Elasticsearch_dsl基本用法_elasticsearch-dsl-优快云博客

本文链接：https://blog.youkuaiyun.com/sumatch/article/details/106469655

本文详细介绍如何使用Python连接Elasticsearch，创建索引数据，以及进行各种查询操作，包括index、query、filter、sort、分页、高亮和限制返回字段查询。此外，还深入讲解了聚合分析的方法，如以价格分桶、查询平均价格、计算每桶中车辆销售日期等。

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1.连接es

from elasticsearch import Elasticsearch
from elasticsearch_dsl import Search,Q

# 连接es
es = Elasticsearch(hosts="127.0.0.1:9200")
# 创建实例
s = Search(using=es)

2.创建索引数据

index_body = { "price" : 30000, "color" : "green", "make" : "ford", "sold" : "2014-05-18" }
es.index(index="cars", doc_type="transactions", id="bulk", body=index_body)

为了后续测试，同时创建几条数据：

{ "price" : 10000, "color" : "red", "make" : "honda", "sold" : "2014-10-28" }
{ "price" : 20000, "color" : "red", "make" : "honda", "sold" : "2014-11-05" }
{ "price" : 30000, "color" : "green", "make" : "ford", "sold" : "2014-05-18" }
{ "price" : 15000, "color" : "blue", "make" : "toyota", "sold" : "2014-07-02" }
{ "price" : 12000, "color" : "green", "make" : "toyota", "sold" : "2014-08-19" }
{ "price" : 20000, "color" : "red", "make" : "honda", "sold" : "2014-11-05" }
{ "price" : 80000, "color" : "red", "make" : "bmw", "sold" : "2014-01-01" }
{ "price" : 25000, "color" : "blue", "make" : "ford", "sold" : "2014-02-12" }

3.查询

3.1 index查询

res1 = s.index("cars").execute()
print(res1)

3.1 query查询

# 空查询
res2 = s.query("match_all").execute()
print(res2)

# 精确查询,遍历搜索返回的命中文档
res3 = s.query("term", price=25000)
for hit in res3:
    print(hit.color)

# 多值查询，可以将查询结果直接转化为字典格式方便阅读
res4 = s.query("term", price=25000).query("match", color="blue").execute().to_dict()
print(res4)

3.2 filter查询

res5 = s.filter({"term":{"price":25000}}).execute()
print(res5)

3.3 sort查询

res6 = s.sort("sold").execute()
print(res6)

3.4 分页查询

res7 = s[10:20].execute()   # {"from": 10, "size": 10}
print(res7)

3.5 高亮查询

res8 = s.highlight("sold").execute().to_dict()
print(res8)

3.6 限制返回字段查询 source

res9 = s.query("match",price=25000).source(['price', 'color']).execute().to_dict()
print(res9)

3.2 Q查询

将原生的查询语句嵌入Q中，实现组合查询。比如：

q = Q({"constant_score": {"filter": {"term":{"price":25000}}}})
res10 = s.query(q).execute()
print(res10)

或者;
q = Q('bool',
    must=[Q('match', color='blue')],
    should=[Q('match', make='ford'), Q('match', sold='2014-02-12')],
    minimum_should_match=1
)
res11 = s.query(q).execute()
print(res11)

4.聚合

聚合有bucket()，metric()方法:

bucket: 又被称作桶，满足特定条件的文档集合，可以看作是一个数据分组。聚合开始后，Elasticsearch会根据文档的值计算出文档究竟符合哪个桶，如果匹配，则将文档放入相应的桶。当所有的文档都经过计算后，再分别对每个桶进行聚合操作。
metric: 又被称作指标，对桶内的文档进行进行聚合分析操作，操作有若干种类别，如:求和、最大值、最小值、平均值等，通过对桶内文档进行相应的操作，我们可以得到想要的指标。

在/cars/transactions/中加入数据：

_index	_id	_type	_score	price	color	make	sold
cars	transactions	v9VaYHIBPeXg5lVgIA9f	1	10000	red	honda	2014-10-28
cars	transactions	wNVaYHIBPeXg5lVgIA-8	1	20000	red	honda	2014-11-05
cars	transactions	wdVaYHIBPeXg5lVgIA-8	1	30000	green	ford	2014-05-18
cars	transactions	wtVaYHIBPeXg5lVgIA_M	1	15000	blue	toyota	2014-07-02
cars	transactions	w9VaYHIBPeXg5lVgIA_c	1	12000	green	toyota	2014-08-19
cars	transactions	xNVaYHIBPeXg5lVgIA_r	1	20000	red	honda	2014-11-05
cars	transactions	xdVaYHIBPeXg5lVgIA_7	1	80000	red	bmw	2014-01-01
cars	transactions	xtVaYHIBPeXg5lVgIA_7	1	25000	blue	ford	2014-02-12

