第一章 ElasticSearch入门

编程知识更新时间:2023-05-03 04:03:32

ElasticSearch 是什么

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。

Elasticsearch 应用案例

GitHub: 2013 年初，抛弃了 Solr，采取 Elasticsearch 来做 PB 级的搜索。 “GitHub 使用Elasticsearch 搜索 20TB 的数据，包括 13 亿文件和 1300 亿行代码”。
维基百科：启动以 Elasticsearch 为基础的核心搜索架构
百度：目前广泛使用 Elasticsearch 作为文本数据分析，采集百度所有服务器上的各类指标数据及用户自定义数据，通过对各种数据进行多维分析展示，辅助定位分析实例异常或业务层面异常。目前覆盖百度内部 20 多个业务线（包括云分析、网盟、预测、文库、直达号、钱包、风控等），单集群最大 100 台机器， 200 个 ES 节点，每天导入 30TB+数据。
新浪：使用 Elasticsearch 分析处理 32 亿条实时日志。
阿里：使用 Elasticsearch 构建日志采集和分析体系。
Stack Overflow：解决 Bug 问题的网站，全英文，编程人员交流的网站。

环境准备

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：
解压后，进入 bin 文件目录，点击 elasticsearch.bat 文件启动 ES 服务。
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：

倒排索引

正排索引（传统）
倒排索引
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

HTTP

索引-创建

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
}

索引-查询

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
这里请求路径中的_cat 表示查看的意思， indices 表示索引，所以整体含义就是查看当前 ES服务器中的所有索引，就好像 MySQL 中的 show tables 的感觉，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

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

{
    "shopping": {//索引名
        "aliases": {},//别名
        "mappings": {},//映射
        "settings": {//设置
            "index": {//设置 - 索引
                "creation_date": "1617861426847",//设置 - 索引 - 创建时间
                "number_of_shards": "1",//设置 - 索引 - 主分片数量
                "number_of_replicas": "1",//设置 - 索引 - 主分片数量
                "uuid": "J0WlEhh4R7aDrfIc3AkwWQ",//设置 - 索引 - 主分片数量
                "version": {//设置 - 索引 - 主分片数量
                    "created": "7080099"
                },
                "provided_name": "shopping"//设置 - 索引 - 主分片数量
            }
        }
    }
}

索引-删除

在 Postman 中，向 ES 服务器发 DELETE 请求： http://127.0.0.1:9200/shopping

{
    "acknowledged": true
}

文档-创建

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，请求体JSON内容为：

{
    "title":"小米手机",
    "category":"小米",
    "images":"http://www.gulixueyuan/xm.jpg",
    "price":3999.00
}

注意，此处发送请求的方式必须为 POST，不能是 PUT，否则会发生错误。
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/1，请求体JSON内容为：

{
    "title":"小米手机",
    "category":"小米",
    "images":"http://www.gulixueyuan/xm.jpg",
    "price":3999.00
}

返回结果如下：

{
    "_index": "shopping",
    "_type": "_doc",
    "_id": "1",//<------------------自定义唯一性标识
    "_version": 1,
    "result": "created",
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    },
    "_seq_no": 1,
    "_primary_term": 1
}

此处需要注意：如果增加数据时明确数据主键，那么请求方式也可以为 PUT。

文档-查询

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 。

{
    "_index": "shopping",
    "_type": "_doc",
    "_id": "1",
    "_version": 1,
    "_seq_no": 1,
    "_primary_term": 1,
    "found": true,
    "_source": {
        "title": "小米手机",
        "category": "小米",
        "images": "http://www.gulixueyuan/xm.jpg",
        "price": 3999
    }
}

查找不存在的内容，向 ES 服务器发 GET 请求： http://127.0.0.1:9200/shopping/_doc/1001。

{
    "_index": "shopping",
    "_type": "_doc",
    "_id": "1001",
    "found": false
}

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。

{
    "took": 133,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 2,
            "relation": "eq"
        },
        "max_score": 1,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "1",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            }
        ]
    }
}

文档-修改

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
请求体JSON内容为:

{
    "title":"华为手机",
    "category":"华为",
    "images":"http://www.gulixueyuan/hw.jpg",
    "price":1999.00
}

