The Mmseg Analysis plugin integrates Lucene mmseg4j-analyzer:http://code.google.com/p/mmseg4j/ into elasticsearch, support customized dictionary.
The plugin ships with analyzers: mmseg_maxword
,mmseg_complex
,mmseg_simple
and tokenizers: mmseg_maxword
,mmseg_complex
,mmseg_simple
and token_filter: cut_letter_digit
.
Mmseg ver | ES version |
---|---|
master | 5.x -> master |
5.2.2 | 5.2.2 |
5.1.2 | 5.1.2 |
1.10.1 | 2.4.1 |
1.9.5 | 2.3.5 |
1.8.1 | 2.2.1 |
1.7.0 | 2.1.1 |
1.5.0 | 2.0.0 |
1.4.0 | 1.7.0 |
1.3.0 | 1.6.0 |
1.2.1 | 0.90.2 |
1.1.2 | 0.20.1 |
mvn package
Unzip and place into elasticsearch's plugins folder, you can checkout example from https://github.com/medcl/elasticsearch-rtf
index:
analysis:
analyzer:
my_mmseg_maxword:
type: custom
filter:
- lowercase
tokenizer: mmseg_maxword
mmseg_maxword_with_cut_letter_digi:
type: custom
filter:
- lowercase
- cut_letter_digit
tokenizer: mmseg_maxword
Here is a quick example:
1.Create a index
curl -XPUT http://localhost:9200/index
2.Create a mapping
curl -XPOST http://localhost:9200/index/fulltext/_mapping -d'
{
"fulltext": {
"_all": {
"analyzer": "mmseg_maxword",
"search_analyzer": "mmseg_maxword",
"term_vector": "no",
"store": "false"
},
"properties": {
"content": {
"type": "text",
"store": "no",
"term_vector": "with_positions_offsets",
"analyzer": "mmseg_maxword",
"search_analyzer": "mmseg_maxword",
"include_in_all": "true",
"boost": 8
}
}
}
}'
3.Indexing some docs
curl -XPOST http://localhost:9200/index/fulltext/1 -d'
{content:"美国留给伊拉克的是个烂摊子吗"}
'
curl -XPOST http://localhost:9200/index/fulltext/2 -d'
{content:"公安部:各地校车将享最高路权"}
'
curl -XPOST http://localhost:9200/index/fulltext/3 -d'
{content:"中韩渔警冲突调查:韩警平均每天扣1艘**渔船"}
'
curl -XPOST http://localhost:9200/index/fulltext/4 -d'
{content:"**驻洛杉矶领事馆遭亚裔男子枪击 嫌犯已自首"}
'
4.Query with highlighting
curl -XPOST http://localhost:9200/index/fulltext/_search -d'
{
"query" : { "term" : { "content" : "**" }},
"highlight" : {
"pre_tags" : ["<tag1>", "<tag2>"],
"post_tags" : ["</tag1>", "</tag2>"],
"fields" : {
"content" : {}
}
}
}
'
Here is the query result
{
"took": 14,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 2,
"hits": [
{
"_index": "index",
"_type": "fulltext",
"_id": "4",
"_score": 2,
"_source": {
"content": "**驻洛杉矶领事馆遭亚裔男子枪击 嫌犯已自首"
},
"highlight": {
"content": [
"<tag1>**</tag1>驻洛杉矶领事馆遭亚裔男子枪击 嫌犯已自首 "
]
}
},
{
"_index": "index",
"_type": "fulltext",
"_id": "3",
"_score": 2,
"_source": {
"content": "中韩渔警冲突调查:韩警平均每天扣1艘**渔船"
},
"highlight": {
"content": [
"均每天扣1艘<tag1>**</tag1>渔船 "
]
}
}
]
}
}
Have fun.