引言

之前已经介绍了如何搭建elasticsearch服务端和简单的索引创建，和中文分词的支持。今天我们来说一说如何实现elasticsearch同时实现中文分词和pinyin分词。并且实现类似百度搜索栏的搜索建议的功能。

混合查询

实现混合查询有很多方式，这里介绍我认为是一个偷懒的方法，就是为你要拼音搜索的字段提供两个额外的字段，一个是全拼字段，一个是首字母缩写字段。我这里用的是官网的Employee的例子：

public class Employee implements Serializable {

private String firstName;

private String lastName;

private String pinyin;//firstName全拼

private String header;//firstName首字母缩写

private int age;

private String about;

private List interests;

....省略getter setter

接下来为index添加setting和mapping

XContentBuilder settings = XContentFactory.jsonBuilder();

settings.startObject()

.startObject("analysis")

.startObject("analyzer")

.startObject("ik_analyzer").field("tokenizer","ik_smart")

.endObject()

.endObject()

.endObject().endObject();

CreateIndexRequest createIndexRequest = new CreateIndexRequest(index).settings(settings);

CreateIndexResponse createIndexResponse = esClient.admin().indices().create(createIndexRequest).get();

logger.info("Index:{} created,response:{}", index, JSON.toJSON(createIndexResponse));

XContentBuilder builder = XContentFactory.jsonBuilder();

builder.startObject()

.startObject(type)

.startObject("properties")

.startObject("firstName").field("type", "string").field("analyzer","ik_smart")

/* .field("search_analyzer","ik_smart").field("preserve_separators",false) .field("preserve_position_increments",false)*/

.endObject()

.startObject("lastName").field("type", "string").field("analyzer","ik_smart")

.endObject()

.startObject("pinyin").field("type","string").field("analyzer","pinyin")

.startObject()

.startObject("header").field("type","string").field("analyzer","pinyin")

.startObject("about").field("type", "string").field("analyzer","ik_smart")

.endObject()

.startObject("interests").field("type", "string").field("analyzer","ik_smart")

.endObject()

.endObject()

.endObject()

.endObject();

PutMappingRequest putMappingRequest = new PutMappingRequest(index);

putMappingRequest.type(type);

putMappingRequest.source(builder);

PutMappingResponse putMappingResponse = esClient.admin().indices().putMapping(putMappingRequest).get();

logger.info("Mapping for `{}.{}` putted, response:{}", index, type, JSON.toJSON(putMappingResponse));

return true;

} catch (Exception e) {

logger.error("doCreateIndex", e);

return false;

}

添加几个测试用例，我这里直接用了批量插入索引的方法：

public Boolean bulkIndex(List jsonList){

if(esIndexTypes.get(index)==null) {

if(getMapping(index, indexType)) esIndexTypes.put(index,true);

}

BulkRequestBuilder bulkBuilder= esClient.prepareBulk();

for (String s : jsonList) {

IndexRequestBuilder requestBuilder = esClient.prepareIndex(index, indexType)

.setSource(s);

bulkBuilder.add(requestBuilder);

}

BulkResponse bulkResponse = bulkBuilder.execute().actionGet();

logger.info("index:{} bulk request,:response:{}",index,JSON.toJSON(bulkResponse));

return true;

}

@org.junit.Test

public void test(){

List list1 = new ArrayList<>(10000);

for (int i=0;i<10000;i++) {

Employee employee = new Employee();

employee.setFirstName("告白气球"+i);

employee.setPinyin("gaobaiqiqiu"+i);

employee.setHeader("gbqq");

employee.setLastName("周杰伦,日记");

employee.setAbout("呜啦啦啦火车笛\n" +

"\n" +

"随着奔腾的马蹄\n" +

"\n" +

"小妹妹吹着口琴\n" +

"\n" +

"夕阳下美了剪影\n" +

"\n" +

"我用子弹写日记,我泡妞看电影");

employee.setAge(18);

List list = new ArrayList();

list.add("喜欢打篮球");

list.add("在大晴天晒太阳");

list.add("泡妞看电影");

employee.setInterests(list);

list1.add(JSON.toJSONString(employee));

