ElasticSearch--1
第一章 ElasticSearch 概念
1-1 ElasticSearch 概念
The Elastic Stack, 包括 Elasticsearch、 Kibana、 Beats 和 Logstash（也称为 ELK Stack）。能够安全可靠地获取任何来源、任何格式的数据，然后实时地对数据进行搜索、分析和可视化。
Elaticsearch，简称为 ES， ES 是一个开源的高扩展的分布式全文搜索引擎， 是整个 ElasticStack 技术栈的核心。
它可以近乎实时的存储、检索数据；本身扩展性很好，可以扩展到上百台服务器，处理 PB 级别的数据。
1-2 全文搜索引擎
Google，百度类的网站搜索，它们都是根据网页中的关键字生成索引，我们在搜索的时候输入关键字，它们会将该关键字即索引匹配到的所有网页返回；还有常见的项目中应用日志的搜索等等。对于这些非结构化的数据文本，关系型数据库搜索不是能很好的支持。
这里说到的全文搜索引擎指的是目前广泛应用的主流搜索引擎。它的工作原理是计算机索引程序通过扫描文章中的每一个词，对每一个词建立一个索引，指明该词在文章中出现的次数和位置，当用户查询时，检索程序就根据事先建立的索引进行查找，并将查找的结果反馈给用户的检索方式。这个过程类似于通过字典中的检索字表查字的过程。
1-3 ElasticSearch 应用实例
GitHub、维基百科、百度、新浪、阿里
第二章 ElasticSearch 入门
2-1 官方地址
官方网址
官方文档
Elasticsearch 7.8.0下载
Windows 版的 Elasticsearch 压缩包，解压即安装完毕，解压后的 Elasticsearch 的目录结构如下 ：
目录 |
含义 |
bin |
可执行脚本目录 |
config |
配置目录 |
jdk |
内置 JDK 目录 |
lib |
类库 |
logs |
日志目录 |
modules |
模块目录 |
plugins |
插件目录 |
解压后，进入 bin 文件目录，点击 elasticsearch.bat 文件启动 ES 服务 。
注意： 9300 端口为 Elasticsearch 集群间组件的通信端口， 9200 端口为浏览器访问的 http协议 RESTful 端口。
打开浏览器，输入地址： http://localhost:9200，测试返回结果，返回结果如下：
{
"name" : "琪哥",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "8nGKx-9LTLywpqUKvDDGng",
"version" : {
"number" : "7.8.0",
"build_flavor" : "default",
"build_type" : "zip",
"build_hash" : "757314695644ea9a1dc2fecd26d1a43856725e65",
"build_date" : "2020-06-14T19:35:50.234439Z",
"build_snapshot" : false,
"lucene_version" : "8.5.1",
"minimum_wire_compatibility_version" : "6.8.0",
"minimum_index_compatibility_version" : "6.0.0-beta1"
},
"tagline" : "You Know, for Search"
}2-2 ElasticSearch与MYSQL类比
Elasticsearch 是面向文档型数据库，一条数据在这里就是一个文档。 为了方便大家理解，我们将 Elasticsearch 里存储文档数据和关系型数据库 MySQL 存储数据的概念进行一个类比
ES 里的 Index 可以看做一个库，而 Types 相当于表， Documents 则相当于表的行。这里 Types 的概念已经被逐渐弱化， Elasticsearch 6.X 中，一个 index 下已经只能包含一个type， Elasticsearch 7.X 中, Type 的概念已经被删除了。
2-3 HTTP索引
2-3-1 创建索引
对比关系型数据库，创建索引就等同于创建数据库。
在 Postman 中，向 ES 服务器发 PUT 请求 ： http://127.0.0.1:9200/shopping
请求后，服务器返回响应：
{
"acknowledged": true,//响应结果
"shards_acknowledged": true,//分片结果
"index": "shopping"//索引名称
}如果重复发 PUT 请求 ： http://127.0.0.1:9200/shopping 添加索引，会返回错误信息 :
{
"error": {
"root_cause": [
{
"type": "resource_already_exists_exception",
"reason": "index [shopping/J0WlEhh4R7aDrfIc3AkwWQ] already exists",
"index_uuid": "J0WlEhh4R7aDrfIc3AkwWQ",
"index": "shopping"
}
],
"type": "resource_already_exists_exception",
"reason": "index [shopping/J0WlEhh4R7aDrfIc3AkwWQ] already exists",
"index_uuid": "J0WlEhh4R7aDrfIc3AkwWQ",
"index": "shopping"
},
"status": 400
}2-3-2 查看所有索引
在 Postman 中，向 ES 服务器发 GET 请求 ：http://127.0.0.1:9200/_cat/indices?v 这里 _cat 表示查看的意思， indices 表示索引，与MySQL 中的 show tables 意思一致
服务器响应结果如下 :
health status index uuid pri rep docs.count docs.deleted store.size pri.store.size
yellow open shopping J0WlEhh4R7aDrfIc3AkwWQ 1 1 0 0 208b 208b表头 |
含义 |
health |
当前服务器健康状态： green(集群完整) yellow(单点正常、集群不完整) red(单点不正常) |
status |
索引打开、关闭状态 |
index |
索引名 |
uuid |
索引统一编号 |
pri |
主分片数量 |
rep |
副本数量 |
docs.count |
可用文档数量 |
docs.deleted |
文档删除状态（逻辑删除） |
store.size |
主分片和副分片整体占空间大小 |
pri.store.size |
主分片占空间大小 |
postman示例图：
2-3-3 查看单个索引
在 Postman 中，向 ES 服务器发 GET 请求 ： http://127.0.0.1:9200/shopping
返回结果如下：
{
"shopping": {
"aliases": {},
"mappings": {},
"settings": {
"index": {
"creation_date": "1675322492685",
"number_of_shards": "1",
"number_of_replicas": "1",
"uuid": "kefeAL0TRwet9Oz6DgzBNg",
"version": {
"created": "7080099"
},
"provided_name": "shopping"
}
}
}
}2-3-4 删除索引
在 Postman 中，向 ES 服务器发 DELETE 请求 ： http://127.0.0.1:9200/shopping
再次查看所有索引，GET http://127.0.0.1:9200/_cat/indices?v，返回结果如下：
health status index uuid pri rep docs.count docs.deleted store.size pri.store.size删除成功。
2-4 HTTP文档
2-4-1 创建索引
假设索引已经创建好了，接下来我们来创建文档，并添加数据。这里的文档可以类比为关系型数据库中的表数据，添加的数据格式为 JSON 格式
在 Postman 中，向 ES 服务器发 POST 请求 ： http://127.0.0.1:9200/shopping/_doc
注意未标明唯一标识时候必须为POST请求
返回结果：
{
"_index": "shopping",//索引
"_type": "_doc",//类型-文档
"_id": "ANQqsHgBaKNfVnMbhZYU",//唯一标识，可以类比为 MySQL 中的主键，随机生成
