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一、简介和安装
ElasticSearch 是一个基于 Lucene 的搜索服务器。它提供了一个分布式多用户能力的全文搜索引擎,基于 RESTful web 接口。
这里使用 Docker 安装 Elasticsearch:
docker run -d \
--name elasticsearch \
-p 9200:9200 \
-p 9300:9300 \
-e "discovery.type=single-node" \
-v /home/docker/es/plugins:/usr/share/elasticsearch/plugins \
-v /home/docker/es/data:/usr/share/elasticsearch/data \
--restart always \
elasticsearch:7.14.2
如果启动报错,执行 chmod 777 /home/docker/es/data
访问 9200 端口,能够看见如下信息则表示搭建成功。
二、相关概念
-
索引(Index): ES将数据存储于一个或多个索引中,索引是具有类似特性的文档的集合。类比传统的关系型数据库领域来说,索引相当于SQL中的一个数据库,或者一个数据存储方案(schema)。索引由其名称(必须为全小写字符)进行标识,并通过引用此名称完成文档的创建、搜索、更新及删除操作。一个ES集群中可以按需创建任意数目的索引。
-
类型(Type):类型是索引内部的逻辑分区(category/partition),然而其意义完全取决于用户需求。因此,一个索引内部可定义一个或多个类型(type)。一般来说,类型就是为那些拥有相同的域的文档做的预定义。例如,在索引中,可以定义一个用于存储用户数据的类型,一个存储日志数据的类型,以及一个存储评论数据的类型。类比传统的关系型数据库领域来说,类型相当于“表”。
-
文档(Document):文档是Lucene索引和搜索的原子单位,它是包含了一个或多个域的容器,基于JSON格式进行表示。文档由一个或多个域组成,每个域拥有一个名字及一个或多个值,有多个值的域通常称为“多值域”。每个文档可以存储不同的域集,但同一类型下的文档至应该有某种程度上的相似之处。
-
映射(Mapping): ES中,所有的文档在存储之前都要首先进行分析。用户可根据需要定义如何将文本分割成token、哪些token应该被过滤掉,以及哪些文本需要进行额外处理等等。另外,ES还提供了额外功能,例如将域中的内容按需排序。事实上,ES也能自动根据其值确定域的类型。
-
节点(Node):运行了单个实例的ES主机称为节点,它是集群的一个成员,可以存储数据、参与集群索引及搜索操作。类似于集群,节点靠其名称进行标识,默认为启动时自动生成的随机Marvel字符名称。用户可以按需要自定义任何希望使用的名称,但出于管理的目的,此名称应该尽可能有较好的识别性。节点通过为其配置的ES集群名称确定其所要加入的集群。
-
分片(Shard)和副本(Replica):ES的“分片(shard)”机制可将一个索引内部的数据分布地存储于多个节点,它通过将一个索引切分为多个底层物理的Lucene索引完成索引数据的分割存储功能,这每一个物理的Lucene索引称为一个分片(shard)。每个分片其内部都是一个全功能且独立的索引,因此可由集群中的任何主机存储。创建索引时,用户可指定其分片的数量,默认数量为5个。
三、基本使用
1、基础
1.1 索引
1.1.1 创建索引
PUT http://127.0.0.1:9200/sj
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "sj"
}
1.1.2 查看所有索引
GET http://127.0.0.1:9200/_cat/indices
green open .geoip_databases 69SccWg_Qy-WcYTahh-x7g 1 0 46 7 48.2mb 48.2mb
yellow open bank p1ZJWKzLSL2yPe_NfhED5w 1 1 1000 0 372.7kb 372.7kb
green open .apm-custom-link sfwTjQZjTMy7QZgQfR-0Zg 1 0 0 0 208b 208b
yellow open my_index a_wq-ITURwCCxxa5TCQgAA 1 1 0 0 208b 208b
green open .kibana_task_manager_7.14.2_001 zi4N4a88S5uJC3JDjRvu7A 1 0 14 2758 474.9kb 474.9kb
yellow open sj Frku6z9qQ-ih4cNV-CcyiQ 1 1 1 2 17.7kb 17.7kb
green open .apm-agent-configuration cv7NcBeERa-ZwoRuXEgbgQ 1 0 0 0 208b 208b
green open .kibana_7.14.2_001 2qIDo8JJSGuJj7DdBOYzAg 1 0 44 1 2.3mb 2.3mb
yellow open 2sj xAc5JA7WSD-YSGei6RhDaQ 1 1 0 0 208b 208b
yellow open index WvnJ6OIRQ2GGewXderW0ew 1 1 4 0 16kb 16kb
green open .tasks sn8q8od2QNC9rujgg51RGQ 1 0 8 0 36.6kb 36.6kb
green open .kibana-event-log-7.14.2-000001 7_Wq_AiMRjemTW3nOOSD2g 1 0 5 0 27.3kb 27.3kb
1.1.3 删除索引
DELETE http://127.0.0.1:9200/sj
{
"acknowledged": true
}
1.2 文档
1.2.1 创建文档
POST http://127.0.0.1:9200/sj/sj/1001
{
"title": "小米手机",
"catagory": "xiaomi",
"images": "www.baidu.com",
"price": 8999
}
{
"_index": "sj",
"_type": "sj",
"_id": "1001",
"_version": 2,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 1,
"_primary_term": 9
}
1.2.2 查询单个文档
GET http://127.0.0.1:9200/sj/sj/1001
{
"_index": "sj",
"_type": "sj",
"_id": "1001",
"_version": 2,
"_seq_no": 1,
"_primary_term": 9,
"found": true,
"_source": {
"title": "小米手机",
"catagory": "xiaomi",
"images": "www.baidu.com",
"price": 8999
}
}
1.2.3 查询单个索引下所有文档
GET http://127.0.0.1:9200/sj/_search
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "sj",
"_type": "sj",
"_id": "1001",
"_score": 1.0,
