浅谈Elasticsearch（二）---文档基本CRUD、集群健康检查

Leo_CX330
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一、 document数据格式

面向文档的搜索分析引擎：

  1. 应用系统的数据结构都是面向对象的，复杂的
  2. 对象数据存储到数据库中，只能拆解开来，变为扁平的多张表，每次查询的时候还得还原回对象格式，相当麻烦
  3. ES是面向文档的，文档中存储的数据结构，与面向对象的数据结构是一样的，基于这种文档数据结构，es可以提供复杂的索引，全文检索，分析聚合等功能
  4. es的document用json数据格式来表达
public class Employee {

  private String email;
  private String firstName;
  private String lastName;
  private EmployeeInfo info;
  private Date joinDate;

}

private class EmployeeInfo {
  
  private String bio; // 性格
  private Integer age;
  private String[] interests; // 兴趣爱好

}

EmployeeInfo info = new EmployeeInfo();
info.setBio("curious and modest");
info.setAge(30);
info.setInterests(new String[]{"bike", "climb"});

Employee employee = new Employee();
employee.setEmail("zhangsan@sina.com");
employee.setFirstName("san");
employee.setLastName("zhang");
employee.setInfo(info);
employee.setJoinDate(new Date());

employee对象：里面包含了Employee类自己的属性，还有一个EmployeeInfo对象

两张表：employee表，employee_info表，将employee对象的数据重新拆开来，变成Employee数据和EmployeeInfo数据
employee表：email，first_name，last_name，join_date，4个字段
employee_info表：bio，age，interests，3个字段；此外还有一个外键字段，比如employee_id，关联着employee表

{
    "email":      "zhangsan@sina.com",
    "first_name": "san",
    "last_name": "zhang",
    "info": {
        "bio":         "curious and modest",
        "age":         30,
        "interests": [ "bike", "climb" ]
    },
    "join_date": "2020/12/01"
}

我们就明白了es的document数据格式和数据库的关系型数据格式的区别

二、简单的集群管理

1、快速检查集群的健康状况

es提供了一套api，叫做cat api，可以查看es中各种各样的数据

GET /_cat/health?v

epoch      timestamp cluster       status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_time active_shards_percent
1488006741 15:12:21  elasticsearch yellow          1         1      1   1    0    0        1             0                  -                 50.0%

epoch      timestamp cluster       status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_time active_shards_percent
1488007113 15:18:33  elasticsearch green           2         2      2   1    0    0        0             0                  -                100.0%

epoch      timestamp cluster       status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_time active_shards_percent
1488007216 15:20:16  elasticsearch yellow          1         1      1   1    0    0        1             0                  -                 50.0%

2、集群的健康状况？green、yellow、red？

  1. green：每个索引的primary shard和replica shard都是active状态的
  2. yellow：每个索引的primary shard都是active状态的，但是部分replica shard不是active状态，处于不可用的状态
  3. red：不是所有索引的primary shard都是active状态的，部分索引有数据丢失了

3、快速查看集群中有哪些索引？


GET /_cat/indices?v

health status index   uuid                   pri rep docs.count docs.deleted store.size pri.store.size
yellow open   .kibana rUm9n9wMRQCCrRDEhqneBg   1   1          1            0      3.1kb          3.1kb

4、 简单的索引操作


创建索引：PUT /test_index?pretty

health status index      uuid                   pri rep docs.count docs.deleted store.size pri.store.size
yellow open   test_index XmS9DTAtSkSZSwWhhGEKkQ   5   1          0            0       650b           650b
yellow open   .kibana    rUm9n9wMRQCCrRDEhqneBg   1   1          1            0      3.1kb          3.1kb

删除索引：DELETE /test_index?pretty

health status index   uuid                   pri rep docs.count docs.deleted store.size pri.store.size
yellow open   .kibana rUm9n9wMRQCCrRDEhqneBg   1   1          1            0      3.1kb          3.1kb

三、面向document的CRUD

1、新增商品：新增文档，建立索引


PUT /index/type/id
{
  "json数据"
}

PUT /ecommerce/product/1
{
    "name" : "gaolujie yagao",
    "desc" :  "gaoxiao meibai",
    "price" :  30,
    "producer" :      "gaolujie producer",
    "tags": [ "meibai", "fangzhu" ]
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 1,
  "result": "created",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": true
}

PUT /ecommerce/product/2
{
    "name" : "jiajieshi yagao",
    "desc" :  "youxiao fangzhu",
    "price" :  25,
    "producer" :      "jiajieshi producer",
    "tags": [ "fangzhu" ]
}

