ElasticSearch索引操作总结归纳便于后期使用查找

Index索引操作

一、使用kibana工具操作索引

1.索引类型:

text/keyword、
整数类型、
浮点类型、
日期类型、
boolean 、
array类型(其实就是josn对象中数组写法”[{},{}]”)、
Object类型(其实就是一个json对象)

2.创建索引和映射对象

PUT /索引库名 
{
    
    "mappings": {
    
        "类型名称":{
    //类似于数据库中的不同表字段名：任意填写 ，相当于表的名称。
            "properties": {
    
                "字段名": {
    
                    "type": "类型", 
                    "index": true， 
                    "store": true， 
                    "analyzer": "分词器"//比如ik_max_word
                } 
            } 
        } 
    }

先分析，那些需要建立索引放入到索引库中，比如

#创建索引结构 
PUT sku {
    
    "mappings": {
    
        "doc":{
    
            "properties":{
    
                "name":{
    
                    "type":"text", 
                    "analyzer":"ik_smart" 
                },
                "price":{
    
                    "type":"integer" 
                },
                "image":{
    
                    "type":"text",
                    "index":false
                },
                "createTime":{
    
                    "type":"date" 
                },
                "spuId":{
   
                    "type":"text" 
                },
                "categoryName":{
   
                    "type":"keyword" 
                },
                "brandName":{
   
                    "type":"keyword" 
                },
                "spec":{
   
                    "type":"object" 
                },
                "saleNum":{
   
                    "type":"integer" 
                },
                "commentNum":{
    
                    "type":"integer" 
                } 
            } 
        } 
    }
}

3.添加文档

分为指定id，和不指定id。如果不指定id，系统会自动生成。

POST 索引库名/ 类型名  //POST 索引库名/ 类型名/id值
{
   
"key":"value"
}

### 插入文档   手动指定指定id写法:POST sku/doc/3
POST sku/doc
{
   
  "name":"小米手机",
  "price":200000,
  "spuId":101,
  "createTime":"2019-05-01",
  "brandName":"小米",
  "categerName":"手机",
  "saleNum":1203,
  "commentNum":2356,
  "spec":{
   
    "网络制式":"移动4G",
    "屏幕尺寸":"4.5"
  }
}

在java中如何体现添加添加spec??

Map skuMap = new HashMap();

Map specMap = new HashMap();

specMap.put("网络制式","移动4G");

specMap.put("屏幕尺寸","4.5");

skuMap.put("spec",specMap);

4.查询索引

查询的基本格式：

Get 索引名称/_search
{
   
    "query":{
   
        "查询类型":{
   
            "查询条件":"查询条件值"
        }
    }
}

query代表一个查询对象，里面可以有不同的查询属性

查询类型
- match_all、match、term(根据字段)、range(根据区间)、等。
查询条件：查询条件会根据类型的不同，写法也有差异。比如bool、过滤查询/分组查询

4.1 查询所有-match_all

查询类型为match_all相当于_search

Get sku/_search
{
   
    "query":{
   
        "match_all":{
   }
    }
}

4.2 匹配查询-match

查询类型match

GET sku/_search
{
   
    "query":{
   
        "match":{
   
            "name":"手机"
        }
    }
}

只要name中包含手机、手、机都会被查询出来.会对手机进行分词，多个词语之间的关系默认为or。如果要精准查询，需要将操作改为and关系.

