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大家好，我是你們的朋友架構(gòu)君，一個會寫代碼吟詩的架構(gòu)師。

1. 業(yè)務(wù)場景概述

目標是實現(xiàn)一個公司的申請審批流程，整個業(yè)務(wù)流程涉及到兩種角色，分別為商務(wù)角色與管理員角色。整個流程如下圖所示：

核心流程總結(jié)為一句話：商務(wù)角色申請?zhí)砑庸竞笥晒芾韱T進行審批。

商務(wù)在添加公司時，可能為了方便，直接填寫公司簡稱，而公司全稱可能之前已經(jīng)被添加過了，為了防止添加重復(fù)的公司，所以管理員在針對公司信息審批之前，需要查看以往添加的公司信息里有無同一個公司。

2. 實現(xiàn)思路

以上是一個業(yè)務(wù)場景的大概介紹。從技術(shù)層面需要考慮實現(xiàn)的功能點：

• ? 分詞

• ? 與庫里已有數(shù)據(jù)進行匹配

• ? 按照匹配度對結(jié)果進行排序

分詞功能有現(xiàn)成的分詞器，所以整個需求的核心重點在于如何與數(shù)據(jù)庫中的數(shù)據(jù)匹配并按照匹配度排序。

3. 模糊匹配技術(shù)選型

• ? 方案一：引入ES

• ? 方案二：利用MySQL實現(xiàn)

本系統(tǒng)規(guī)模較小，單純?yōu)榱藢崿F(xiàn)這個功能引入ES成本較大，還要涉及到數(shù)據(jù)同步等問題，系統(tǒng)復(fù)雜性會提高，所以盡量使用MySQL已有的功能進行實現(xiàn)。

MySQL提供了以下三種模糊搜索的方式：

• ? like匹配： 要求模式串與整個目標字段完全匹配；

• ? RegExp正則匹配： 要求目標字段包含模式串即可；

• ? Fulltext全文索引： 在字段類型為CHAR、VARCHAR、TEXT的列上創(chuàng)建全文索引，執(zhí)行SQL進行查詢。

針對于上述業(yè)務(wù)場景，對相關(guān)技術(shù)進行優(yōu)劣分析：

• ? like匹配： 無法滿足需求，所以pass；

• ? 全文索引： 可定制性差，不支持任意匹配查詢，pass；

• ? 正則匹配： 可實現(xiàn)任意模式匹配，缺點在于執(zhí)行效率不如全文索引。

針對于這個場景，記錄數(shù)目相對來說沒有那么多，所以對于效率稍低的結(jié)果可以接受，因此技術(shù)選型方面采用RegExp正則匹配來實現(xiàn)模糊匹配的需求。

4. 實現(xiàn)效果展示

5. 核心代碼

整個邏輯基于 提取公司名稱關(guān)鍵信息 -->分詞 --> 匹配 三個核心步驟。

5.1 提取公司關(guān)鍵信息

對輸入的公司名稱去除無用信息，保留關(guān)鍵信息。這里的無用信息指的是地名，圓括號，以及集團，股份，有限等。

匹配前處理公司名稱

/**
 * 匹配前去除公司名稱的無意義信息
 * @param targetCompanyName
 * @return
 */
privateStringformatCompanyName(String targetCompanyName){

Stringregex="(?<province>[^省]+自治區(qū)|.*?省|.*?行政區(qū)|.*?市)"+
"?(?<city>[^市]+自治州|.*?地區(qū)|.*?行政單位|.+盟|市轄區(qū)|.*?市|.*?縣)"+
"?(?<county>[^(區(qū)|市|縣|旗|島)]+區(qū)|.*?市|.*?縣|.*?旗|.*?島)"+
"?(?<village>.*)";
Matchermatcher=Pattern.compile(regex).matcher(targetCompanyName);
while(matcher.find()){
Stringprovince= matcher.group("province");
        log.info("province:{}",province);
if(StringUtils.isNotBlank(province)&& targetCompanyName.contains(province)){
            targetCompanyName = targetCompanyName.replace(province,"");
}
        log.info("處理完省份的公司名稱:{}",targetCompanyName);
Stringcity= matcher.group("city");
        log.info("city:{}",city);
if(StringUtils.isNotBlank(city)&& targetCompanyName.contains(city)){
            targetCompanyName = targetCompanyName.replace(city,"");
}
        log.info("處理完城市的公司名稱:{}",targetCompanyName);
Stringcounty= matcher.group("county");
        log.info("county:{}",county);
if(StringUtils.isNotBlank(county)&& targetCompanyName.contains(county)){
            targetCompanyName = targetCompanyName.replace(county,"");
}
        log.info("處理完區(qū)縣級的公司名稱:{}",targetCompanyName);
}
String[][] address =AddressUtil.ADDRESS;
for(String[] city: address){
for(String b : city ){
if(targetCompanyName.contains(b)){
                targetCompanyName = targetCompanyName.replace(b,"");
}
}
}
    log.info("處理后的公司名稱:{}",targetCompanyName);
return targetCompanyName;
}