"_version": 1,//版本
"result": "created",//结果，这里的 create 表示创建成功
"_shards": {//
"total": 2,//分片 - 总数
"successful": 1,//分片 - 总数
"failed": 0//分片 - 总数
},
"_seq_no": 0,
"_primary_term": 1
}上面的数据创建后，由于没有指定数据唯一性标识（ID），默认情况下， ES 服务器会随机生成一个。
如果想要自定义唯一性标识，需要在创建时指定： http://127.0.0.1:9200/shopping/_doc/doc_1
请求标明唯一标识后请求方式可为POST可为PUT
2-4-2 查询单个索引
查看文档时，需要指明文档的唯一性标识，类似于 MySQL 中数据的主键查询
在 Postman 中，向 ES 服务器发 GET 请求 ： http://127.0.0.1:9200/shopping/_doc/1 。
查找不存在的内容时，返回结果如下：
2-4-3 查询所有索引
查看索引下所有数据，向 ES 服务器发 GET 请求 ： http://127.0.0.1:9200/shopping/_search。
2-4-4 修改索引
全量修改
和新增文档一样，输入相同的 URL 地址请求，如果请求体变化，会将原有的数据内容覆盖
在 Postman 中，向 ES 服务器发 POST 请求 ： http://127.0.0.1:9200/shopping/_doc/1
修改成功后响应结果：
{
"_index": "shopping",
"_type": "_doc",
"_id": "1",
"_version": 2,
"result": "updated",//<-----------updated 表示数据被更新
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 2,
"_primary_term": 1
}局部修改
修改数据时，也可以只修改某一给条数据的局部信息
在 Postman 中，向 ES 服务器发 POST 请求 ： http://127.0.0.1:9200/shopping/_update/1。
请求体JSON内容为:
{
"doc": {
"title":"小米手机",
"category":"小米"
}
}
2-4-5 删除索引
删除一个文档不会立即从磁盘上移除，它只是被标记成已删除（逻辑删除）。
在 Postman 中，向 ES 服务器发 DELETE 请求 ： http://127.0.0.1:9200/shopping/_doc/1
2-4-6 高级查询
条件查询
查找category为小米的文档
URL带参查询
在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search?q=category:小米，返回结果如下：
{
"took": 45,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 2.4079456,
"hits": [
{
"_index": "shopping",
"_type": "_doc",
"_id": "doc_2",
"_score": 2.4079456,
"_source": {
"title": "小米手机",
"category": "华为",
"images": "http://www.gulixueyuan.com/xm.jpg",
"price": 3999.0
}
}
]
}
}
上述为URL带参数形式查询，这很容易让不善者心怀恶意，或者参数值出现中文会出现乱码情况。为了避免这些情况，我们可用使用带JSON请求体请求进行查询。
请求体带参查询
带请求体方式的查找所有内容
查找所有文档内容，也可以这样，在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"query":{
"match_all":{}
}
}
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 3,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "shopping",
"_type": "_doc",
"_id": "dBrJKYYBYIWGZQXRZ2Lw",
"_score": 1.0,
"_source": {
"title": "小米手机",
"category": "小米",
"images": "http://www.gulixueyuan.com/xm.jpg",
"price": 3999.00
}
},
{
"_index": "shopping",
"_type": "_doc",
"_id": "dRrNKYYBYIWGZQXRNGLG",
"_score": 1.0,
"_source": {
"title": "小米手机",
"category": "小米",
"images": "http://www.gulixueyuan.com/xm.jpg",
"price": 3999.00
}
},
{
"_index": "shopping",
"_type": "_doc",
"_id": "doc_2",
"_score": 1.0,
"_source": {
"title": "小米手机",
"category": "华为",
"images": "http://www.gulixueyuan.com/xm.jpg",
"price": 3999.0
}
}
]
}
}查询指定字段
如果你想查询指定字段，在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"query":{
"match_all":{}
},
"_source":["title"]
}
分页查询
在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"query":{
"match_all":{}
},
"from":1, //起始位置
"size":3 //结束位置
}
查询排序
如果你想通过排序查出价格最高的手机，在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"query":{
"match_all":{}
},
"sort":{
"price":{
"order":"desc"
}
}
}
多条件查询
假设想找出小米牌子，价格为3999元的。（must相当于数据库的&&）
在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"query":{
"bool":{
"must":[{
"match":{
"category":"小米"
}
},
{ "match":{
"price":1999
}
}]
}
}
}
假设想找出小米和华为的牌子,并且价格大于2000的。（should相当于数据库的||）
在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"query":{
"bool":{
"should":[{
"match":{
"category":"小米"
}
},{
"match":{
"category":"华为"
}
}],
"filter":{
"range":{
"price":{
"gt":2000
}
}
}
}
}
}
聚合查询
聚合允许使用者对 es 文档进行统计分析，类似与关系型数据库中的 group by，当然还有很多其他的聚合，例如取最大值max、平均值avg等等。
接下来按price字段进行分组：
在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"aggs":{//聚合操作
"price_group":{//名称，随意起名
"terms":{//分组
"field":"price"//分组字段
}
}
}
}{
"took": 21,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 3,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "shopping",
"_type": "_doc",
"_id": "dBrJKYYBYIWGZQXRZ2Lw",
"_score": 1.0,
"_source": {
"title": "小米手机",
"category": "小米",
"images": "http://www.gulixueyuan.com/xm.jpg",
"price": 1999
}
},
{
"_index": "shopping",