PUT /ecommerce/product/3
{
    "name" : "zhonghua yagao",
    "desc" :  "caoben zhiwu",
    "price" :  40,
    "producer" :      "zhonghua producer",
    "tags": [ "qingxin" ]
}

es会自动建立index和type，不需要提前创建，而且es默认会对document每个field都建立倒排索引，让其可以被搜索

2、查询商品：检索文档


GET /index/type/id

GET /ecommerce/product/1

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 1,
  "found": true,
  "_source": {
    "name": "gaolujie yagao",
    "desc": "gaoxiao meibai",
    "price": 30,
    "producer": "gaolujie producer",
    "tags": [
      "meibai",
      "fangzhu"
    ]
  }
}

3、 修改商品：替换文档


PUT /ecommerce/product/1
{
    "name" : "jiaqiangban gaolujie yagao",
    "desc" :  "gaoxiao meibai",
    "price" :  30,
    "producer" :      "gaolujie producer",
    "tags": [ "meibai", "fangzhu" ]
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 1,
  "result": "created",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": true
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 2,
  "result": "updated",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": false
}


PUT /ecommerce/product/1
{
    "name" : "jiaqiangban gaolujie yagao"
}

替换方式有一个不好，即使必须带上所有的field，才能去进行信息的修改

4、修改商品：更新文档


POST /ecommerce/product/1/_update
{
  "doc": {
    "name": "jiaqiangban gaolujie yagao"
  }
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 8,
  "result": "updated",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  }
}

5、 删除商品：删除文档


DELETE /ecommerce/product/1

{
  "found": true,
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "_version": 9,
  "result": "deleted",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  }
}

{
  "_index": "ecommerce",
  "_type": "product",
  "_id": "1",
  "found": false
}

四、多种搜索方式

1、query string search


搜索全部商品：GET /ecommerce/product/_search

took：耗费了几毫秒
timed_out：是否超时，这里是没有
_shards：数据拆成了5个分片，所以对于搜索请求，会打到所有的primary shard（或者是它的某个replica shard也可以）
hits.total：查询结果的数量，3个document
hits.max_score：score的含义，就是document对于一个search的相关度的匹配分数，越相关，就越匹配，分数也高
hits.hits：包含了匹配搜索的document的详细数据


{
  "took": 2,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 3,
    "max_score": 1,
    "hits": [
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "2",
        "_score": 1,
        "_source": {
          "name": "jiajieshi yagao",
          "desc": "youxiao fangzhu",
          "price": 25,
          "producer": "jiajieshi producer",
          "tags": [
            "fangzhu"
          ]
        }
      },
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "1",
        "_score": 1,
        "_source": {
          "name": "gaolujie yagao",
          "desc": "gaoxiao meibai",
          "price": 30,
          "producer": "gaolujie producer",
          "tags": [
            "meibai",
            "fangzhu"
          ]
        }
      },
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "3",
        "_score": 1,
        "_source": {
          "name": "zhonghua yagao",
          "desc": "caoben zhiwu",
          "price": 40,
          "producer": "zhonghua producer",
          "tags": [
            "qingxin"
          ]
        }
      }
    ]
  }
}

query string search的由来，因为search参数都是以http请求的query string来附带的

搜索商品名称中包含yagao的商品，而且按照售价降序排序：GET /ecommerce/product/_search?q=name:yagao&sort=price:desc

适用于临时的在命令行使用一些工具，比如curl，快速的发出请求，来检索想要的信息；但是如果查询请求很复杂，是很难去构建的
在生产环境中，几乎很少使用query string search

2、query DSL


DSL：Domain Specified Language，特定领域的语言
http request body：请求体，可以用json的格式来构建查询语法，比较方便，可以构建各种复杂的语法，比query string search肯定强大多了

查询所有的商品

GET /ecommerce/product/_search
{
  "query": { "match_all": {} }
}

查询名称包含yagao的商品，同时按照价格降序排序

GET /ecommerce/product/_search
{
    "query" : {
        "match" : {
            "name" : "yagao"
        }
    },
    "sort": [
        { "price": "desc" }
    ]
}

分页查询商品，总共3条商品，假设每页就显示1条商品，现在显示第2页，所以就查出来第2个商品

GET /ecommerce/product/_search
{
  "query": { "match_all": {} },
  "from": 1,
  "size": 1
}

指定要查询出来商品的名称和价格就可以

GET /ecommerce/product/_search
{
  "query": { "match_all": {} },
  "_source": ["name", "price"]
}

更加适合生产环境的使用，可以构建复杂的查询

3、query filter


搜索商品名称包含yagao，而且售价大于25元的商品

GET /ecommerce/product/_search
{
    "query" : {
        "bool" : {
            "must" : {
                "match" : {
                    "name" : "yagao" 
                }
            },
            "filter" : {
                "range" : {
                    "price" : { "gt" : 25 } 
                }
            }
        }
    }
}

4、full-text search（全文检索）


GET /ecommerce/product/_search
{
    "query" : {
        "match" : {
            "producer" : "yagao producer"
        }
    }
}


