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개발잡부
[900] Java High Level REST Client Query 3 본문
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인덱스 생성 setting, mapping Class
너무 복잡스럽네.. 나중에 index template 으로 변경해야 할듯..
package com.bbongdoo.doo.apis;
import org.elasticsearch.client.indices.CreateIndexRequest;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.XContentFactory;
import java.io.IOException;
public class IndexGoodsApi {
public static CreateIndexRequest createIndex(String indexName) throws IOException {
CreateIndexRequest request = new CreateIndexRequest(indexName);
request.settings(Settings.builder()
.put("index.number_of_shards", 3)
.put("index.number_of_replicas", 0)
);
XContentBuilder settingBuilder = XContentFactory.jsonBuilder()
.startObject()
.field("number_of_shards", 3)
.field("number_of_replicas", 0)
.startObject("analysis")
.startObject("tokenizer")
.startObject("doo-nori-tokenizer")
.field("type", "nori_tokenizer")
.field("decompound_mode", "mixed")
.field("user_dictionary", "user_dictionary.txt")
.endObject()
.endObject()
.startObject("analyzer")
.startObject("jamo-analyzer")
.field("type", "custom")
.field("tokenizer", "standard")
.array("filter", new String[]{
"doo-jamo"
}
)
.endObject()
.startObject("chosung-analyzer")
.field("type", "custom")
.field("tokenizer", "standard")
.array("filter", new String[]{
"doo-chosung"
}
)
.endObject()
.startObject("doo-nori-analyzer")
.field("type", "custom")
.field("tokenizer", "doo-nori-tokenizer")
.array("filter", new String[]{
"doo-nori-posfilter",
"nori_readingform",
"doo-synonym-filter",
"doo-stop-filter"
}
)
.endObject()
.endObject()
.startObject("filter")
.startObject("doo-nori-posfilter")
.field("type", "nori_part_of_speech")
.array("stoptaags", new String[]{
"E", "IC", "J", "MAG", "MM", "NA", "NR", "SC",
"SE", "SF", "SH", "SL", "SN", "SP", "SSC", "SSO",
"SY", "UNA", "UNKNOWN", "VA", "VCN", "VCP", "VSV",
"VV", "VX", "XPN", "XR", "XSA", "XSN", "XSV"
}
)
.endObject()
.startObject("doo-synonym-filter")
.field("type", "synonym")
.field("synonyms_path", "synonymsFilter.txt")
.endObject()
.startObject("doo-stop-filter")
.field("type", "stop")
.field("stopwords_path", "stopFilter.txt")
.endObject()
.endObject()
.endObject()
.endObject();
request.settings(settingBuilder);
XContentBuilder builder = XContentFactory.jsonBuilder();
builder.startObject();
{
builder.startObject("properties");
{
builder.startObject("id");
{
builder.field("type", "long");
}
builder.endObject();
builder.startObject("name");
{
builder.field("type", "text");
builder.startObject("fields");
builder.startObject("nori");
builder.field("type", "text");
builder.field("analyzer", "doo-nori-analyzer");
builder.endObject();
builder.startObject("jamo");
builder.field("type", "text");
builder.field("analyzer", "jamo-analyzer");
builder.endObject();
builder.startObject("chosung");
builder.field("type", "text");
builder.field("analyzer", "chosung-analyzer");
builder.endObject();
builder.startObject("keyword");
builder.field("type", "keyword");
builder.endObject();
builder.endObject();
}
builder.endObject();
builder.startObject("category");
{
builder.field("type", "text");
builder.startObject("fields");
builder.startObject("keyword");
builder.field("type", "keyword");
builder.endObject();
builder.endObject();
}
builder.endObject();
builder.startObject("category1");
{
builder.field("type", "keyword");
}
builder.endObject();
builder.startObject("category2");
{
builder.field("type", "keyword");
}
builder.endObject();
builder.startObject("category3");
{
builder.field("type", "keyword");
}
builder.endObject();
builder.startObject("category4");
{
builder.field("type", "keyword");
}
builder.endObject();
builder.startObject("category5");
{
builder.field("type", "keyword");
}
builder.endObject();
builder.startObject("price");
{
builder.field("type", "long");
}
builder.endObject();
builder.startObject("brand");
{
builder.field("type", "keyword");
}
builder.endObject();
builder.startObject("keyword");
{
builder.field("type", "keyword");
}
builder.endObject();
builder.startObject("image");
{
builder.field("type", "text");
}
builder.endObject();
builder.startObject("popular");
{
builder.field("type", "integer");
builder.field("null_value", "1");
}
builder.endObject();
builder.startObject("weight");
{
builder.field("type", "float");
}
builder.endObject();
builder.startObject("feature_vector");
{
builder.field("type", "dense_vector");
builder.field("dims", 512);
}
builder.endObject();
builder.startObject("type");
{
builder.field("type", "keyword");
}
builder.endObject();
builder.startObject("created_time");
{
builder.field("type", "date");
builder.field("format", "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis||strict_date_hour_minute_second_millis||strict_date_optional_time");
}
builder.endObject();
builder.startObject("updated_time");
{
builder.field("type", "date");
builder.field("format", "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis||strict_date_hour_minute_second_millis||strict_date_optional_time");
}
builder.endObject();
}
builder.endObject();
}
builder.endObject();