"_type": "_doc",
"_id": "doc_2",
"_score": 1.0,
"_source": {
"title": "小米手机",
"category": "华为",
"images": "http://www.gulixueyuan.com/xm.jpg",
"price": 3999.0
}
},
{
"_index": "shopping",
"_type": "_doc",
"_id": "dRrNKYYBYIWGZQXRNGLG",
"_score": 1.0,
"_source": {
"title": "小米手机",
"category": "小米",
"images": "http://www.gulixueyuan.com/xm.jpg",
"price": 3999.00
}
}
]
},
"aggregations": {
"price_group": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 3999.0,
"doc_count": 2
},
{
"key": 1999.0,
"doc_count": 1
}
]
}
}
}上面返回结果会附带原始数据的。若不想要不附带原始数据的结果，在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"aggs":{
"price_group":{
"terms":{
"field":"price"
}
}
},
"size":0
}{
"took": 60,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 6,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"price_group": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 1999,
"doc_count": 5
},
{
"key": 3999,
"doc_count": 1
}
]
}
}
}
若想对所有手机价格求平均值。
在 Postman 中，向 ES 服务器发 GET请求 ： http://127.0.0.1:9200/shopping/_search，附带JSON体如下：
{
"aggs":{
"price_avg":{//名称，随意起名
"avg":{//求平均
"field":"price"
}
}
},
"size":0
}
{
"took": 14,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 6,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"price_avg": {
"value": 2332.3333333333335
}
}
}
2-4-7 映射关系
有了索引库，等于有了数据库中的 database。
接下来就需要建索引库(index)中的映射了，类似于数据库(database)中的表结构(table)。
创建数据库表需要设置字段名称，类型，长度，约束等；索引库也一样，需要知道这个类型下有哪些字段，每个字段有哪些约束信息，这就叫做映射(mapping)。
# PUT http://127.0.0.1:9200/user返回结果：
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "user"
}创建映射
# PUT http://127.0.0.1:9200/user/_mapping
{
"properties": {
"name":{
"type": "text",
"index": true
},
"sex":{
"type": "keyword",
"index": true
},
"tel":{
"type": "keyword",
"index": false
}
}
}
返回结果如下：
{
"acknowledged": true
}
查询映射
#GET http://127.0.0.1:9200/user/_mapping返回结果如下：
{
"user": {
"mappings": {
"properties": {
"name": {
"type": "text"
},
"sex": {
"type": "keyword"
},
"tel": {
"type": "keyword",
"index": false
}
}
}
}
}
增加数据
#PUT http://127.0.0.1:9200/user/_create/1001
{
"name":"小米",
"sex":"男的",
"tel":"1111"
}
返回结果如下：
{
"_index": "user",
"_type": "_doc",
"_id": "1001",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1
}
查找name含有”小“数据：
#GET http://127.0.0.1:9200/user/_search
{
"query":{
"match":{
"name":"小"
}
}
}
返回结果如下
{
"took": 495,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 0.2876821,
"hits": [
{
"_index": "user",
"_type": "_doc",
"_id": "1001",
"_score": 0.2876821,
"_source": {
"name": "小米",
"sex": "男的",
"tel": "1111"
}
}
]
}
}
查找sex含有”男“数据：
#GET http://127.0.0.1:9200/user/_search
{
"query":{
"match":{
"sex":"男"
}
}
}返回结果如下：
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 0,
"relation": "eq"
},
"max_score": null,
"hits": []
}
}
找不想要的结果，只因创建映射时"sex"的类型为"keyword"。
"sex"只能完全为”男的“，才能得出原数据。
#GET http://127.0.0.1:9200/user/_search
{
"query":{
"match":{
"sex":"男的"
}
}
}
返回结果如下：
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 0.2876821,
"hits": [
{
"_index": "user",
"_type": "_doc",
"_id": "1001",
"_score": 0.2876821,
"_source": {
"name": "小米",
"sex": "男的",
"tel": "1111"
}
}
]
}
}
查询电话
# GET http://127.0.0.1:9200/user/_search
{
"query":{
"match":{
"tel":"11"
}
}
}
返回结果如下：
{
"error": {
"root_cause": [
{
"type": "query_shard_exception",
"reason": "failed to create query: Cannot search on field [tel] since it is not indexed.",
"index_uuid": "ivLnMfQKROS7Skb2MTFOew",
"index": "user"
}
],
"type": "search_phase_execution_exception",
"reason": "all shards failed",
"phase": "query",
"grouped": true,
"failed_shards": [
{
"shard": 0,
"index": "user",
"node": "4P7dIRfXSbezE5JTiuylew",
"reason": {
"type": "query_shard_exception",
"reason": "failed to create query: Cannot search on field [tel] since it is not indexed.",
"index_uuid": "ivLnMfQKROS7Skb2MTFOew",
"index": "user",
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Cannot search on field [tel] since it is not indexed."