"_source": {
"title": "小米手机",
"catagory": "xiaomi",
"images": "www.baidu.com",
"price": 8999
}
}
]
}
}
1.2.4 局部更新文档
POST http://127.0.0.1:9200/sj/sj/1001/_update
{
"doc": {
"title": "华为手机"
}
}
{
"_index": "sj",
"_type": "sj",
"_id": "1001",
"_version": 3,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 2,
"_primary_term": 9
}
再次查询结果:
{
"_index": "sj",
"_type": "sj",
"_id": "1001",
"_version": 3,
"_seq_no": 2,
"_primary_term": 9,
"found": true,
"_source": {
"title": "华为手机",
"catagory": "xiaomi",
"images": "www.baidu.com",
"price": 8999
}
}
1.2.5 完全覆盖更新
POST http://127.0.0.1:9200/sj/sj/1001
{
"title": "锤子手机"
}
{
"_index": "sj",
"_type": "sj",
"_id": "1001",
"_version": 4,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 3,
"_primary_term": 9
}
再次查询结果:
{
"_index": "sj",
"_type": "sj",
"_id": "1001",
"_version": 4,
"_seq_no": 3,
"_primary_term": 9,
"found": true,
"_source": {
"title": "锤子手机"
}
}
1.2.6 删除文档
DELETE http://127.0.0.1:9200/sj/sj/1001
{
"_index": "sj",
"_type": "sj",
"_id": "1001",
"_version": 5,
"result": "deleted",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 4,
"_primary_term": 9
}
2、进阶
2.1 批量操作
2.1.1 批量创建
POST http://127.0.0.1:9200/sj/sj/_bulk
{"index":{"_id":"11"}}
{"price":10,"productID":"华为"}
{"index":{"_id":"12"}}
{"price":20,"productID":"小米"}
{"index":{"_id":"13"}}
{"price":30,"productID":"oppo"}
{"index":{"_id":"14"}}
{"price":40,"productID":"vivo"}
{
"took": 654,
"errors": false,
"items": [
{
"index": {
"_index": "sj",
"_type": "sj",
"_id": "11",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 5,
"_primary_term": 9,
"status": 201
}
},
{
"index": {
"_index": "sj",
"_type": "sj",
"_id": "12",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 6,
"_primary_term": 9,
"status": 201
}
},
{
"index": {
"_index": "sj",
"_type": "sj",
"_id": "13",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 7,
"_primary_term": 9,
"status": 201
}
},
{
"index": {
"_index": "sj",
"_type": "sj",
"_id": "14",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 8,
"_primary_term": 9,
"status": 201
}
}
]
}
2.1.2 批量增删改
POST http://127.0.0.1:9200/sj/sj/_bulk
{"delete":{"_index":"sj","_type":"sj","_id":"11"}}
{"create":{"_index":"sj","_type":"sj","_id":"10"}}
{"price":50,"productID":"1115"}
{"index":{"_index":"sj","_type":"sj","_id":"16"}}
{"price":60,"productID":"1116"}
{"update":{"_index":"sj","_type":"sj","_id":"12"}}
{"doc": {"price":120,"productID":"11120"}}
{
"took": 141,
"errors": false,
"items": [
{
"index": {
"_index": "sj",
"_type": "sj",
"_id": "11",
"_version": 2,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 9,
"_primary_term": 9,
"status": 200
}
},
{
"index": {
"_index": "sj",
"_type": "sj",
"_id": "12",
"_version": 2,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 10,
"_primary_term": 9,
"status": 200
}
},
{
"index": {
"_index": "sj",
"_type": "sj",
"_id": "13",
"_version": 2,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 11,
"_primary_term": 9,
"status": 200
}
},
{
"index": {
"_index": "sj",
"_type": "sj",
"_id": "14",
"_version": 2,
"result": "updated",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 12,
"_primary_term": 9,
"status": 200
}
}
]
}
2.2 普通查询
2.2.1 数据导入
POST http://127.0.0.1:9200/bank/account/_bulk
... (es 官方测试数据,可以 github 中找到)
{
"took": 2450,
"errors": false,
...