GET sku/_search
{
   
    "query":{
   
        "match":{
   
            "name":{
   
                "query":"小米手机",
                "operator":"and"
            }
        }
    }
}

4.3 多字段查询-multi_match

查询类型名称为:“multi_match”

Get sku/_search
{
   
    "query":{
   
        "multi_match":{
   
            "query":"小米",
            "fields":["name","brandName","categoryName"]
        }
    }
}

"fields":["name","brandName","categoryName"]从这些字段查询小米

4.4 词条匹配-term

查询类型名称为:“term”,精确值匹配，可能是数字、时间、布尔或者未分词的字符串。

###单词条匹配
GET sku/_search
{
   
    "query":{
   
        "term":{
   
            "price":20000
        }
    }
}

###多词条匹配
GET sku/_search
{
   
    "query":{
   
        "term":{
   
            "price":[200000,300000]
        }
    }
}

4.5 布尔组合查询bool

查询类型为:“bool”。把”match”/“match_all”/“term”/“terms”等查询方式通过”must(与)”、“must_not（非）”、”should(或)”的方式进行组合。

#查询名称包含手机,并且品牌名称为小米的数据
Get sku/_search
{
   
    "query":{
   
        "bool":{
   
            "must":[
                "match":{
   
                "name":"手机"
                },
        		"term":{
   
                    "brandName":"小米"
                }
            ]
        }
    }
}

4.6 过滤查询-bool-filter

过滤器查询的效率比查询效率高，过滤查询不会计算判断文档匹配度的得分.推荐尽量使用过滤

器去实现查询或者过滤器和查询共同使用。

过滤查询场景:我们希望查询出来的文档不需要对他进行匹配度评分、简单的进行筛选一下

查询类型为:“bool”

GET sku/_search
{
   
    "query":{
   
        "bool":{
   
            "filter":{
   
                "match":{
   "brandName":"小米"}
            }
        }
    }
}

4.7 分组查询-aggs

#分组查询
GET sku/_search
{
   
 ### aggs 表示分组 
  "size": 0, ###如果size:0 表示不用展示hits:[] 里面的数据了  
  "aggs": {
   
    "sku_category": {
    //分组展示的名称
      "terms": {
   
        "field": "price"
      }
    }
  }
}

#多个分组条件
GET sku/_search
{
   
  
   "size": 0, ###如果size:0 表示不用展示hits:[] 里面的数据了
  "aggs": {
   
    "sku_category": {
   //分组展示的名称
      "terms": {
   
        "field": "price" //分组字段
      }
    },
    "sku_brand": {
   
      "terms": {
   
        "field": "brandName"
      }
    }
    
  }
}

###Mysql中多个字段的分组
####对Subject_Selection表中的数据进行分组，
####将具有相同Subject和Semester字段值的记录放到同一个分组里去， 
####然后对每个分组中的数据应用聚合函数（COUNT，SUM， AVG，etc）。
####分组条件使用having
SELECT Subject, Semester, Count(*)FROM Subject_Selection GROUP BY Subject, Semester

二、使用java操作索引

使用java high level rest client。elasticsearch 版本需要在ES5以上。

创建索引和映射对象，可以使用kibana工具进行创建，然后添加、查询、修改索引使用java代码进行操作。

1.新增修改数据

HttpHost : url地址封装

RestClientBuilder： rest客户端构建器

RestHighLevelClient： rest高级客户端

HttpHost、RestClientBuild、RestHighLevelClient 这三个类用于连接ElasticSearch。

IndexRequest：新增或修改请求

IndexResponse：新增或修改的响应结果

BulkRequest：批量请求（用于增删改操作） ;BulkRequest里面可以装入多个IndexRequest。

BulkResponse：批量请求（用于增删改操作）

1.1 新增修改单条数据

import org.apache.http.HttpHost;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import java.util.HashMap;
import java.util.Map;
public class Demo1 {