修改成功后，服务器响应结果：

{
    "_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"
	}
}

返回结果如下：

{
    "_index": "shopping",
    "_type": "_doc",
    "_id": "1",
    "_version": 3,
    "result": "updated",//<-----------updated 表示数据被更新
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    },
    "_seq_no": 3,
    "_primary_term": 1
}

在 Postman 中，向 ES 服务器发 GET请求： http://127.0.0.1:9200/shopping/_doc/1，查看修改内容：

{
    "_index": "shopping",
    "_type": "_doc",
    "_id": "1",
    "_version": 3,
    "_seq_no": 3,
    "_primary_term": 1,
    "found": true,
    "_source": {
        "title": "小米手机",
        "category": "小米",
        "images": "http://www.gulixueyuan/hw.jpg",
        "price": 1999
    }
}

文档-删除

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

{
    "_index": "shopping",
    "_type": "_doc",
    "_id": "1",
    "_version": 4,
    "result": "deleted",//<---删除成功
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    },
    "_seq_no": 4,
    "_primary_term": 1
}

在 Postman 中，向 ES 服务器发 GET请求： http://127.0.0.1:9200/shopping/_doc/1，查看是否删除成功：

{
    "_index": "shopping",
    "_type": "_doc",
    "_id": "1",
    "found": false
}

条件查询

假设有以下文档内容，（在 Postman 中，向 ES 服务器发 GET请求： http://127.0.0.1:9200/shopping/_search）：

{
    "took": 5,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 6,
            "relation": "eq"
        },
        "max_score": 1,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "A9R5sHgBaKNfVnMb25Ya",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BNR5sHgBaKNfVnMb7pal",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BtR6sHgBaKNfVnMbX5Y5",
                "_score": 1,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "B9R6sHgBaKNfVnMbZpZ6",
                "_score": 1,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "CdR7sHgBaKNfVnMbsJb9",
                "_score": 1,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            }
        ]
    }
}

URL带参查询

查找category为小米的文档，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": 94,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 3,
            "relation": "eq"
        },
        "max_score": 1.3862942,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "A9R5sHgBaKNfVnMb25Ya",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BNR5sHgBaKNfVnMb7pal",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            }
        ]
    }
}

请求体带参查询

接下带JSON请求体，还是查找category为小米的文档，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":{
			"category":"小米"
		}
	}
}

返回结果如下：

{
    "took": 3,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 3,
            "relation": "eq"
        },
        "max_score": 1.3862942,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "A9R5sHgBaKNfVnMb25Ya",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BNR5sHgBaKNfVnMb7pal",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            }
        ]
    }
}

带请求体方式的查找所有内容

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":{}
	}
}

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":0,
	"size":2
}

返回结果如下：

{
    "took": 1,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 6,
            "relation": "eq"
        },
        "max_score": 1,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "A9R5sHgBaKNfVnMb25Ya",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            }
        ]
    }
}

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"
		}
	}
}

返回结果如下：

{
    "took": 96,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 6,
            "relation": "eq"
        },
        "max_score": null,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": null,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                },
                "sort": [
                    3999
                ]
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "A9R5sHgBaKNfVnMb25Ya",
                "_score": null,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                },
                "sort": [
                    1999
                ]
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BNR5sHgBaKNfVnMb7pal",
                "_score": null,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                },
                "sort": [
                    1999
                ]
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BtR6sHgBaKNfVnMbX5Y5",
                "_score": null,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                },
                "sort": [
                    1999
                ]
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "B9R6sHgBaKNfVnMbZpZ6",
                "_score": null,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                },
                "sort": [
                    1999
                ]
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "CdR7sHgBaKNfVnMbsJb9",
                "_score": null,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                },
                "sort": [
                    1999
                ]
            }
        ]
    }
}

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":3999.00
				}
			}]
		}
	}
}

返回结果如下：

{
    "took": 134,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 1,
            "relation": "eq"
        },
        "max_score": 2.3862944,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 2.3862944,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            }
        ]
    }
}

假设想找出小米和华为的牌子。（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"
				}
			}]
		}
	}
}

