Elasticsearch 邻近查询示例(全切分分词)
JAVA API方式:
1
SpanNearQueryBuilder span =
QueryBuilders.spanNearQuery();
2
span.clause(QueryBuilders.spanTermQuery("Text", "学"
));
3
span.clause(QueryBuilders.spanTermQuery("Text", "联"
));
4
span.inOrder(
true
).slop(1
);
5
SearchRequestBuilder rs = client.prepareSearch("weiboall"
)
6
.setQuery(span).setFrom(0).setSize(20
);
7
SearchResponse response = rs.get();
REST方式（JSON）:
1
{
2
"from": 0
,
3
"size": 20
,
4
"query"
: {
5
"span_near"
: {
6
"clauses"
: [
7
{
8
"span_term"
: {
9
"Text"
: {
10
"value": "在"
11
}
12
}
13
},
14
{
15
"span_term"
: {
16
"Text"
: {
17
"value": "讨"
18
}
19
}
20
}
21
],
22
"slop": 0
,
23
"in_order":
true
24
}
25
}
26
}
Elasticsearch 邻近查询示例（IK分词）
这种方式利用前后缀组合查询，可以识别查询中的未登陆词、新词等
java API方式：
1
MultiTermQueryBuilder mqb1 =
new
WildcardQueryBuilder(
"
Text
"
,
"
*学
"
);
2
SpanQueryBuilder sb1=
new
SpanMultiTermQueryBuilder(mqb1);
3
MultiTermQueryBuilder mqb2 =
new
WildcardQueryBuilder(
"
Text
"
,
"
联*
"
);
4
SpanQueryBuilder sb2=
new
SpanMultiTermQueryBuilder(mqb2);
5
SpanNearQueryBuilder spanb=
new
SpanNearQueryBuilder();
6
spanb.clause(sb1);
7
spanb.clause(sb2);
8
spanb.inOrder(
true
);
9
spanb.slop(
0
);
10
SearchRequestBuilder rs = client.prepareSearch(
"
weiboall
"
)
11
.setQuery(spanb).setFrom(
0
).setSize(
20
);
12
System.
out
.println(rs.toString());
13
SearchResponse response = rs.
get
();
Rest(json)方式：
1
{
2
"from" : 0
,
3
"size" : 20
,
4
"query"
: {
5
"span_near"
: {
6
"clauses"
: [ {
7
"span_multi"
: {
8
"match"
: {
9
"wildcard"
: {
10
"Text"
: {
11
"wildcard" : "*学"
12
}
13
}
14
}
15
}
16
}, {
17
"span_multi"
: {
18
"match"
: {
19
"wildcard"
: {
20
"Text"
: {
21
"wildcard" : "联*"
22
}
23
}
24
}
25
}
26
} ],
27
"slop" : 0
,
28
"in_order" :
true
29
}
30
}
31
}