public static void main(String[] args) {

//1.链接rest接口
HttpHost http = new HttpHost("127.0.0.1", 9200, "http");
RestClientBuilder restClientBuilder = RestClient.builder(http);
RestHighLevelClient restHighLevelClient = new RestHighLevelClient(restClientBuilder);
//2.封装请求对象 (指定id)
IndexRequest indexRequest = new IndexRequest("sku", "doc", "3");
Map skuMap = new HashMap();
skuMap.put("name", "华为p30");
skuMap.put("name", "华为p30pro");
skuMap.put("brandName", "华为");
skuMap.put("categoryName", "手机");
skuMap.put("price", 1010221);
skuMap.put("createTime", "2019-05-01");
skuMap.put("saleNum", 101021);
skuMap.put("commentNum", 10102321);
//spec在索引库的类型为Object ，在java代码中我们使用map进行封装spec，然后在封装到外面一层的map。
Map spec = new HashMap();
spec.put("网络制式", "移动4G");
spec.put("屏幕尺寸", "5");
skuMap.put("spec", spec);
//除了使用Map,也可以使用实体类进行封装。
indexRequest.source(skuMap);
//3.获取请求结果
try{

IndexResponse indexResponse = restHighLevelClient.index(indexRequest, RequestOptions.DEFAULT);
//执行状态
int status = indexResponse.status().getStatus();
System.out.println(status);
}catch (Exception e){

e.printStackTrace();
}
//关闭资源流
}
}

1.2 批量插入

import org.apache.http.HttpHost;
import org.elasticsearch.action.bulk.BulkRequest;
import org.elasticsearch.action.bulk.BulkResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import java.util.HashMap;
import java.util.Map;
public class Demo2 {

public static void main(String[] args) {

//1.连接rest接口
HttpHost http = new HttpHost("127.0.0.1", 9200, "http");
RestClientBuilder builder = RestClient.builder(http);
//rest构建器 
RestHighLevelClient restHighLevelClient = new RestHighLevelClient(builder);
//高级客户端对象 
// 2.封装请求对象
BulkRequest bulkRequest = new BulkRequest();
//----------------------
IndexRequest indexRequest = new IndexRequest("sku", "doc", "4");
Map skuMap = new HashMap();
skuMap.put("name", "华为p30pro 火爆上市");
skuMap.put("brandName", "华为");
skuMap.put("categoryName", "手机");
skuMap.put("price", 1010221);
skuMap.put("createTime", "2019‐05‐01");
skuMap.put("saleNum", 101021);
skuMap.put("commentNum", 10102321);
Map spec = new HashMap();
spec.put("网络制式", "移动4G");
spec.put("屏幕尺寸", "5");
skuMap.put("spec", spec);
indexRequest.source(skuMap);
bulkRequest.add(indexRequest); //可以循环加入的
//--------------------
//可以多次添加 
// 3.获取响应结果 
try {

BulkResponse response = restHighLevelClient.bulk(bulkRequest, RequestOptions.DEFAULT);
int status = response.status().getStatus();
System.out.println(status);
String message = response.buildFailureMessage();
System.out.println(message);
restHighLevelClient.close();
} catch (Exception e) {

e.printStackTrace();
}
}
}

2.匹配查询

SearchRequest：查询请求对象

SearchResponse：查询响应对象

SearchSourceBuilder：查询源构建器

MatchQueryBuilder：匹配查询构建器

查询商品名称包含手机的数据

import org.apache.http.HttpHost;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.MatchQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
public class Demo3 {

public static void main(String[] args) throws  Exception{

//1.连接rest接口
HttpHost http = new HttpHost("127.0.0.1", 9200, "http");
RestClientBuilder builder = RestClient.builder(http);
RestHighLevelClient restHighLevelClient = new RestHighLevelClient(builder);
//2.封装查询请求
//对应GET sku 这部分。
SearchRequest searchRequest = new SearchRequest("sku");
searchRequest.types("doc");//如果不写,可以查询所有类型. GET sku/doc/_search
//查询源构造器
/* { "query": { ---->new SearchSourceBuilder(); "match": { ----> "name": "手机" ---->MatchQueryBuilder } } } */
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("name", "手机");
searchSourceBuilder.query(matchQueryBuilder);
//相当于最外面的大括号.
searchRequest.source(searchSourceBuilder);
//3.获取查询结果
//相当于 _search
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
SearchHits searchHits = searchResponse.getHits();
long totalHits = searchHits.getTotalHits();
System.out.println("返回记录数:"+totalHits);
SearchHit[] hits = searchHits.getHits();
for (SearchHit hit : hits) {

