elasticsearch入门（五）：elasticsearch的数据查询
数据
首先在elasticsearch中新增3条测试数据
PUT /ecommerce/product/1
{
"name" : "gaolujie yagao",
"desc" : "gaoxiao meibai",
"price" : 30,
"producer" : "gaolujie producer",
"tags": [ "meibai", "fangzhu" ]
}
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" ]
}
1.query string search
语法：
GET /index/type/_search
- 查询全部数据
{
"took": 2, //took：耗费了几毫秒
"timed_out": false, //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）
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3, //查询结果的数量，3个document
"max_score": 1, //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": [ //包含了匹配搜索的document的详细数据
{
"_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"
]
}
}
]
}
}
- 按条件查询数据：
query string search的由来，因为search参数都是以http请求的query string来附带的，比如 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
{
"took": 35,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": null,
"hits": [
{
"_index": "ecommerce",
"_type": "product",
"_id": "3",
"_score": null,
"_source": {
"name": "zhonghua yagao",
"desc": "caoben zhiwu",
"price": 40,
"producer": "zhonghua producer",
"tags": [
"qingxin"
]
},
"sort": [
40
]
},
{
"_index": "ecommerce",
"_type": "product",
"_id": "1",
"_score": null,
"_source": {
"name": "gaolujie yagao",
"desc": "gaoxiao meibai",
"price": 30,
"producer": "gaolujie producer",
"tags": [
"meibai",
"fangzhu"
]
},
"sort": [
30
]
},
{
"_index": "ecommerce",
"_type": "product",
"_id": "2",
"_score": null,
"_source": {
"name": "jiajieshi yagao",
"desc": "youxiao fangzhu",
"price": 25,
"producer": "jiajieshi producer",
"tags": [
"fangzhu"
]
},
"sort": [
25
]
}
]
}
}
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
- 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）
匹配producer中包含yagao 和 producer的数据
GET /ecommerce/product/_search
{
"query" : {
"match" : {
"producer" : "yagao producer"
}
}
}
5.phrase search（短语搜索）
与全文检索相反，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"
}
}
}
6.highlight search（高亮搜索结果）
GET /ecommerce/product/_search
{
"query" : {
"match" : {
"producer" : "producer"
}
},
"highlight": {
"fields" : {
"producer" : {}
}
}
}
如下图所示效果：
7.各种嵌套聚合查询
- 第一个分析需求：计算每个tag下的商品数量
将文本field的fielddata属性设置为true
PUT /ecommerce/_mapping/product
{
"properties": {
"tags": {
"type": "text",
"fielddata": true
}
}
}
GET /ecommerce/product/_search
{
"size": 0, //不查询出数据，只统计
"aggs": {
"group_by_tags": {
"terms": { "field": "tags" }
}
}
}
查询结果
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"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": 1
},
{
"key": "qingxin",
"doc_count": 1
}
]
}
}
}
- 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"
}
}
}
}
查询结果
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0,
"hits": []
},
"aggregations": {
"all_tags": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "fangzhu",
"doc_count": 2
},
{
"key": "meibai",
"doc_count": 1
},
{
"key": "qingxin",
"doc_count": 1
}
]
}
}
}
- 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" }
}
}
}
}
}
查询结果
{
"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
}
}
]
}
}
}
- 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" }
}
}
}
}
}
查询结果
{
"took": 8,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0,
"hits": []
},
"aggregations": {
"all_tags": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "qingxin",
"doc_count": 1,
"avg_price": {
"value": 40
}
},
{
"key": "meibai",
"doc_count": 1,
"avg_price": {
"value": 30
}
},
{
"key": "fangzhu",
"doc_count": 2,
"avg_price": {
"value": 27.5
}
}
]
}
}
}
- 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"
}
}
}
}
}
}
}
}
查询结果
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0,
"hits": []
},
"aggregations": {
"group_by_price": {
"buckets": [
{
"key": "0.0-20.0",
"from": 0,
"to": 20,
"doc_count": 0,
"group_by_tags": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
},
{
"key": "20.0-40.0",
"from": 20,
"to": 40,
"doc_count": 2,
"group_by_tags": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "fangzhu",
"doc_count": 2,
"average_price": {
"value": 27.5
}
},
{
"key": "meibai",
"doc_count": 1,
"average_price": {
"value": 30
}
}
]
}
},
{
"key": "40.0-50.0",
"from": 40,
"to": 50,
"doc_count": 1,
"group_by_tags": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "qingxin",
"doc_count": 1,
"average_price": {
"value": 40
}
}
]
}
}
]
}
}
}