地名工具類

public classAddressUtil{
publicstaticfinalString[][] ADDRESS ={
{"北京"},
{"天津"},
{"安徽","安慶","蚌埠","亳州","巢湖","池州","滁州","阜陽","合肥","淮北","淮南","黃山","六安","馬鞍山","宿州","銅陵","蕪湖","宣城"},
{"澳門"},
{"香港"},
{"福建","福州","龍巖","南平","寧德","莆田","泉州","廈門","漳州"},
{"甘肅","白銀","定西","甘南藏族自治州","嘉峪關(guān)","金昌","酒泉","蘭州","臨夏回族自治州","隴南","平?jīng)?,"慶陽","天水","武威","張掖"},
{"廣東","潮州","東莞","佛山","廣州","河源","惠州","江門","揭陽","茂名","梅州","清遠","汕頭","汕尾","韶關(guān)","深圳","陽江","云浮","湛江","肇慶","中山","珠海"},
{"廣西","百色","北海","崇左","防城港","貴港","桂林","河池","賀州","來賓","柳州","南寧","欽州","梧州","玉林"},
{"貴州","安順","畢節(jié)地區(qū)","貴陽","六盤水","黔東南苗族侗族自治州","黔南布依族苗族自治州","黔西南布依族苗族自治州","銅仁地區(qū)","遵義"},
{"海南","?？?,"三亞","直轄縣級行政區(qū)劃"},
{"河北","保定","滄州","承德","邯鄲","衡水","廊坊","秦皇島","石家莊","唐山","邢臺","張家口"},
{"河南","安陽","鶴壁","焦作","開封","洛陽","漯河","南陽","平頂山","濮陽","三門峽","商丘","新鄉(xiāng)","信陽","許昌","鄭州","周口","駐馬店"},
{"黑龍江","大慶","大興安嶺地區(qū)","哈爾濱","鶴崗","黑河","雞西","佳木斯","牡丹江","七臺河","齊齊哈爾","雙鴨山","綏化","伊春"},
{"湖北","鄂州","恩施土家族苗族自治州","黃岡","黃石","荊門","荊州","十堰","隨州","武漢","咸寧","襄樊","孝感","宜昌"},
{"湖南","長沙","常德","郴州","衡陽","懷化","婁底","邵陽","湘潭","湘西土家族苗族自治州","益陽","永州","岳陽","張家界","株洲"},
{"吉林","白城","白山","長春","吉林","遼源","四平","松原","通化","延邊朝鮮族自治州"},
{"江蘇","常州","淮安","連云港","南京","南通","蘇州","宿遷","泰州","無錫","徐州","鹽城","揚州","鎮(zhèn)江"},
{"江西","撫州","贛州","吉安","景德鎮(zhèn)","九江","南昌","萍鄉(xiāng)","上饒","新余","宜春","鷹潭"},
{"遼寧","鞍山","本溪","朝陽","大連","丹東","撫順","阜新","葫蘆島","錦州","遼陽","盤錦","沈陽","鐵嶺","營口"},
{"內(nèi)蒙古","阿拉善盟","巴彥淖爾","包頭","赤峰","鄂爾多斯","呼和浩特","呼倫貝爾","通遼","烏海","烏蘭察布","錫林郭勒盟","興安盟"},
{"寧夏回族","固原","石嘴山","吳忠","銀川","中衛(wèi)"},
{"青海","果洛藏族自治州","海北藏族自治州","海東地區(qū)","海南藏族自治州","海西蒙古族藏族自治州","黃南藏族自治州","西寧","玉樹藏族自治州"},
{"山東","濱州","德州","東營","菏澤","濟南","濟寧","萊蕪","聊城","臨沂","青島","日照","泰安","威海","濰坊","煙臺","棗莊","淄博"},
{"山西","長治","大同","晉城","晉中","臨汾","呂梁","朔州","太原","忻州","陽泉","運城"},
{"陜西","安康","寶雞","漢中","商洛","銅川","渭南","西安","咸陽","延安","榆林"},
{"上海"},
{"四川","阿壩藏族羌族自治州","巴中","成都","達州","德陽","甘孜藏族自治州","廣安","廣元","樂山","涼山彝族自治州","瀘州","眉山","綿陽","內(nèi)江","南充","攀枝花","遂寧","雅安","宜賓","資陽","自貢"},
{"西藏","阿里地區(qū)","昌都地區(qū)","拉薩","林芝地區(qū)","那曲地區(qū)","日喀則地區(qū)","山南地區(qū)"},
{"新疆維吾爾","阿克蘇地區(qū)","阿勒泰地區(qū)","巴音郭楞蒙古自治州","博爾塔拉蒙古自治州","昌吉回族自治州","哈密地區(qū)","和田地區(qū)","喀什地區(qū)","克拉瑪依","克孜勒蘇柯爾克孜自治州","塔城地區(qū)","吐魯番地區(qū)","烏魯木齊","伊犁哈薩克自治州","直轄縣級行政區(qū)劃"},
{"云南","保山","楚雄彝族自治州","大理白族自治州","德宏傣族景頗族自治州","迪慶藏族自治州","紅河哈尼族彝族自治州","昆明","麗江","臨滄","怒江僳僳族自治州","普洱","曲靖","文山壯族苗族自治州","西雙版納傣族自治州","玉溪","昭通"},
{"浙江","杭州","湖州","嘉興","金華","麗水","寧波","衢州","紹興","臺州","溫州","舟山"},
{"重慶"},
{"臺灣","臺北","高雄","基隆","臺中","臺南","新竹","嘉義"},
};
}