}
}
}
]
},
"status": 400
}
报错只因创建映射时"tel"的"index"为false。
2-5 JavaAPI索引
2-5-1 环境准备
添加依赖：
org.elasticsearch
elasticsearch
7.8.0
org.elasticsearch.client
elasticsearch-rest-high-level-client
7.8.0
org.apache.logging.log4j
log4j-api
2.8.2
org.apache.logging.log4j
log4j-core
2.8.2
com.fasterxml.jackson.core
jackson-databind
2.9.9
junit
junit
4.12
HelloElasticsearch
import java.io.IOException;
import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
public class HelloElasticsearch {
public static void main(String[] args) throws IOException {
// 创建客户端对象
RestHighLevelClient client = new RestHighLevelClient(
RestClient.builder(new HttpHost("localhost", 9200, "http")));
// ...
System.out.println(client);
// 关闭客户端连接
client.close();
}
}2-5-2 创建索引
import org.apache.http.HttpHost;
import org.elasticsearch.action.admin.indices.create.CreateIndexRequest;
import org.elasticsearch.action.admin.indices.create.CreateIndexResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import java.io.IOException;
public class CreateIndex {
public static void main(String[] args) throws IOException {
// 创建客户端对象
RestHighLevelClient client = new RestHighLevelClient(
RestClient.builder(new HttpHost("localhost", 9200, "http")));
// 创建索引 - 请求对象
CreateIndexRequest request = new CreateIndexRequest("user2");
// 发送请求，获取响应
CreateIndexResponse response = client.indices().create(request,
RequestOptions.DEFAULT);
boolean acknowledged = response.isAcknowledged();
// 响应状态
System.out.println("操作状态 = " + acknowledged);
// 关闭客户端连接
client.close();
}
}
后台打印：
四月 09, 2021 2:12:08 下午 org.elasticsearch.client.RestClient logResponse
警告: request [PUT http://localhost:9200/user2?master_timeout=30s&include_type_name=true&timeout=30s] returned 1 warnings: [299 Elasticsearch-7.8.0-757314695644ea9a1dc2fecd26d1a43856725e65 "[types removal] Using include_type_name in create index requests is deprecated. The parameter will be removed in the next major version."]
操作状态 = true
Process finished with exit code 02-5-2 查询索引
import org.apache.http.HttpHost;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.client.indices.GetIndexRequest;
import org.elasticsearch.client.indices.GetIndexResponse;
import java.io.IOException;
public class SearchIndex {
public static void main(String[] args) throws IOException {
// 创建客户端对象
RestHighLevelClient client = new RestHighLevelClient(
RestClient.builder(new HttpHost("localhost", 9200, "http")));
// 查询索引 - 请求对象
GetIndexRequest request = new GetIndexRequest("user2");
// 发送请求，获取响应
GetIndexResponse response = client.indices().get(request,
RequestOptions.DEFAULT);
System.out.println("aliases:"+response.getAliases());
System.out.println("mappings:"+response.getMappings());
System.out.println("settings:"+response.getSettings());
client.close();
}
}
后台打印：
aliases:{user2=[]}
mappings:{user2=org.elasticsearch.cluster.metadata.MappingMetadata@ad700514}
settings:{user2={"index.creation_date":"1617948726976","index.number_of_replicas":"1","index.number_of_shards":"1","index.provided_name":"user2","index.uuid":"UGZ1ntcySnK6hWyP2qoVpQ","index.version.created":"7080099"}}
Process finished with exit code 02-5-3 删除索引
import org.apache.http.HttpHost;
import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest;
import org.elasticsearch.action.support.master.AcknowledgedResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import java.io.IOException;
public class DeleteIndex {
public static void main(String[] args) throws IOException {
RestHighLevelClient client = new RestHighLevelClient(
RestClient.builder(new HttpHost("localhost", 9200, "http")));
// 删除索引 - 请求对象
DeleteIndexRequest request = new DeleteIndexRequest("user2");
// 发送请求，获取响应
AcknowledgedResponse response = client.indices().delete(request,RequestOptions.DEFAULT);
// 操作结果
System.out.println("操作结果 ： " + response.isAcknowledged());
client.close();
}
}
后台打印：
操作结果 ： true
Process finished with exit code 02-6 JavaAPI 文档
上文由于频繁使用以下连接Elasticsearch和关闭它的代码，于是个人对它进行重构。
重构后的代码：
import org.elasticsearch.client.RestHighLevelClient;
public interface ElasticsearchTask {
void doSomething(RestHighLevelClient client) throws Exception;
}public class ConnectElasticsearch{
public static void connect(ElasticsearchTask task){
// 创建客户端对象
RestHighLevelClient client = new RestHighLevelClient(
RestClient.builder(new HttpHost("localhost", 9200, "http")));
try {
task.doSomething(client);
// 关闭客户端连接
client.close();
} catch (Exception e) {
e.printStackTrace();
}
}
}接下来，如果想让Elasticsearch完成一些操作，就编写一个lambda式即可。
public class SomeClass {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
//do something
});
}
}2-6-1 创建索引
import com.fasterxml.jackson.databind.ObjectMapper;
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.model.User;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.common.xcontent.XContentType;
public class InsertDoc {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
// 新增文档 - 请求对象
