文章目录背景： IK分词提供的两个分词器，并不支持一些新的词汇，有时候也不能满足实际业务需要，这时候，我们可以定义自定义词库来完成目标。
目标： 定制化中文分词器，使得我们的中文分词器支持扩展的词汇
- 一、搜索现状
- 1. 搜索关键词
- 2. 数据结果
- 3. 数据分析
- 4. ES IK分词
- 5. IK分词结果+分析
- 二、定制化分词器
- 2.1. 新增分词词典库
- 2.2. 词典配置
- 2.3. 重启es7
- 2.4. 重新查看分词结果
- 2.5. 重新搜索
- 2.6. 重建分词索引
- 2.7. 再次查询
- 2.8. 数据分析
# 搜索凯悦相关的酒店
GET /shop/_search
{
"query":{
"match": {"name":"凯悦"}
}
}
2. 数据结果
{
"took" : 7,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 5,
"relation" : "eq"
},
"max_score" : 3.3362136,
"hits" : [
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "9",
"_score" : 3.3362136,
"_source" : {
"price_per_man" : 176,
"remark_score" : 2.2,
"category_name" : "酒店",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.916Z",
"tags" : "落地大窗",
"location" : "31.306172,121.525843",
"seller_remark_score" : 3.0,
"id" : 9,
"name" : "凯悦酒店",
"seller_id" : 17,
"category_id" : 2
}
},
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "10",
"_score" : 2.836244,
"_source" : {
"price_per_man" : 182,
"remark_score" : 0.5,
"category_name" : "酒店",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.918Z",
"tags" : "自助餐",
"location" : "31.196742,121.322846",
"seller_remark_score" : 3.0,
"id" : 10,
"name" : "凯悦嘉轩酒店",
"seller_id" : 17,
"category_id" : 2
}
},
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "11",
"_score" : 2.836244,
"_source" : {
"price_per_man" : 74,
"remark_score" : 1.0,
"category_name" : "酒店",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.920Z",
"tags" : "自助餐",
"location" : "31.156899,121.238362",
"seller_remark_score" : 3.0,
"id" : 11,
"name" : "新虹桥凯悦酒店",
"seller_id" : 17,
"category_id" : 2
}
},
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "12",
"_score" : 2.638537,
"_source" : {
"price_per_man" : 71,
"remark_score" : 2.0,
"category_name" : "美食2",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.923Z",
"tags" : "有包厢",
"location" : "30.679819,121.651921",
"seller_remark_score" : 3.0,
"id" : 12,
"name" : "凯悦咖啡(新建西路店)",
"seller_id" : 17,
"category_id" : 1
}
},
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "4",
"_score" : 1.3119392,
"_source" : {
"price_per_man" : 152,
"remark_score" : 2.0,
"category_name" : "美食2",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.907Z",
"tags" : "落地大窗 有WIFI",
"location" : "31.306419,121.524878",
"seller_remark_score" : 2.0,
"id" : 4,
"name" : "花悦庭果木烤鸭",
"seller_id" : 2,
"category_id" : 1
}
}
]
}
}
3. 数据分析
上面数据中有一条不符的结果数据，此数据中无**“凯悦”**关键词，但是，搜索后还是显示在页面上，不符合预期搜索结果。
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "4",
"_score" : 1.3119392,
"_source" : {
"price_per_man" : 152,
"remark_score" : 2.0,
"category_name" : "美食2",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.907Z",
"tags" : "落地大窗 有WIFI",
"location" : "31.306419,121.524878",
"seller_remark_score" : 2.0,
"id" : 4,
"name" : "花悦庭果木烤鸭",
"seller_id" : 2,
"category_id" : 1
}
}
4. ES IK分词
# 查阅凯悦分词
GET /shop/_analyze
{
"analyzer": "ik_smart",
"text": "凯悦"
}
5. IK分词结果+分析
{
"tokens" : [
{
"token" : "凯",
"start_offset" : 0,
