The Mmseg Analysis plugin integrates Lucene mmseg4j-analyzer:http://code.google.com/p/mmseg4j/ into elasticsearch, support customized dictionary.
The plugin ships with a mmseg analyzer ,a mmseg tokenizer and a cut_letter_digit token_filter.
| Mmseg ver | ES version |
|---|---|
| master | 1.0.0 -> master |
| 1.4.0 | 1.7.0 |
| 1.3.0 | 1.6.0 |
| 1.2.2 | 1.0.0 |
| 1.2.1 | 0.90.2 |
| 1.2.0 | 0.90.0 |
| 1.1.2 | 0.20.1 |
| 1.1.1 | 0.19.x |
you can download this plugin from RTF project(https://github.com/medcl/elasticsearch-rtf) https://github.com/medcl/elasticsearch-rtf/tree/master/plugins/analysis-mmseg
download the dict files,unzip these dict file to your elasticsearch's config folder,such as: your-es-root/config/mmseg https://github.com/medcl/elasticsearch-rtf/tree/master/config/mmseg
you need a service restart after that!
index:
analysis:
analyzer:
mmseg:
alias: [news_analyzer, mmseg_analyzer]
type: org.elasticsearch.index.analysis.MMsegAnalyzerProvider
index.analysis.analyzer.default.type : "mmseg"
additional parameters that can be used to customize the mmseg tokenizer
index:
analysis:
tokenizer:
mmseg_maxword:
type: mmseg
seg_type: "max_word"
mmseg_complex:
type: mmseg
seg_type: "complex"
mmseg_simple:
type: mmseg
seg_type: "simple"
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": {
"indexAnalyzer": "mmseg",
"searchAnalyzer": "mmseg",
"term_vector": "no",
"store": "false"
},
"properties": {
"content": {
"type": "string",
"store": "no",
"term_vector": "with_positions_offsets",
"indexAnalyzer": "mmseg",
"searchAnalyzer": "mmseg",
"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艘中国渔船"}
'
curl -XPOST http://localhost:9200/index/fulltext/4 -d'
{content:"中国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" : "中国" }},
"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": "中国驻洛杉矶领事馆遭亚裔男子枪击 嫌犯已自首"
},
"highlight": {
"content": [
"<tag1>中国</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艘中国渔船"
},
"highlight": {
"content": [
"均每天扣1艘<tag1>中国</tag1>渔船 "
]
}
}
]
}
}
have fun.