}
2.2.2 分页查询
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"match_all": {}
},
"from": 0,
"size": 2
}
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1000,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "bank",
"_type": "account",
"_id": "1",
"_score": 1.0,
"_source": {
"account_number": 1,
"balance": 39225,
"firstname": "Amber",
"lastname": "Duke",
"age": 32,
"gender": "M",
"address": "880 Holmes Lane",
"employer": "Pyrami",
"email": "amberduke@pyrami.com",
"city": "Brogan",
"state": "IL"
}
},
{
"_index": "bank",
"_type": "account",
"_id": "6",
"_score": 1.0,
"_source": {
"account_number": 6,
"balance": 5686,
"firstname": "Hattie",
"lastname": "Bond",
"age": 36,
"gender": "M",
"address": "671 Bristol Street",
"employer": "Netagy",
"email": "hattiebond@netagy.com",
"city": "Dante",
"state": "TN"
}
}
]
}
}
2.2.3 返回部分字段
POST http://127.0.0.1:9200/bank/_search
{
"query":{
"match_all":{}
},
"sort":[
{
"balance": {
"order": "desc"
}
}
],
"from": 0,
"size": 2,
"_source": [
"firstname",
"lastname",
"city",
"age"
]
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1000,
"relation": "eq"
},
"max_score": null,
"hits": [
{
"_index": "bank",
"_type": "account",
"_id": "248",
"_score": null,
"_source": {
"firstname": "West",
"city": "Maury",
"age": 36,
"lastname": "England"
},
"sort": [
49989
]
},
{
"_index": "bank",
"_type": "account",
"_id": "854",
"_score": null,
"_source": {
"firstname": "Jimenez",
"city": "Moscow",
"age": 25,
"lastname": "Barry"
},
"sort": [
49795
]
}
]
}
}
2.2.4 数值等值匹配
对于数值,只查询等值匹配的数据
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"match":{
"account_number": 20
}
}
}
{
"took": 0,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "bank",
"_type": "account",
"_id": "20",
"_score": 1.0,
"_source": {
"account_number": 20,
"balance": 16418,
"firstname": "Elinor",
"lastname": "Ratliff",
"age": 36,
"gender": "M",
"address": "282 Kings Place",
"employer": "Scentric",
"email": "elinorratliff@scentric.com",
"city": "Ribera",
"state": "WA"
}
}
]
}
}
2.2.5 字符串模糊匹配
将匹配类似的数据
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"match":{
"address": "mill lane foajfoaofjja"
}
}
}
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
...
