ES7.x使用深分页和浅分页
//以关键字开头(优先级最高)
FunctionScoreQueryBuilder.FilterFunctionBuilder[] filterFunctionBuilders = new FunctionScoreQueryBuilder.FilterFunctionBuilder[]{
new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.termQuery("grade", "高"), ScoreFunctionBuilders.weightFactorFunction(3)),
new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.termQuery("grade", "中"), ScoreFunctionBuilders.weightFactorFunction(2)),
new FunctionScoreQueryBuilder.FilterFunctionBuilder(QueryBuilders.termQuery("grade", "低"), ScoreFunctionBuilders.weightFactorFunction(1))};
FunctionScoreQueryBuilder functionScoreQueryBuilder = QueryBuilders.functionScoreQuery(boolQueryBuilder,filterFunctionBuilders);
sourceBuilder.query(functionScoreQueryBuilder)
.sort("_score", SortOrder.DESC)
.sort("happen_time", SortOrder.DESC);
public Page searchSystemDoc(ParamPI paramPI) throws IOException, ParseException {
Page page = new Page(paramPI.getPageNum(),paramPI.getPageSize());
final Scroll scroll = new Scroll(TimeValue.timeValueSeconds(60));
// 1、创建search请求
SearchRequest searchRequest = new SearchRequest("syslog_system");
searchRequest.scroll(scroll);
// 2、用SearchSourceBuilder来构造查询请求体 ,请仔细查看它的方法，构造各种查询的方法都在这。
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder().trackTotalHits(true);
//Settings settings = Settings.builder().put("syslog_system.max_result_window", 500000000).build();
//match分析器，模糊匹配 term精准 multi_match多个字段同时进行匹配
// bool包含四种操作符，分别是must,should,must_not,query filter查询查询对结果进行缓存
//sourceBuilder.query(QueryBuilders.termQuery("age", 24));
//分页设置 浅分页 //深分页 scroll
// int from = (paramPI.getPageNum()-1)*paramPI.getPageSize();
// sourceBuilder.from(from);
//sourceBuilder.timeout(new TimeValue(60, TimeUnit.SECONDS));
sourceBuilder.size(paramPI.getPageSize());
//搜索条件
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
if(paramPI.getKeyword() != null){
QueryBuilder queryBuilder = QueryBuilders.matchPhraseQuery("name", paramPI.getKeyword());
boolQueryBuilder.should(queryBuilder);
}
if(paramPI.getAssetId() != null){
QueryBuilder queryBuilder = QueryBuilders.termQuery("asset_id",paramPI.getAssetId());
boolQueryBuilder.must(queryBuilder);
}
if(paramPI.getLogtype() != null ){
//elasticsearch 里默认的IK分词器是会将每一个中文都进行了分词的切割，所以你直接想查一整个词 加上.keyword
QueryBuilder queryBuilder = QueryBuilders.termQuery("type",paramPI.getLogtype());
boolQueryBuilder.must(queryBuilder);
}
QueryBuilder queryBuilder1 = QueryBuilders.rangeQuery("hapeen_time_stamp").from(paramPI.getCustomStartTime().getTime()).to(paramPI.getCustomEndTime().getTime());
boolQueryBuilder.must(queryBuilder1);
QueryBuilder queryBuilder2 = QueryBuilders.rangeQuery("s_ip_num").from(paramPI.getSip1()).to(paramPI.getSip2());
boolQueryBuilder.must(queryBuilder2);
QueryBuilder queryBuilder3 = QueryBuilders.rangeQuery("d_ip_num").from(paramPI.getDip1()).to(paramPI.getDip2());
boolQueryBuilder.must(queryBuilder3);
if(paramPI.getNetStruct() != null && !paramPI.getNetStruct().isEmpty()){