request.mapping(builder);
return request;
}
}
상품검색 Service
package com.bbongdoo.doo.service;
import com.bbongdoo.doo.component.TextEmbedding;
import com.bbongdoo.doo.dto.TextEmbeddingDTO;
import com.bbongdoo.doo.model.response.CommonResult;
import com.google.common.base.Functions;
import lombok.RequiredArgsConstructor;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.lucene.search.function.FunctionScoreQuery;
import org.elasticsearch.common.lucene.search.function.ScoreFunction;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.functionscore.*;
import org.elasticsearch.script.Script;
import org.elasticsearch.script.ScriptType;
import org.elasticsearch.script.mustache.SearchTemplateRequest;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.springframework.stereotype.Service;
import java.io.IOException;
import java.util.*;
import static java.util.Collections.emptyMap;
@Service
@RequiredArgsConstructor
public class GoodsService {
private final ResponseService responseService;
private final RestHighLevelClient client;
private final String ALIAS = "goods";
public CommonResult getProducts(String searchWord) {
SearchRequest searchRequest = new SearchRequest();
searchRequest.indices(ALIAS);
try {
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
Vector<Double> vectors = TextEmbedding.getVector(
TextEmbeddingDTO.builder()
.tensorApiUrl("http://localhost:5000/vectors")
.keyword(searchWord).build()
);
// String[] includeFields = new String[]{"name", "category"};
String[] includeFields = new String[]{};
String[] excludeFields = new String[]{"feature_vector"};
searchSourceBuilder.fetchSource(includeFields, excludeFields);
Map<String, Object> map = new HashMap<>();
map.put("query_vector", vectors);
FunctionScoreQueryBuilder functionScoreQueryBuilder = new FunctionScoreQueryBuilder(
QueryBuilders.multiMatchQuery(searchWord, "name", "category"),
new FunctionScoreQueryBuilder.FilterFunctionBuilder[]{
new FunctionScoreQueryBuilder.FilterFunctionBuilder(
new ScriptScoreFunctionBuilder(
new Script(
ScriptType.INLINE,
Script.DEFAULT_SCRIPT_LANG,
"cosineSimilarity(params.query_vector, 'feature_vector') * doc['weight'].value * doc['popular'].value / doc['name.keyword'].length + doc['category.keyword'].length",
map)
)
)
}
);
searchSourceBuilder.query(functionScoreQueryBuilder);
searchSourceBuilder.size(8);
searchRequest.source(searchSourceBuilder);
System.out.println(searchRequest.source());
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
List<Map<String, Object>> returnValue = new ArrayList<>();
SearchHit[] results = searchResponse.getHits().getHits();
Arrays.stream(results).forEach(hit -> {
Map<String, Object> result = hit.getSourceAsMap();
System.out.println(result.get("name"));
returnValue.add(result);
});
return responseService.getListResult(returnValue);
} catch (IOException e) {
e.printStackTrace();
}
return new CommonResult();
}
}
{
"size":8,
"query":{
"function_score":{
"query":{
"multi_match":{
"query":"나이키 남성 운동화",
"fields":[
"category^1.0",
"name^1.0"
],
"type":"best_fields",
"operator":"OR",
"slop":0,
"prefix_length":0,
"max_expansions":50,
"zero_terms_query":"NONE",
"auto_generate_synonyms_phrase_query":true,
"fuzzy_transpositions":true,
"boost":1.0
}
},
"functions":[
{
"filter":{
"match_all":{
"boost":1.0
}
},
"script_score":{
"script":{
"source":"cosineSimilarity(params.query_vector, 'feature_vector') * doc['weight'].value * doc['popular'].value / doc['name.keyword'].length + doc['category.keyword'].length",
"lang":"painless",
"params":{
"query_vector":[
-0.01783534698188305,
0.028291134163737297,
-0.051035501062870026,
0.054820429533720016,
0.027929922565817833,
0.017169641330838203,
0.011979538016021252,
-0.05850313603878021,
0.044365379959344864,
0.009025814011693,
-0.03733707591891289,
-0.10298466682434082,
0.02317744866013527,
-0.07803352922201157,
-0.020095884799957275,
-0.008477125316858292,
0.025829441845417023,
-0.038644202053546906,
-0.04253268241882324,
-0.05130152776837349,
-0.03544012829661369,
0.009226053021848202,
0.07006046175956726,
0.01600527949631214,
0.033890847116708755,
-0.046707652509212494,
-0.03490631282329559,
0.013379461131989956,
-0.028714260086417198,
-0.01032843068242073,
0.029945025220513344,
0.01121340598911047,
-0.00766092911362648,
-0.043811339884996414,
0.011022261343896389,
0.032461993396282196,
-0.05491628125309944,
-0.04712033271789551,
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-0.02819782681763172,
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0.05998484045267105,
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0.07570209354162216,
0.03409837186336517,
-0.013013171032071114,
0.010583481751382351,
0.06911060214042664,
-0.018828244879841805,
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0.021606246009469032,
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0.061350952833890915,
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}
],
"score_mode":"multiply",
"max_boost":3.4028235E38,
"boost":1.0
}
},
"_source":{
"includes":[
],
"excludes":[
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]
}
}
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