}
2.2.6 短语匹配
不拆分关键字,当作一个整体
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"match_phrase":{
"address": "mill lane"
}
}
}
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 9.507477,
"hits": [
{
"_index": "bank",
"_type": "account",
"_id": "136",
"_score": 9.507477,
"_source": {
"account_number": 136,
"balance": 45801,
"firstname": "Winnie",
"lastname": "Holland",
"age": 38,
"gender": "M",
"address": "198 Mill Lane",
"employer": "Neteria",
"email": "winnieholland@neteria.com",
"city": "Urie",
"state": "IL"
}
}
]
}
}
2.2.7 多字段匹配
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"multi_match":{
"query": "mill Movico",
"fields": ["address", "city"]
}
}
}
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 4,
"relation": "eq"
},
"max_score": 6.5059485,
"hits": [
{
"_index": "bank",
"_type": "account",
"_id": "472",
"_score": 6.5059485,
"_source": {
"account_number": 472,
"balance": 25571,
"firstname": "Lee",
"lastname": "Long",
"age": 32,
"gender": "F",
"address": "288 Mill Street",
"employer": "Comverges",
"email": "leelong@comverges.com",
"city": "Movico",
"state": "MT"
}
},
{
"_index": "bank",
"_type": "account",
"_id": "970",
"_score": 5.4032025,
"_source": {
"account_number": 970,
"balance": 19648,
"firstname": "Forbes",
"lastname": "Wallace",
"age": 28,
"gender": "M",
"address": "990 Mill Road",
"employer": "Pheast",
"email": "forbeswallace@pheast.com",
"city": "Lopezo",
"state": "AK"
}
},
{
"_index": "bank",
"_type": "account",
"_id": "136",
"_score": 5.4032025,
"_source": {
"account_number": 136,
"balance": 45801,
"firstname": "Winnie",
"lastname": "Holland",
"age": 38,
"gender": "M",
"address": "198 Mill Lane",
"employer": "Neteria",
"email": "winnieholland@neteria.com",
"city": "Urie",
"state": "IL"
}
},
{
"_index": "bank",
"_type": "account",
"_id": "345",
"_score": 5.4032025,
"_source": {
"account_number": 345,
"balance": 9812,
"firstname": "Parker",
"lastname": "Hines",
"age": 38,
"gender": "M",
"address": "715 Mill Avenue",
"employer": "Baluba",
"email": "parkerhines@baluba.com",
"city": "Blackgum",
"state": "KY"
}
}
]
}
}
2.2.8 复合查询
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"bool":{
"must":[
{"match": {
"gender": "M"
}},
{"match": {
"address": "mill"
}}
],
"must_not":[
{
"match":{
"age": 28
}
}
],
"should":[
{"match": {
"lastname": "Wallace"
}}
]
}
}
}
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 6.0824604,
"hits": [
{
"_index": "bank",
"_type": "account",
"_id": "136",
"_score": 6.0824604,
"_source": {
"account_number": 136,
"balance": 45801,
"firstname": "Winnie",
"lastname": "Holland",
"age": 38,
"gender": "M",
"address": "198 Mill Lane",
"employer": "Neteria",
"email": "winnieholland@neteria.com",
"city": "Urie",
"state": "IL"
}
},
{
"_index": "bank",
"_type": "account",
"_id": "345",
"_score": 6.0824604,
"_source": {
"account_number": 345,
"balance": 9812,
"firstname": "Parker",
"lastname": "Hines",
"age": 38,
"gender": "M",
"address": "715 Mill Avenue",
"employer": "Baluba",
"email": "parkerhines@baluba.com",
"city": "Blackgum",
"state": "KY"
}
}
]
}
}
2.2.9 过滤
must should会贡献相关性得分,filter 不参与
POST http://127.0.0.1:9200/bank/_search
{
"query":{
"bool":{
"must":[
{"match": {
"gender": "M"
}},
{"match": {
"address": "mill"
}}
],
"must_not":[
{
"match":{
"age": 28
}
}
],
"should":[
{"match": {
"lastname": "Wallace"
}}
],
"filter":[
{"range":{
"age":{
"gte": 18,
"lte": 40
}
}}
]
}
}
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 6.0824604,
"hits": [
{
"_index": "bank",
"_type": "account",
"_id": "136",
"_score": 6.0824604,
"_source": {
"account_number": 136,
"balance": 45801,
"firstname": "Winnie",
"lastname": "Holland",
"age": 38,
"gender": "M",
"address": "198 Mill Lane",
"employer": "Neteria",
"email": "winnieholland@neteria.com",
"city": "Urie",
"state": "IL"
}
},
{
"_index": "bank",
"_type": "account",
"_id": "345",
"_score": 6.0824604,
"_source": {
"account_number": 345,
"balance": 9812,
"firstname": "Parker",
"lastname": "Hines",