{
  "took": 4,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 0.70293105,
    "hits": [
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "4",
        "_score": 0.70293105,
        "_source": {
          "name": "special yagao",
          "desc": "special meibai",
          "price": 50,
          "producer": "special yagao producer",
          "tags": [
            "meibai"
          ]
        }
      },
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "1",
        "_score": 0.25811607,
        "_source": {
          "name": "gaolujie yagao",
          "desc": "gaoxiao meibai",
          "price": 30,
          "producer": "gaolujie producer",
          "tags": [
            "meibai",
            "fangzhu"
          ]
        }
      },
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "3",
        "_score": 0.25811607,
        "_source": {
          "name": "zhonghua yagao",
          "desc": "caoben zhiwu",
          "price": 40,
          "producer": "zhonghua producer",
          "tags": [
            "qingxin"
          ]
        }
      },
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "2",
        "_score": 0.1805489,
        "_source": {
          "name": "jiajieshi yagao",
          "desc": "youxiao fangzhu",
          "price": 25,
          "producer": "jiajieshi producer",
          "tags": [
            "fangzhu"
          ]
        }
      }
    ]
  }
}

5、phrase search（短语搜索）


跟全文检索相对应，相反，全文检索会将输入的搜索串拆解开来，去倒排索引里面去一一匹配，只要能匹配上任意一个拆解后的单词，就可以作为结果返回
phrase search，要求输入的搜索串，必须在指定的字段文本中，完全包含一模一样的，才可以算匹配，才能作为结果返回

GET /ecommerce/product/_search
{
    "query" : {
        "match_phrase" : {
            "producer" : "yagao producer"
        }
    }
}

{
  "took": 11,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 0.70293105,
    "hits": [
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "4",
        "_score": 0.70293105,
        "_source": {
          "name": "special yagao",
          "desc": "special meibai",
          "price": 50,
          "producer": "special yagao producer",
          "tags": [
            "meibai"
          ]
        }
      }
    ]
  }
}

6、highlight search（高亮搜索结果）

GET /ecommerce/product/_search
{
    "query" : {
        "match" : {
            "producer" : "producer"
        }
    },
    "highlight": {
        "fields" : {
            "producer" : {}
        }
    }
}

五、聚合分析

1、计算每个tag下的商品数量


GET /ecommerce/product/_search
{
  "size": 0,
  "aggs": {
    "all_tags": {
      "terms": { "field": "tags" }
    }
  }
}



{
  "took": 20,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "group_by_tags": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "fangzhu",
          "doc_count": 2
        },
        {
          "key": "meibai",
          "doc_count": 2
        },
        {
          "key": "qingxin",
          "doc_count": 1
        }
      ]
    }
  }
}

3、对名称中包含yagao的商品，计算每个tag下的商品数量


GET /ecommerce/product/_search
{
  "size": 0,
  "query": {
    "match": {
      "name": "yagao"
    }
  },
  "aggs": {
    "all_tags": {
      "terms": {
        "field": "tags"
      }
    }
  }
}

4、先分组，再算每组的平均值，计算每个tag下的商品的平均价格


GET /ecommerce/product/_search
{
    "size": 0,
    "aggs" : {
        "group_by_tags" : {
            "terms" : { "field" : "tags" },
            "aggs" : {
                "avg_price" : {
                    "avg" : { "field" : "price" }
                }
            }
        }
    }
}

{
  "took": 8,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "group_by_tags": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "fangzhu",
          "doc_count": 2,
          "avg_price": {
            "value": 27.5
          }
        },
        {
          "key": "meibai",
          "doc_count": 2,
          "avg_price": {
            "value": 40
          }
        },
        {
          "key": "qingxin",
          "doc_count": 1,
          "avg_price": {
            "value": 40
          }
        }
      ]
    }
  }
}

5、计算每个tag下的商品的平均价格，并且按照平均价格降序排序


GET /ecommerce/product/_search
{
    "size": 0,
    "aggs" : {
        "all_tags" : {
            "terms" : { "field" : "tags", "order": { "avg_price": "desc" } },
            "aggs" : {
                "avg_price" : {
                    "avg" : { "field" : "price" }
                }
            }
        }
    }
}

6、按照指定的价格范围区间进行分组，然后在每组内再按照tag进行分组，最后再计算每组的平均价格


GET /ecommerce/product/_search
{
  "size": 0,
  "aggs": {
    "group_by_price": {
      "range": {
        "field": "price",
        "ranges": [
          {
            "from": 0,
            "to": 20
          },
          {
            "from": 20,
            "to": 40
          },
          {
            "from": 40,
            "to": 50
          }
        ]
      },
      "aggs": {
        "group_by_tags": {
          "terms": {
            "field": "tags"
          },
          "aggs": {
            "average_price": {
              "avg": {
                "field": "price"
              }
            }
          }
        }
      }
    }
  }
}
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