4.1以价格分桶

GET /cars/transactions/_search
{
    "size" : 0,
    "aggs" : { 
        "price" : { 
            "terms" : { 
              "field" : "price"
            }
        }
    }
}

elasticsearch-dsl:

s = Search(using=es, index="cars")
s.aggs.bucket("price", "terms", field="price")
res1 = s.execute()
print(res1.to_dict())

4.2查询平均价格

GET /cars/transactions/_search
{
   "size" : 0,
   "aggs": {
      "price": {
         "terms": {
            "field": "price"
         },
         "aggs": { 
            "avg_price": { 
               "avg": {
                  "field": "price" 
               }
            }
         }
      }
   }
}

elasticsearch-dsl:

s = Search(using=es, index="cars")
s.aggs.bucket("price", "terms", field="price").metric("avg_price", "avg", field="price")
res2 = s.execute()
print(res2.to_dict())

4.3 以价格分桶，并计算每桶中车辆最先销售日期和最后销售日期

GET /cars/transactions/_search
{
   "size" : 0,
   "aggs": {
      "price": {
         "terms": {
            "field": "price"
         },
         "aggs" : { 
                "min_sold" : { "min": { "field": "sold"} }, 
                "max_sold" : { "max": { "field": "sold"} } 
            
         }
      }
   }
}

elasticsearch-dsl:

s = Search(using=es, index="cars")
s.aggs.bucket("price", "terms", field="price")
s.aggs["price"].metric("min_sold", "min", field="sold")
s.aggs["price"].metric("max_sold", "max", field="sold")
res3 = s.execute()
print(res3.to_dict())

4.4 统计每个月销售多少台汽车

GET /cars/transactions/_search
{
   "size" : 0,
   "aggs": {
      "sales": {
         "date_histogram": {
            "field": "sold",
            "interval": "month", 
            "format": "yyyy-MM-dd" ,
            "extended_bounds": {
            "min": "2014-01-01",
            "max": "2014-12-31"
            }
         }
      }
   }
}

elasticsearch-dsl:

s = Search(using=es, index="cars")
s.aggs.bucket("sales", "date_histogram", field="sold", interval="month", format="yyyy-MM-dd", extended_bounds={"min": "2014-01-01", "max": "2014-12-31"})
res4 = s.execute()
print(res4.to_dict())

4.5限定范围内的聚合，福特车有几种价格？

GET /cars/transactions/_search
{
    "query" : {
        "match" : {
            "make" : "ford"
        }
    },
    "aggs" : {
        "price" : {
            "terms" : {
              "field" : "price"
            }
        }
    }
}

elasticsearch-dsl:

s = Search(using=es, index="cars").query("match", make="ford")
s.aggs.bucket("price", "terms", field="price")
res5 = s.execute()
print(res5.to_dict())

4.6全局桶（global），找出福特汽车与所有汽车平均售价

GET /cars/transactions/_search
{
    "size" : 0,
    "query" : {
        "match" : {
            "make" : "ford"
        }
    },
    "aggs" : {
        "single_avg_price": {
            "avg" : { "field" : "price" } 
        },
        "all": {
            "global" : {}, 
            "aggs" : {
                "avg_price": {
                    "avg" : { "field" : "price" } 
                }

            }
        }
    }
}

elasticsearch-dsl:

s = Search(using=es, index="cars").query("match", make="ford")
s.aggs.metric("single_avg_price", "avg", field="price")
s.aggs.bucket("all", "global").metric("avg_price", "avg", field="price")
res6 = s.execute()
print(res6.to_dict())

4.7过滤查找，找到售价在 $10,000 美元之上的所有汽车同时计算这些车的平均售价

GET /cars/transactions/_search
{
    "size" : 0,
    "query" : {
        "constant_score": {
            "filter": {
                "range": {
                    "price": {
                        "gte": 10000
                    }
                }
            }
        }
    },
    "aggs" : {
        "single_avg_price": {
            "avg" : { "field" : "price" }
        }
    }
}

elasticsearch-dsl:

s = Search(using=es, index="cars").query("range", price={"gte": 10000})
s.aggs.metric("single_avg_price", "avg", field="price")
res7 = s.execute()
print(res7.to_dict())

4.8内置排序。以价格分桶，且排序

GET /cars/transactions/_search
{
    "size" : 0,
    "aggs" : {
        "prices" : {
            "terms" : {
              "field" : "price",
              "order": {
                "_count" : "asc" 
              }
            }
        }
    }
}

elasticsearch-dsl:

s = Search(using=es, index="cars")
s.aggs.bucket("prices", "terms", field="price", order={"_count": "asc"})
res8 = s.execute()
print(res8.to_dict())