"end_offset" : 1,
"type" : "CN_CHAR",
"position" : 0
},
{
"token" : "悦",
"start_offset" : 1,
"end_offset" : 2,
"type" : "CN_CHAR",
"position" : 1
}
]
}
从上面数据可以看出，使用ik_smart分词api，分词“凯”，“悦”，并没有将“凯悦”关键词当做一个分词元素，主要原因就是，es安装的ik中文分词库中没有将“凯悦”放入分词库。
二、定制化分词器 2.1. 新增分词词典库cd /app/elasticsearch-7.15.2/config/analysis-ik/ vim new_word.dic
添加自定义分词
凯悦2.2. 词典配置
使用ik加载我们自定义的分词词典库
vim IKAnalyzer.cfg.xml
内容：
2.3. 重启es7IK Analyzer 扩展配置 new_word.dic
ps -ef|grep elasticsearch
kill -9 es进程号
cd /app/elasticsearch-7.15.2/ bin/elasticsearch -d2.4. 重新查看分词结果
# 查阅凯悦分词
GET /shop/_analyze
{
"analyzer": "ik_smart",
"text": "凯悦"
}
GET /shop/_analyze
{
"analyzer": "ik_max_word",
"text": "凯悦"
}
2.5. 重新搜索
GET /shop/_search
{
"query":{
"match": {"name":"凯悦"}
}
}
GET /shop/_search
发现一条数据都没查询出来，但是，数据都还在。
2.6. 重建分词索引索引创建的时候，是在ik分词器上当时没有“凯悦”这个词的时候。目前，我们凯悦酒店这条记录对应的记录”凯和悦”已经在索引成型，单字的”凯”和单字“悦”。因为在擦黄建索引的时候，并没有做分词的扩展分词库加载。
目前的问题，现在索引中存储的是”凯和悦”分开的，但是我搜索的时候，执行的凯悦，却是按照搜索当前search的分词器，也就是分出来的是”凯和悦”连字存在。
我搜索是2个字，但是倒排索引的时候是按照单字做搜引得，因此导致搜素数据为空。
解决方案：
第一种（第一次）：把索引全部删除，然后全量同步分词索引
第二种（推荐）：针对搜索的索引中包含“凯“或者“悦“的索引执行重建索引，其他的索引不重建索引。
# 重建凯悦分析索引
POST /shop/_update_by_query
{
"query": {
"bool": {
"must": [
{"term":{"name":"凯"}},
{"term":{"name":"悦"}}
]
}
}
}
2.7. 再次查询
GET /shop/_search
{
"query":{
"match": {"name":"凯悦"}
}
}
2.8. 数据分析
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : 2.0709352,
"hits" : [
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "9",
"_score" : 2.0709352,
"_source" : {
"price_per_man" : 176,
"remark_score" : 2.2,
"category_name" : "酒店",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.916Z",
"tags" : "落地大窗",
"location" : "31.306172,121.525843",
"seller_remark_score" : 3.0,
"id" : 9,
"name" : "凯悦酒店",
"seller_id" : 17,
"category_id" : 2
}
},
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "10",
"_score" : 1.7177677,
"_source" : {
"price_per_man" : 182,
"remark_score" : 0.5,
"category_name" : "酒店",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.918Z",
"tags" : "自助餐",
"location" : "31.196742,121.322846",
"seller_remark_score" : 3.0,
"id" : 10,
"name" : "凯悦嘉轩酒店",
"seller_id" : 17,
"category_id" : 2
}
},
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "11",
"_score" : 1.7177677,
"_source" : {
"price_per_man" : 74,
"remark_score" : 1.0,
"category_name" : "酒店",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.920Z",
"tags" : "自助餐",
"location" : "31.156899,121.238362",
"seller_remark_score" : 3.0,
"id" : 11,
"name" : "新虹桥凯悦酒店",
"seller_id" : 17,
"category_id" : 2
}
},
{
"_index" : "shop",
"_type" : "_doc",
"_id" : "12",
"_score" : 1.5828056,
"_source" : {
"price_per_man" : 71,
"remark_score" : 2.0,
"category_name" : "美食2",
"@version" : "1",
"seller_disabled_flag" : 0,
"@timestamp" : "2021-11-21T04:10:03.923Z",
"tags" : "有包厢",
"location" : "30.679819,121.651921",
"seller_remark_score" : 3.0,
"id" : 12,
"name" : "凯悦咖啡(新建西路店)",
"seller_id" : 17,
"category_id" : 1
}
}
]
}
}
从上面数据可以看出，符合预期结果！
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