5.2 分詞相關(guān)代碼

pom文件：引入IK分詞器相關(guān)依賴

 <!-- ikAnalyzer 中文分詞器  -->
<dependency>
<groupId>com.janeluo</groupId>
<artifactId>ikanalyzer</artifactId>
<version>2012_u6</version>
<exclusions>
<exclusion>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-core</artifactId>
</exclusion>
<exclusion>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-queryparser</artifactId>
</exclusion>
<exclusion>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-analyzers-common</artifactId>
</exclusion>
</exclusions>
</dependency>

<!--  lucene-queryParser 查詢分析器模塊 -->
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-queryparser</artifactId>
<version>7.3.0</version>
</dependency>

IKAnalyzerSupport類：用于配置分詞器

@Slf4j
publicclassIKAnalyzerSupport{
/**
     * IK分詞
     * @param target
     * @return
     */
publicstaticList<String>iKSegmenterToList(String target)throwsException{
if(StringUtils.isEmpty(target)){
returnnewArrayList();
}
List<String> result =newArrayList<>();
StringReadersr=newStringReader(target);
// false:關(guān)閉智能分詞 (對分詞的精度影響較大)
IKSegmenterik=newIKSegmenter(sr,true);
Lexeme lex;
while((lex=ik.next())!=null){
StringlexemeText= lex.getLexemeText();
            result.add(lexemeText);
}
return result;
}
}

ServiceImpl類：進行分詞處理

 /**
 * 對目標公司名稱進行分詞
 * @param targetCompanyName
 * @return
 */
privateStringsplitWord(String targetCompanyName){
    log.info("對處理后端公司名稱進行分詞");

List<String> splitWord =newArrayList<>();
Stringresult= targetCompanyName;
try{
        splitWord = iKSegmenterToList(targetCompanyName);
        result =  splitWord.stream().map(String::valueOf).distinct().collect(Collectors.joining("|"));
        log.info("分詞結(jié)果:{}",result);
}catch(Exception e){
        log.error("分詞報錯:{}",e.getMessage());
}
return result;
}

5.3 匹配

ServiceImpl類：匹配核心代碼

public JsonResultmatchCompanyName(CompanyDTO companyDTO, String accessToken, String localIp){
// 對公司名稱進行處理
StringsourceCompanyName= companyDTO.getCompanyName();
StringtargetCompanyName= sourceCompanyName;
    log.info("處理前公司名稱:{}",targetCompanyName);
// 處理圓括號
    targetCompanyName = targetCompanyName.replaceAll("[（]|[）]|[(]|[)]","");
// 處理公司相關(guān)關(guān)鍵詞
    targetCompanyName = targetCompanyName.replaceAll("[(集團|股份|有限|責任|分公司)]","");

if(!targetCompanyName.contains("銀行")){
// 去除行政區(qū)域
        targetCompanyName = formatCompanyName(targetCompanyName);
}
// 分詞
StringsplitCompanyName= splitWord(targetCompanyName);
//  匹配
List<Company> matchedCompany = companyRepository.queryMatchCompanyName(splitCompanyName,targetCompanyName);

List<String> result =newArrayList();
for(Company companyInfo : matchedCompany){
        result.add(companyInfo.getCompanyName());
if(companyDTO.getCompanyId().equals(companyInfo.getCompanyId())){
            result.remove(companyInfo.getCompanyName());
}
}
returnJsonResult.successResult(result);
}

Repository類：編寫SQL語句

/**  
* 模糊匹配公司名稱  
* @param companyNameRegex 分詞后的公司名稱
* @param companyName 分詞前的公司名稱  
* @return  
*/
@Query(value = 
"SELECT * FROM company WHERE isDeleted = '0' and companyName REGEXP ?1 
ORDER BY length(REPLACE(companyName,?2,''))/length(companyName) ",
nativeQuery = true)  
List<Company> queryMatchCompanyName(String companyNameRegex,String companyName);

按照匹配度排序這個功能點，LENGTH(companyName)返回companyName的長度，LENGTH(REPLACE(companyName, ?2, ''))計算出companyName中關(guān)鍵詞出現(xiàn)的次數(shù)。通過這種方式，我們可以根據(jù)匹配程度進行排序，匹配次數(shù)越多的公司名稱排序越靠前。