String source = hit.getSourceAsString();//json字符串。也可以获取map类型
System.out.println(source);
}
restHighLevelClient.close();
}
}

3.布尔和词条查询

SearchRequest：查询请求对象

SearchResponse：查询响应对象

SearchSourceBuilder：查询源构建器

BoolQueryBuilder：布尔查询构建器

TermQueryBuilder：词条查询构建器

QueryBuilders：查询构建器工厂

查询名称包含手机的，并且品牌为小米的记录

#查询名称包含手机的，并且品牌为小米的。
Get sku/_search
{

"query":{

"bool":{

"must":[
{
"match":{
"name":"手机"}},
{
"term":{
"brandName":"小米"}}
]
}
}
}

import org.apache.http.HttpHost;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.*;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
public class Demo4 {

/* #查询名称包含手机的，并且品牌为小米的。 Get sku/_search { "query":{ ---- new SearchSourceBuilder(); "bool":{ ---> BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); "must":[ {"match":{"name":"手机"}}, ----->MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("name","手机"); {"term":{"brandName":"小米"}} ----> TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("brandName", "小米"); ] } } } */
public static void main(String[] args) throws Exception {

//1.连接rest接口
HttpHost http = new HttpHost("127.0.0.1", 9200, "http");
RestClientBuilder builder = RestClient.builder(http);
RestHighLevelClient restHighLevelClient = new RestHighLevelClient(builder);
//2.封装查询对象
SearchRequest searchRequest = new SearchRequest("sku");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//布尔构建查询器
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("name","手机");
boolQueryBuilder.must(matchQueryBuilder);
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("brandName", "小米");
boolQueryBuilder.must(termQueryBuilder);
//相当于最外面的大括号.
searchRequest.source(searchSourceBuilder);
//3.获取查询结果
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
SearchHits searchHits = searchResponse.getHits();
long totalHits = searchHits.getTotalHits();
System.out.println("返回记录数:"+totalHits);
SearchHit[] hits = searchHits.getHits();
for (SearchHit hit : hits) {

String source = hit.getSourceAsString();//json字符串。也可以获取map类型
System.out.println(source);
}
restHighLevelClient.close();
}
}

4.过滤查询

过滤查询依赖bool，filter是一个链接关键字，相当于must

筛选品牌为小米记录

package com.qingcheng;
import org.apache.http.HttpHost;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.MatchQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.TermQueryBuilder;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
public class Demo5 {

/* #查询名称包含手机的，并且品牌为小米的。 Get sku/_search { "query":{ ---- new SearchSourceBuilder(); "bool":{ ---> BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); "filter":[ {"match":{"name":"手机"}}, ----->MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("name","手机"); ] } } } */
public static void main(String[] args) throws Exception {

//1.连接rest接口
HttpHost http = new HttpHost("127.0.0.1", 9200, "http");
RestClientBuilder builder = RestClient.builder(http);
RestHighLevelClient restHighLevelClient = new RestHighLevelClient(builder);
//2.封装查询对象
SearchRequest searchRequest = new SearchRequest("sku");
searchRequest.types("doc");
//查询源构造器
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//布尔构建查询器
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("brandName", "小米");
boolQueryBuilder.filter(termQueryBuilder);
//相当于最外面的大括号.
searchRequest.source(searchSourceBuilder);
//3.获取查询结果
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
SearchHits searchHits = searchResponse.getHits();
long totalHits = searchHits.getTotalHits();
System.out.println("返回记录数:"+totalHits);
SearchHit[] hits = searchHits.getHits();
for (SearchHit hit : hits) {

String source = hit.getSourceAsString();//json字符串。也可以获取map类型
System.out.println(source);
}
restHighLevelClient.close();
}
}