返回结果如下：

{
    "took": 8,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 6,
            "relation": "eq"
        },
        "max_score": 1.3862942,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "A9R5sHgBaKNfVnMb25Ya",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BNR5sHgBaKNfVnMb7pal",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BtR6sHgBaKNfVnMbX5Y5",
                "_score": 1.3862942,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "B9R6sHgBaKNfVnMbZpZ6",
                "_score": 1.3862942,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "CdR7sHgBaKNfVnMbsJb9",
                "_score": 1.3862942,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            }
        ]
    }
}

范围查询

假设想找出小米和华为的牌子，价格大于2000元的手机。
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":{
		"bool":{
			"should":[{
				"match":{
					"category":"小米"
				}
			},{
				"match":{
					"category":"华为"
				}
			}],
            "filter":{
            	"range":{
                	"price":{
                    	"gt":2000
                	}
	            }
    	    }
		}
	}
}

返回结果如下：

{
    "took": 72,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 1,
            "relation": "eq"
        },
        "max_score": 1.3862942,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 1.3862942,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            }
        ]
    }
}

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。
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
			}
		}
	}
}

返回结果如下：

{
    "took": 63,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 6,
            "relation": "eq"
        },
        "max_score": 1,
        "hits": [
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "ANQqsHgBaKNfVnMbhZYU",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 3999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "A9R5sHgBaKNfVnMb25Ya",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BNR5sHgBaKNfVnMb7pal",
                "_score": 1,
                "_source": {
                    "title": "小米手机",
                    "category": "小米",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "BtR6sHgBaKNfVnMbX5Y5",
                "_score": 1,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "B9R6sHgBaKNfVnMbZpZ6",
                "_score": 1,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            },
            {
                "_index": "shopping",
                "_type": "_doc",
                "_id": "CdR7sHgBaKNfVnMbsJb9",
                "_score": 1,
                "_source": {
                    "title": "华为手机",
                    "category": "华为",
                    "images": "http://www.gulixueyuan/xm.jpg",
                    "price": 1999
                }
            }
        ]
    },
    "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
                }
            ]
        }
    }
}

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
}

返回结果如下：

{
    "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
}

返回结果如下：

{
    "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
        }
    }
}

JavaAPI

环境准备

添加依赖：

<dependencies>
    <dependency>
        <groupId>org.elasticsearch</groupId>
        <artifactId>elasticsearch</artifactId>
        <version>7.8.0</version>
    </dependency>
    <!-- elasticsearch 的客户端 -->
    <dependency>
        <groupId>org.elasticsearch.client</groupId>
        <artifactId>elasticsearch-rest-high-level-client</artifactId>
        <version>7.8.0</version>
    </dependency>
    <!-- elasticsearch 依赖 2.x 的 log4j -->
    <dependency>
        <groupId>org.apache.logging.log4j</groupId>
        <artifactId>log4j-api</artifactId>
        <version>2.8.2</version>
    </dependency>
    <dependency>
        <groupId>org.apache.logging.log4j</groupId>
        <artifactId>log4j-core</artifactId>
        <version>2.8.2</version>
    </dependency>
    <dependency>
        <groupId>com.fasterxml.jackson.core</groupId>
        <artifactId>jackson-databind</artifactId>
        <version>2.9.9</version>
    </dependency>
    <!-- junit 单元测试 -->
    <dependency>
        <groupId>junit</groupId>
        <artifactId>junit</artifactId>
        <version>4.12</version>
    </dependency>
</dependencies>

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();
	}
}

索引-创建

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 0

索引-查询

查询

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 0

索引-删除

删除

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 0

重构

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。

public class SomeClass {
    public static void main(String[] args) throws IOException {
        RestHighLevelClient client = new RestHighLevelClient(
                RestClient.builder(new HttpHost("localhost", 9200, "http")));
		
        ...
        
        client.close();
    }
}

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
        });
    }
}

文档-新增

新增

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:UPDATED

Process finished with exit code 0

文档-修改

修改

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:UPDATED

Process finished with exit code 0

文档-查询

查询

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"}

Process finished with exit code 0

文档-删除

删除

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=[]}]