IndexRequest request = new IndexRequest();
// 设置索引及唯一性标识
request.index("user").id("1001");
// 创建数据对象
User user = new User();
user.setName("zhangsan");
user.setAge(30);
user.setSex("男");
ObjectMapper objectMapper = new ObjectMapper();
String productJson = objectMapper.writeValueAsString(user);
// 添加文档数据，数据格式为 JSON 格式
request.source(productJson, XContentType.JSON);
// 客户端发送请求，获取响应对象
IndexResponse response = client.index(request, RequestOptions.DEFAULT);
3.打印结果信息
System.out.println("_index:" + response.getIndex());
System.out.println("_id:" + response.getId());
System.out.println("_result:" + response.getResult());
});
}
}
后台打印：
_index:user
_id:1001
_result:UPDATED2-6-2 修改索引
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import org.elasticsearch.action.update.UpdateRequest;
import org.elasticsearch.action.update.UpdateResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.common.xcontent.XContentType;
public class UpdateDoc {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
// 修改文档 - 请求对象
UpdateRequest request = new UpdateRequest();
// 配置修改参数
request.index("user").id("1001");
// 设置请求体，对数据进行修改
request.doc(XContentType.JSON, "sex", "女");
// 客户端发送请求，获取响应对象
UpdateResponse response = client.update(request, RequestOptions.DEFAULT);
System.out.println("_index:" + response.getIndex());
System.out.println("_id:" + response.getId());
System.out.println("_result:" + response.getResult());
});
}
}
后台打印：
_index:user
_id:1001
_result:UPDATED2-6-3 查询索引
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import org.elasticsearch.action.get.GetRequest;
import org.elasticsearch.action.get.GetResponse;
import org.elasticsearch.client.RequestOptions;
public class GetDoc {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
//1.创建请求对象
GetRequest request = new GetRequest().index("user").id("1001");
//2.客户端发送请求，获取响应对象
GetResponse response = client.get(request, RequestOptions.DEFAULT);
3.打印结果信息
System.out.println("_index:" + response.getIndex());
System.out.println("_type:" + response.getType());
System.out.println("_id:" + response.getId());
System.out.println("source:" + response.getSourceAsString());
});
}
}
后台打印：
_index:user
_type:_doc
_id:1001
source:{"name":"zhangsan","age":30,"sex":"男"}2-6-4 删除索引
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import org.elasticsearch.action.delete.DeleteRequest;
import org.elasticsearch.action.delete.DeleteResponse;
import org.elasticsearch.client.RequestOptions;
public class DeleteDoc {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
//创建请求对象
DeleteRequest request = new DeleteRequest().index("user").id("1001");
//客户端发送请求，获取响应对象
DeleteResponse response = client.delete(request, RequestOptions.DEFAULT);
//打印信息
System.out.println(response.toString());
});
}
}
后台打印：
DeleteResponse[index=user,type=_doc,id=1001,version=16,result=deleted,shards=ShardInfo{total=2, successful=1, failures=[]}]2-6-5 批量新增
import com.lun.elasticsearch.hello.ConnectElasticsearch;
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.common.xcontent.XContentType;
public class BatchInsertDoc {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
//创建批量新增请求对象
BulkRequest request = new BulkRequest();
request.add(new
IndexRequest().index("user").id("1001").source(XContentType.JSON, "name",
"zhangsan"));
request.add(new
IndexRequest().index("user").id("1002").source(XContentType.JSON, "name",
"lisi"));
request.add(new
IndexRequest().index("user").id("1003").source(XContentType.JSON, "name",
"wangwu"));
//客户端发送请求，获取响应对象
BulkResponse responses = client.bulk(request, RequestOptions.DEFAULT);
//打印结果信息
System.out.println("took:" + responses.getTook());
System.out.println("items:" + responses.getItems());
});
}
}
后台打印：
took:294ms
items:[Lorg.elasticsearch.action.bulk.BulkItemResponse;@2beee7ff2-6-6 批量删除
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import org.elasticsearch.action.bulk.BulkRequest;
import org.elasticsearch.action.bulk.BulkResponse;
import org.elasticsearch.action.delete.DeleteRequest;
import org.elasticsearch.client.RequestOptions;
public class BatchDeleteDoc {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
//创建批量删除请求对象
BulkRequest request = new BulkRequest();
request.add(new DeleteRequest().index("user").id("1001"));
request.add(new DeleteRequest().index("user").id("1002"));
request.add(new DeleteRequest().index("user").id("1003"));
//客户端发送请求，获取响应对象
BulkResponse responses = client.bulk(request, RequestOptions.DEFAULT);
//打印结果信息
System.out.println("took:" + responses.getTook());
System.out.println("items:" + responses.getItems());
});
}
}
后台打印：
took:108ms
items:[Lorg.elasticsearch.action.bulk.BulkItemResponse;@7b02881e2-6-7 高级查询
public class BatchInsertDoc {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
//创建批量新增请求对象
BulkRequest request = new BulkRequest();
request.add(new IndexRequest().index("user").id("1001").source(XContentType.JSON, "name", "zhangsan", "age", "10", "sex","女"));