List list = paramPI.getNetStruct();
for(NetStruct netStruct : list){
QueryBuilder queryBuilder = QueryBuilders.rangeQuery("d_ip_num").from(netStruct.getStartIp()).to(netStruct.getEndIp());
boolQueryBuilder.must(queryBuilder);
}
}
sourceBuilder.query(boolQueryBuilder);
//将请求体加入到请求中
searchRequest.source(sourceBuilder);
//3、发送请求
SearchResponse searchResponse = restHighLevelClient.search(searchRequest,RequestOptions.DEFAULT);
//处理搜索命中文档结果
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits().value;
List list = new ArrayList<>();
String scrollId = null;
int pageNum = paramPI.getPageNum();
int i = 1;
while (searchResponse.getHits().getHits().length != 0){
if(i == pageNum){
//业务
for (SearchHit hit : hits.getHits()) {
Map sourceAsMap = hit.getSourceAsMap(); // 取成map对象
setDataSystem(sourceAsMap,list);
}
System.out.println("ES分页查询成功");
break;
}
i++;
//每次循环完后取得scrollId,用于记录下次将从这个游标开始取数
scrollId = searchResponse.getScrollId();
SearchScrollRequest scrollRequest = new SearchScrollRequest(scrollId);
scrollRequest.scroll(scroll);
searchResponse = restHighLevelClient.scroll(scrollRequest, RequestOptions.DEFAULT);
}
if(scrollId != null){
//清除滚屏
ClearScrollRequest clearScrollRequest = new ClearScrollRequest();
//也可以选择setScrollIds()将多个scrollId一起使用
clearScrollRequest.addScrollId(scrollId);
ClearScrollResponse clearScrollResponse = restHighLevelClient.clearScroll(clearScrollRequest,RequestOptions.DEFAULT);
}
page.setTotal(totalHits);
return (Page) page.setRecords(list);
} java连接ES7.x
@Bean
public RestHighLevelClient restHighLevelClient(){
final CredentialsProvider credentialsProvider =
new BasicCredentialsProvider();
credentialsProvider.setCredentials(AuthScope.ANY,
new UsernamePasswordCredentials("xxx", "xxx"));
//解析hostlist配置信息
String[] split = hostlist.split(",");
//创建HttpHost数组，其中存放es主机和端口的配置信息
HttpHost[] httpHostArray = new HttpHost[split.length];
for(int i=0;i所以将字段设置成keyword的时候查询的时候已有的值不会被分词。
说明text类型的字段会被分词，查询的时候如果用拆开查可以查询的到，但是要是直接全部查，就是查询不到。
1、query string search ：查询字符串搜索
2、query DSL ：特定领域的语言
3、query filter : 过滤查询
4、full-text search :（全文检索）
5、phrase search ：（短语搜索）
6、highlight search ：（高亮搜索）
https://blog.csdn.net/weixin_41244495/article/details/87776792
ES使用倒排索引 所以比较快
text字段会被分词 用于模糊
keyword字段不会被分词 用于精确
1, 2”会被拆分成[1, 2]，但是"1,2"是不拆分的，因为之间少了个空格
//搜索条件 考虑查询text keyword不同
match分词 模糊匹配 match_phrase会被分词
term精准不分词 text字段 terms，in检索
range 范围
扫描所有倒排索引, 性能较差
prefix 前缀检索
wildcard 通配符检索
regexp 正则
fuzzy 纠错检索
boost评分权重 令满足某个条件的文档的得分更高, 从而使得其排名更靠前
multi_match多个字段同时进行匹配
bool包含四种操作符，分别是must,should,must_not,query filter过滤查询查询对结果进行缓存
phrase search（短语搜索） full-text search（全文检索）
elasticsearch 里默认的IK分词器是会将每一个中文都进行了分词的切割，所以你直接想查一整个词 加上.keyword
ES的默认分词设置是standard 其中f‘-’不在了 simple 分析器当它遇到只要不是字⺟的字符 分词
* matchAllQuery: 查询索引库中所有的数据;
* termQuery: 词条查询,词条的完全匹配;
* wildcardQuery: 模糊查询(* ? 通配符);
* queryStringQuery: 将查询条件分词后根据词条匹配 默认返回的并集;
* boolQuery: must(and), should(or), must_not(not);
sort自定义排序