5.分组查询(聚合查询)

AggregationBuilders：聚合构建器工厂

TermsAggregationBuilder：词条聚合构建器

Aggregations：分组结果封装

Terms.Bucket：桶

package com.qingcheng;
import org.apache.http.HttpHost;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.TermQueryBuilder;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.aggregations.Aggregation;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.aggregations.Aggregations;
import org.elasticsearch.search.aggregations.bucket.terms.Terms;
import org.elasticsearch.search.aggregations.bucket.terms.TermsAggregationBuilder;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import java.util.List;
import java.util.Map;
public class Demo6 {

public static void main(String[] args) throws Exception {

//1.连接rest接口
HttpHost http = new HttpHost("127.0.0.1", 9200, "http");
RestClientBuilder builder = RestClient.builder(http);
RestHighLevelClient restHighLevelClient = new RestHighLevelClient(builder);
//2.封装查询对象
SearchRequest searchRequest = new SearchRequest("sku");
searchRequest.types("doc");
//查询员构造器
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
/* #分组查询 GET sku/_search { ### aggs 表示分组 size:0 "aggs": { "sku_category": { //分组展示的名称 "terms": { "field": "categoryName" } } } } */
//聚合构造器工程
TermsAggregationBuilder sku_category = AggregationBuilders.terms("sku_category");
//词条聚合构建器
TermsAggregationBuilder termsAggregationBuilder = sku_category.field("categoryName");//指定按照什么分组
searchSourceBuilder.aggregation(termsAggregationBuilder);
searchSourceBuilder.size(0);
//相当于最外面的大括号.
searchRequest.source(searchSourceBuilder);
//3.获取查询结果
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
/* SearchHits searchHits = searchResponse.getHits(); long totalHits = searchHits.getTotalHits(); System.out.println("返回记录数:"+totalHits); SearchHit[] hits = searchHits.getHits(); for (SearchHit hit : hits) { String source = hit.getSourceAsString();//json字符串。也可以获取map类型 System.out.println(source); }*/
Aggregations aggregations = searchResponse.getAggregations();
Map<String, Aggregation> aggregationMap = aggregations.getAsMap();
// Aggregation aggregation = aggregationMap.get("sku_category");
//Terms 是Aggregation的子类
Terms terms = (Terms)aggregationMap.get("sku_category");
List<? extends Terms.Bucket> buckets = terms.getBuckets();
for (Terms.Bucket bucket : buckets) {

System.out.println(bucket.getKeyAsString()+"___"+bucket.getDocCount());
}
restHighLevelClient.close();
}
}

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02_ElasticSearch索引操作总结归纳

Index索引操作

文章目录

一、使用kibana工具操作索引

1.索引类型:

2.创建索引和映射对象

3.添加文档

4.查询索引

4.1 查询所有-match_all

4.2 匹配查询-match

4.3 多字段查询-multi_match

4.4 词条匹配-term

4.5 布尔组合查询bool

4.6 过滤查询-bool-filter

4.7 分组查询-aggs

二、使用java操作索引

1.新增修改数据

1.1 新增修改单条数据

1.2 批量插入

2.匹配查询

3.布尔和词条查询

4.过滤查询

5.分组查询(聚合查询)

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02_ElasticSearch索引操作总结归纳

Index索引操作

文章目录

一、使用kibana工具操作索引

1.索引类型:

2.创建索引和映射对象

3.添加文档

4.查询索引

4.1 查询所有-match_all

4.2 匹配查询-match

4.3 多字段查询-multi_match

4.4 词条匹配-term

4.5 布尔组合查询bool

4.6 过滤查询-bool-filter

4.7 分组查询-aggs

二、使用java操作索引

1.新增修改数据

1.1 新增修改单条数据

1.2 批量插入

2.匹配查询

3.布尔和词条查询

4.过滤查询

5.分组查询(聚合查询)

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