request.add(new IndexRequest().index("user").id("1002").source(XContentType.JSON, "name", "lisi", "age", "30", "sex","女"));
request.add(new IndexRequest().index("user").id("1003").source(XContentType.JSON, "name", "wangwu1", "age", "40", "sex","男"));
request.add(new IndexRequest().index("user").id("1004").source(XContentType.JSON, "name", "wangwu2", "age", "20", "sex","女"));
request.add(new IndexRequest().index("user").id("1005").source(XContentType.JSON, "name", "wangwu3", "age", "50", "sex","男"));
request.add(new IndexRequest().index("user").id("1006").source(XContentType.JSON, "name", "wangwu4", "age", "20", "sex","男"));
//客户端发送请求，获取响应对象
BulkResponse responses = client.bulk(request, RequestOptions.DEFAULT);
//打印结果信息
System.out.println("took:" + responses.getTook());
System.out.println("items:" + responses.getItems());
});
}
}
后台打印：
took:168ms
items:[Lorg.elasticsearch.action.bulk.BulkItemResponse;@2beee7ff查询所有索引数据
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
public class QueryDoc {
public static void main(String[] args) {
ConnectElasticsearch.connect(client -> {
// 创建搜索请求对象
SearchRequest request = new SearchRequest();
request.indices("user");
// 构建查询的请求体
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
// 查询所有数据
sourceBuilder.query(QueryBuilders.matchAllQuery());
request.source(sourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 查询匹配
SearchHits hits = response.getHits();
System.out.println("took:" + response.getTook());
System.out.println("timeout:" + response.isTimedOut());
System.out.println("total:" + hits.getTotalHits());
System.out.println("MaxScore:" + hits.getMaxScore());
System.out.println("hits========>>");
for (SearchHit hit : hits) {
//输出每条查询的结果信息
System.out.println(hit.getSourceAsString());
}
System.out.println("<<========");
});
}
}
后台打印：
took:2ms
timeout:false
total:6 hits
MaxScore:1.0
hits========>>
{"name":"zhangsan","age":"10","sex":"女"}
{"name":"lisi","age":"30","sex":"女"}
{"name":"wangwu1","age":"40","sex":"男"}
{"name":"wangwu2","age":"20","sex":"女"}
{"name":"wangwu3","age":"50","sex":"男"}
{"name":"wangwu4","age":"20","sex":"男"}
<<========
Process finished with exit code 0条件查询
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.hello.ElasticsearchTask;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.sort.SortOrder;
public class QueryDoc {
public static final ElasticsearchTask SEARCH_BY_CONDITION = client -> {
// 创建搜索请求对象
SearchRequest request = new SearchRequest();
request.indices("user");
// 构建查询的请求体
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.query(QueryBuilders.termQuery("age", "30"));
request.source(sourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 查询匹配
SearchHits hits = response.getHits();
System.out.println("took:" + response.getTook());
System.out.println("timeout:" + response.isTimedOut());
System.out.println("total:" + hits.getTotalHits());
System.out.println("MaxScore:" + hits.getMaxScore());
System.out.println("hits========>>");
for (SearchHit hit : hits) {
//输出每条查询的结果信息
System.out.println(hit.getSourceAsString());
}
System.out.println("<<========");
};
public static void main(String[] args) {
ConnectElasticsearch.connect(SEARCH_BY_CONDITION);
}
}
后台打印：
took:1ms
timeout:false
total:1 hits
MaxScore:1.0
hits========>>
{"name":"lisi","age":"30","sex":"女"}
<<========分页查询
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.hello.ElasticsearchTask;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.sort.SortOrder;
public class QueryDoc {
public static final ElasticsearchTask SEARCH_BY_PAGING = client -> {
// 创建搜索请求对象
SearchRequest request = new SearchRequest();
request.indices("user");
// 构建查询的请求体
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.query(QueryBuilders.matchAllQuery());
// 分页查询
// 当前页其实索引(第一条数据的顺序号)， from
sourceBuilder.from(0);
// 每页显示多少条 size
sourceBuilder.size(2);
request.source(sourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 查询匹配
SearchHits hits = response.getHits();
System.out.println("took:" + response.getTook());
System.out.println("timeout:" + response.isTimedOut());
System.out.println("total:" + hits.getTotalHits());
System.out.println("MaxScore:" + hits.getMaxScore());
System.out.println("hits========>>");
for (SearchHit hit : hits) {
//输出每条查询的结果信息
System.out.println(hit.getSourceAsString());
}
System.out.println("<<========");
};
public static void main(String[] args) {
ConnectElasticsearch.connect(SEARCH_BY_CONDITION);
}
}
后台打印:
took:1ms
timeout:false
total:6 hits
MaxScore:1.0
hits========>>
{"name":"zhangsan","age":"10","sex":"女"}
{"name":"lisi","age":"30","sex":"女"}
<<========
查询排序
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.hello.ElasticsearchTask;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.sort.SortOrder;
public class QueryDoc {
public static final ElasticsearchTask SEARCH_WITH_ORDER = client -> {
// 创建搜索请求对象
