool query has three main properties: must
, should
, and must_not
. Each of these accepts another query, or array of queries. The clause names are fairly self-explanatory; in your case, the should
clause may specify a list filters, a match against any one of which will return the document you're looking for.
From the docs:
In a boolean query with no
must
clauses, one or moreshould
clauses must match a document. The minimum number of should clauses to match can be set using theminimum_should_match
parameter.
Here's an example of what that Bool query might look like in isolation:
{
"bool": {
"should": [
{ "term": { "tag": "c" }},
{ "term": { "tag": "d" }}
]
}
}
And here's another example of that Bool query as a filter within a more general-purpose Filtered Query:
{
"filtered": {
"query": {
"match": { "title": "hello world" }
},
"filter": {
"bool": {
"should": [
{ "term": { "tag": "c" }},
{ "term": { "tag": "d" }}
]
}
}
}
}
Whether you use Bool as a query (e.g., to influence the score of matches), or as a filter (e.g., to reduce the hits that are then being scored or post-filtered) is subjective, depending on your requirements.
It is generally preferable to use Bool in favor of an Or Filter, unless you have a reason to use And/Or/Not (such reasons do exist). The Elasticsearch blog has more information about the different implementations of each, and good examples of when you might prefer Bool over And/Or/Not, and vice-versa.
Elasticsearch blog: All About Elasticsearch Filter Bitsets
Update with a refactored query...
Now, with all of that out of the way, the terms
query is a DRYer version of all of the above. It does the right thing with respect to the type of query under the hood, it behaves the same as the bool
+ should
using the minimum_should_match
options, and overall is a bit more terse.
Here's that last query refactored a bit:
{
"filtered": {
"query": {
"match": { "title": "hello world" }
},
"filter": {
"terms": {
"tag": [ "c", "d" ],
"minimum_should_match": 1
}
}
}
}