Process finished with exit code 0

文档-批量新增

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;@2beee7ff

Process finished with exit code 0

文档-批量删除

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;@7b02881e

Process finished with exit code 0

文档-高级查询-全量查询

先批量增加数据

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());
        });
    }
}

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

文档-高级查询-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);
    }
}

took:1ms
timeout:false
total:1 hits
MaxScore:1.0
hits========>>
{"name":"lisi","age":"30","sex":"女"}
<<========

文档-高级查询-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);
    }

}

took:1ms
timeout:false
total:6 hits
MaxScore:1.0
hits========>>
{"name":"zhangsan","age":"10","sex":"女"}
{"name":"lisi","age":"30","sex":"女"}
<<========

文档-高级查询-排序查询

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_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);
    }

}

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"}
<<========

文档-高级查询-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);
    }
}

took:28ms
timeout:false
total:1 hits
MaxScore:1.0
hits========>>
{"name":"lisi","age":"30","sex":"女"}
<<========

Process finished with exit code 0

文档-高级查询-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);
    }

}

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

文档-高级查询-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);
    }

}

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

文档-高级查询-高亮查询

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.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_HIGHLIGHT = client -> {
        // 高亮查询
        SearchRequest request = new SearchRequest().indices("user");
        //2.创建查询请求体构建器
        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        //构建查询方式：高亮查询
        TermsQueryBuilder termsQueryBuilder =
                QueryBuilders.termsQuery("name","zhangsan");
        //设置查询方式
        sourceBuilder.query(termsQueryBuilder);
        //构建高亮字段
        HighlightBuilder highlightBuilder = new HighlightBuilder();
        highlightBuilder.preTags("<font color='red'>");//设置标签前缀
        highlightBuilder.postTags("</font>");//设置标签后缀
        highlightBuilder.field("name");//设置高亮字段
        //设置高亮构建对象
        sourceBuilder.highlighter(highlightBuilder);
        //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("took::"+response.getTook());
        System.out.println("time_out::"+response.isTimedOut());
        System.out.println("total::"+hits.getTotalHits());
        System.out.println("max_score::"+hits.getMaxScore());
        System.out.println("hits::::>>");
        for (SearchHit hit : hits) {
            String sourceAsString = hit.getSourceAsString();
            System.out.println(sourceAsString);
            //打印高亮结果
            Map<String, HighlightField> highlightFields = hit.getHighlightFields();
            System.out.println(highlightFields);
        }
        System.out.println("<<::::");
    };


    public static void main(String[] args) {
        ConnectElasticsearch.connect(SEARCH_WITH_HIGHLIGHT);
    }

}

took::672ms
time_out::false
total::1 hits
max_score::1.0
hits::::>>
{"name":"zhangsan","age":"10","sex":"女"}
{name=[name], fragments[[<font color='red'>zhangsan</font>]]}
<<::::

Process finished with exit code 0

文档-高级查询-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);
    }

}

{"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

文档-高级查询-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);
    }

}

{"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

更多推荐

第一章 ElasticSearch入门

本文发布于:2023-04-30 12:30:00，感谢您对本站的认可！

本文链接:https://www.elefans.com/category/jswz/0c3a42ba81bad1bca85c9508a30af7fc.html

入门 ElasticSearch

发布评论取消回复

评论列表（有 0 条评论）

第一章 ElasticSearch入门

ElasticSearch 是什么

Elasticsearch 应用案例

环境准备

倒排索引

HTTP

索引-创建

索引-查询

索引-删除

文档-创建

文档-查询

文档-修改

文档-删除

条件查询

分页查询

查询排序

多条件查询

范围查询

聚合查询

JavaAPI

环境准备

索引-创建

索引-查询

索引-删除

重构

文档-新增

文档-修改

文档-查询

文档-删除

文档-批量新增

文档-批量删除

文档-高级查询-全量查询

文档-高级查询-条件查询

文档-高级查询-分页查询

文档-高级查询-排序查询

文档-高级查询-组合查询

文档-高级查询-范围查询

文档-高级查询-模糊查询

文档-高级查询-高亮查询

文档-高级查询-最大值查询

文档-高级查询-分组查询

相关文章

发布评论取消回复

最近发表

热门文章

标签列表