SearchRequest request = new SearchRequest();
request.indices("user");
// 构建查询的请求体
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.query(QueryBuilders.matchAllQuery());
// 排序
sourceBuilder.sort("age", SortOrder.ASC);
request.source(sourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 查询匹配
SearchHits hits = response.getHits();
System.out.println("took:" + response.getTook());
System.out.println("timeout:" + response.isTimedOut());
System.out.println("total:" + hits.getTotalHits());
System.out.println("MaxScore:" + hits.getMaxScore());
System.out.println("hits========>>");
for (SearchHit hit : hits) {
//输出每条查询的结果信息
System.out.println(hit.getSourceAsString());
}
System.out.println("<<========");
};
public static void main(String[] args) {
ConnectElasticsearch.connect(SEARCH_WITH_ORDER);
}
}
后台打印：
took:1ms
timeout:false
total:6 hits
MaxScore:NaN
hits========>>
{"name":"zhangsan","age":"10","sex":"女"}
{"name":"wangwu2","age":"20","sex":"女"}
{"name":"wangwu4","age":"20","sex":"男"}
{"name":"lisi","age":"30","sex":"女"}
{"name":"wangwu1","age":"40","sex":"男"}
{"name":"wangwu3","age":"50","sex":"男"}
<<========
组合查询
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.hello.ElasticsearchTask;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.sort.SortOrder;
public class QueryDoc {
public static final ElasticsearchTask SEARCH_BY_BOOL_CONDITION = client -> {
// 创建搜索请求对象
SearchRequest request = new SearchRequest();
request.indices("user");
// 构建查询的请求体
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
// 必须包含
boolQueryBuilder.must(QueryBuilders.matchQuery("age", "30"));
// 一定不含
boolQueryBuilder.mustNot(QueryBuilders.matchQuery("name", "zhangsan"));
// 可能包含
boolQueryBuilder.should(QueryBuilders.matchQuery("sex", "男"));
sourceBuilder.query(boolQueryBuilder);
request.source(sourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 查询匹配
SearchHits hits = response.getHits();
System.out.println("took:" + response.getTook());
System.out.println("timeout:" + response.isTimedOut());
System.out.println("total:" + hits.getTotalHits());
System.out.println("MaxScore:" + hits.getMaxScore());
System.out.println("hits========>>");
for (SearchHit hit : hits) {
//输出每条查询的结果信息
System.out.println(hit.getSourceAsString());
}
System.out.println("<<========");
};
public static void main(String[] args) {
ConnectElasticsearch.connect(SEARCH_BY_BOOL_CONDITION);
}
}
后台打印：
took:28ms
timeout:false
total:1 hits
MaxScore:1.0
hits========>>
{"name":"lisi","age":"30","sex":"女"}
<<========
Process finished with exit code 0范围查询
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.hello.ElasticsearchTask;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.RangeQueryBuilder;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.sort.SortOrder;
public class QueryDoc {
public static final ElasticsearchTask SEARCH_BY_RANGE = client -> {
// 创建搜索请求对象
SearchRequest request = new SearchRequest();
request.indices("user");
// 构建查询的请求体
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
RangeQueryBuilder rangeQuery = QueryBuilders.rangeQuery("age");
// 大于等于
//rangeQuery.gte("30");
// 小于等于
rangeQuery.lte("40");
sourceBuilder.query(rangeQuery);
request.source(sourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 查询匹配
SearchHits hits = response.getHits();
System.out.println("took:" + response.getTook());
System.out.println("timeout:" + response.isTimedOut());
System.out.println("total:" + hits.getTotalHits());
System.out.println("MaxScore:" + hits.getMaxScore());
System.out.println("hits========>>");
for (SearchHit hit : hits) {
//输出每条查询的结果信息
System.out.println(hit.getSourceAsString());
}
System.out.println("<<========");
};
public static void main(String[] args) {
ConnectElasticsearch.connect(SEARCH_BY_RANGE);
}
}
后台打印：
took:1ms
timeout:false
total:5 hits
MaxScore:1.0
hits========>>
{"name":"zhangsan","age":"10","sex":"女"}
{"name":"lisi","age":"30","sex":"女"}
{"name":"wangwu1","age":"40","sex":"男"}
{"name":"wangwu2","age":"20","sex":"女"}
{"name":"wangwu4","age":"20","sex":"男"}
<<========
Process finished with exit code 0
模糊查询
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.hello.ElasticsearchTask;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.common.unit.Fuzziness;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.RangeQueryBuilder;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.sort.SortOrder;
public class QueryDoc {
public static final ElasticsearchTask SEARCH_BY_FUZZY_CONDITION = client -> {
// 创建搜索请求对象
SearchRequest request = new SearchRequest();
request.indices("user");
// 构建查询的请求体
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.query(QueryBuilders.fuzzyQuery("name","wangwu").fuzziness(Fuzziness.ONE));
request.source(sourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 查询匹配
SearchHits hits = response.getHits();
System.out.println("took:" + response.getTook());