}

boolean index = esProxy.bulkIndex(list1);

}

最后直接搜gaobaiqiqiu或gbqq搜出来的数据像这样：

[{"firstName":"告白气球","lastName":"周杰伦,日记","pinyin":"gaobaiqiqiu","about":"呜啦啦啦火车笛\n\n随着奔腾的马蹄\n\n小妹妹吹着口琴\n\n夕阳下美了剪影\n\n我用子弹写日记,我泡妞看电影","header":"gbqq","interests":["喜欢打篮球","在大晴天晒太阳","泡妞看电影"],"age":18}]

如果直接搜告白搜出来的数据像这样:

[{"firstName":"告白气球","lastName":"周杰伦,日记","pinyin":"gaobaiqiqiu","about":"呜啦啦啦火车笛\n\n随着奔腾的马蹄\n\n小妹妹吹着口琴\n\n夕阳下美了剪影\n\n我用子弹写日记,我泡妞看电影","header":"gbqq","interests":["喜欢打篮球","在大晴天晒太阳","泡妞看电影"],"age":18}]

CompletionSuggestion查询建议

使用CompletionSuggestion时mapping需要改一下，实时推荐的字段type需要使用completion。

XContentBuilder builder = XContentFactory.jsonBuilder();

builder.startObject()

.startObject(type)

.startObject("properties")

.startObject("firstName").field("type", "completion").field("analyzer","ik_smart")

.field("search_analyzer","ik_smart").field("preserve_separators",false)

.field("preserve_position_increments",false)

.endObject()

.startObject("lastName").field("type", "string").field("analyzer","ik_smart")

.endObject()

.startObject("pinyin").field("type","string").field("analyzer","pinyin")

.startObject()

.startObject("header").field("type","string").field("analyzer","pinyin")

.startObject("about").field("type", "string").field("analyzer","ik_smart")

.endObject()

.startObject("interests").field("type", "string").field("analyzer","ik_smart")

.endObject()

.endObject()

.endObject()

.endObject();

查询的时候需要使用CompletionSuggestionBuilder.

public void searchSuggest(String str){

CompletionSuggestionBuilder suggestionBuilder = new CompletionSuggestionBuilder("firstName");

suggestionBuilder.analyzer("ik_smart");

suggestionBuilder.text(str);

SearchResponse response = esClient.prepareSearch(index).setTypes(indexType).setQuery(QueryBuilders.matchAllQuery())

.suggest(new SuggestBuilder().addSuggestion("my-suggest-1",suggestionBuilder)).get();

Suggest suggest= response.getSuggest();

CompletionSuggestion suggestion = suggest.getSuggestion("my-suggest-1");

List list = suggestion.getEntries();

for (int i = 0; i < list.size(); i++) {

List options = list.get(i).getOptions();

for (int j = 0; j < options.size(); j++) {

if (options.get(j) instanceof CompletionSuggestion.Entry.Option) {

CompletionSuggestion.Entry.Option op = options.get(j);

System.out.println(op.getScore()+"--"+op.getText());

}

}

}

}

你也可以使用restAPI：http://192.168.10.xxx:9200/megacorp/_search?pretty这里megacorp是indexName,

{ "size": 0,

"suggest": { "my-suggest-1": { "prefix": "someone li", "completion": { "field": "firstName" } } } }

查询出来的结果:

{

"took": 12,

"timed_out": false,

"_shards": { "total": 5, "successful": 5, "failed": 0 },

"hits": { "total": 0, "max_score": 0, "hits": [] },

"suggest": { "blog-suggest": [ { "text": "someone li", "offset": 0, "length": 10, "options": [ { "text": "someone like you", "_index": "megacorp", "_type": "employee", "_id": "AV_doqcXKY206Vs3lcCO", "_score": 1, "_source": { "about": "呜啦啦啦火车笛\n\n随着奔腾的马蹄\n\n小妹妹吹着口琴\n\n夕阳下美了剪影\n\n我用子弹写日记,我泡妞看电影", "age": 18, "firstName": "someone like you", "interests": [ "喜欢打篮球", "在大晴天晒太阳", "泡妞看电影" ], "lastName": "周杰伦,日记" } } ] } ] } }