System.out.println("timeout:" + response.isTimedOut());
System.out.println("total:" + hits.getTotalHits());
System.out.println("MaxScore:" + hits.getMaxScore());
System.out.println("hits========>>");
for (SearchHit hit : hits) {
//输出每条查询的结果信息
System.out.println(hit.getSourceAsString());
}
System.out.println("<<========");
};
public static void main(String[] args) {
// ConnectElasticsearch.connect(SEARCH_ALL);
// ConnectElasticsearch.connect(SEARCH_BY_CONDITION);
// ConnectElasticsearch.connect(SEARCH_BY_PAGING);
// ConnectElasticsearch.connect(SEARCH_WITH_ORDER);
// ConnectElasticsearch.connect(SEARCH_BY_BOOL_CONDITION);
// ConnectElasticsearch.connect(SEARCH_BY_RANGE);
ConnectElasticsearch.connect(SEARCH_BY_FUZZY_CONDITION);
}
}
后台打印
took:152ms
timeout:false
total:4 hits
MaxScore:1.2837042
hits========>>
{"name":"wangwu1","age":"40","sex":"男"}
{"name":"wangwu2","age":"20","sex":"女"}
{"name":"wangwu3","age":"50","sex":"男"}
{"name":"wangwu4","age":"20","sex":"男"}
<<========
Process finished with exit code 0最大值查询
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.hello.ElasticsearchTask;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.common.unit.Fuzziness;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.RangeQueryBuilder;
import org.elasticsearch.index.query.TermsQueryBuilder;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightField;
import org.elasticsearch.search.sort.SortOrder;
import java.util.Map;
public class QueryDoc {
public static final ElasticsearchTask SEARCH_WITH_MAX = client -> {
// 高亮查询
SearchRequest request = new SearchRequest().indices("user");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.aggregation(AggregationBuilders.max("maxAge").field("age"));
//设置请求体
request.source(sourceBuilder);
//3.客户端发送请求，获取响应对象
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
//4.打印响应结果
SearchHits hits = response.getHits();
System.out.println(response);
};
public static void main(String[] args) {
ConnectElasticsearch.connect(SEARCH_WITH_MAX);
}
}
后台打印
{"took":16,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":6,"relation":"eq"},"max_score":1.0,"hits":[{"_index":"user","_type":"_doc","_id":"1001","_score":1.0,"_source":{"name":"zhangsan","age":"10","sex":"女"}},{"_index":"user","_type":"_doc","_id":"1002","_score":1.0,"_source":{"name":"lisi","age":"30","sex":"女"}},{"_index":"user","_type":"_doc","_id":"1003","_score":1.0,"_source":{"name":"wangwu1","age":"40","sex":"男"}},{"_index":"user","_type":"_doc","_id":"1004","_score":1.0,"_source":{"name":"wangwu2","age":"20","sex":"女"}},{"_index":"user","_type":"_doc","_id":"1005","_score":1.0,"_source":{"name":"wangwu3","age":"50","sex":"男"}},{"_index":"user","_type":"_doc","_id":"1006","_score":1.0,"_source":{"name":"wangwu4","age":"20","sex":"男"}}]},"aggregations":{"max#maxAge":{"value":50.0}}}
Process finished with exit code 0分组查询
import com.lun.elasticsearch.hello.ConnectElasticsearch;
import com.lun.elasticsearch.hello.ElasticsearchTask;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.common.unit.Fuzziness;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.RangeQueryBuilder;
import org.elasticsearch.index.query.TermsQueryBuilder;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightField;
import org.elasticsearch.search.sort.SortOrder;
import java.util.Map;
public class QueryDoc {
public static final ElasticsearchTask SEARCH_WITH_GROUP = client -> {
SearchRequest request = new SearchRequest().indices("user");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.aggregation(AggregationBuilders.terms("age_groupby").field("age"));
//设置请求体
request.source(sourceBuilder);
//3.客户端发送请求，获取响应对象
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
//4.打印响应结果
SearchHits hits = response.getHits();
System.out.println(response);
};
public static void main(String[] args) {
ConnectElasticsearch.connect(SEARCH_WITH_GROUP);
}
}
后台打印
{"took":10,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":6,"relation":"eq"},"max_score":1.0,"hits":[{"_index":"user","_type":"_doc","_id":"1001","_score":1.0,"_source":{"name":"zhangsan","age":"10","sex":"女"}},{"_index":"user","_type":"_doc","_id":"1002","_score":1.0,"_source":{"name":"lisi","age":"30","sex":"女"}},{"_index":"user","_type":"_doc","_id":"1003","_score":1.0,"_source":{"name":"wangwu1","age":"40","sex":"男"}},{"_index":"user","_type":"_doc","_id":"1004","_score":1.0,"_source":{"name":"wangwu2","age":"20","sex":"女"}},{"_index":"user","_type":"_doc","_id":"1005","_score":1.0,"_source":{"name":"wangwu3","age":"50","sex":"男"}},{"_index":"user","_type":"_doc","_id":"1006","_score":1.0,"_source":{"name":"wangwu4","age":"20","sex":"男"}}]},"aggregations":{"lterms#age_groupby":{"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buckets":[{"key":20,"doc_count":2},{"key":10,"doc_count":1},{"key":30,"doc_count":1},{"key":40,"doc_count":1},{"key":50,"doc_count":1}]}}}
Process finished with exit code 0