"age": 38,
"gender": "M",
"address": "715 Mill Avenue",
"employer": "Baluba",
"email": "parkerhines@baluba.com",
"city": "Blackgum",
"state": "KY"
}
}
]
}
}
2.2.10 term
和match类似,推荐:找精确字段使用term,找文本字段使用match
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"term":{
"account_number": 20
}
}
}
2.3 聚合查询
2.3.1 聚合一
搜索 address中包含mill的所有人的年龄分布以及平均年龄
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"match":{
"address": "mill"
}
},
"aggs": {
"ageAgg": {
"terms":{
"field": "age",
"size": 10
}
},
"ageAvg": {
"avg": {
"field": "age"
}
},
"balanceAvg": {
"avg": {
"field": "balance"
}
}
},
"size": 0
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 4,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"ageAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 38,
"doc_count": 2
},
{
"key": 28,
"doc_count": 1
},
{
"key": 32,
"doc_count": 1
}
]
},
"ageAvg": {
"value": 34.0
},
"balanceAvg": {
"value": 25208.0
}
}
}
2.3.2 聚合二
按照年龄聚合,并且请求这些年龄段的这些人的平均薪资
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"match_all": {}
},
"aggs": {
"ageAgg": {
"terms": {
"field": "age",
"size": 100
},
"aggs": {
"ageAvg": {
"avg": {
"field": "balance"
}
}
}
}
},
"size": 0
}
{
"query":{
"match_all": {}
},
"aggs": {
"ageAgg": {
"terms": {
"field": "age",
"size": 100
},
"aggs": {
"ageAvg": {
"avg": {
"field": "balance"
}
}
}
}
},
"size": 0
}
2.3.3 聚合三
查出所有年龄分布,并且这些年龄段中M的平均薪资和F的平均薪资以及这个年龄段的总体平均薪资
GET http://127.0.0.1:9200/bank/_search
{
"query":{
"match_all": {}
},
"aggs": {
"ageAgg": {
"terms": {
"field": "age",
"size": 100
},
"aggs": {
"genderAgg": {
"terms": {
"field": "gender.keyword"
},
"aggs": {
"balanceAvg": {
"avg": {
"field": "balance"
}
}
}
},
"balanceAvg": {
"avg": {
"field": "balance"
}
}
}
}
},
"size": 0
}
{
"took": 7,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1000,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"ageAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 31,
"doc_count": 61,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 35,
"balanceAvg": {
"value": 29565.628571428573
}
},
{
"key": "F",
"doc_count": 26,
"balanceAvg": {
"value": 26626.576923076922
}
}
]
},
"balanceAvg": {
"value": 28312.918032786885
}
},
{
"key": 39,
"doc_count": 60,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 38,
"balanceAvg": {
"value": 26348.684210526317
}
},
{
"key": "M",
"doc_count": 22,
"balanceAvg": {
"value": 23405.68181818182
}
}
]
},
"balanceAvg": {
"value": 25269.583333333332
}
},
{
"key": 26,
"doc_count": 59,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 32,
"balanceAvg": {
"value": 25094.78125
}
},
{
"key": "F",
"doc_count": 27,
"balanceAvg": {
"value": 20943.0
}
}
]
},
"balanceAvg": {
"value": 23194.813559322032
}
},
{
"key": 32,
"doc_count": 52,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 28,
"balanceAvg": {
"value": 22941.964285714286
}
},
{
"key": "F",
"doc_count": 24,
"balanceAvg": {
"value": 25128.958333333332
}
}
]
},
"balanceAvg": {
"value": 23951.346153846152
}
},
{
"key": 35,
"doc_count": 52,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 28,
"balanceAvg": {
"value": 24226.321428571428
}
},
{
"key": "F",
"doc_count": 24,
"balanceAvg": {
"value": 19698.791666666668
}
}
]
},
"balanceAvg": {
"value": 22136.69230769231
}
},
{
"key": 36,
"doc_count": 52,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 31,
"balanceAvg": {
"value": 20884.677419354837
}
},
{
"key": "F",
"doc_count": 21,
"balanceAvg": {
"value": 24079.04761904762
}
}
]
},
"balanceAvg": {
"value": 22174.71153846154
}
},
{
"key": 22,
"doc_count": 51,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 27,
"balanceAvg": {
"value": 22152.74074074074
}
},
{
"key": "M",
"doc_count": 24,
"balanceAvg": {
"value": 27631.708333333332
}
}
]
},
"balanceAvg": {
"value": 24731.07843137255
}
},
{
"key": 28,
"doc_count": 51,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 31,
"balanceAvg": {
"value": 27076.8064516129
}
},
{
"key": "M",
"doc_count": 20,
"balanceAvg": {
"value": 30129.35
}
}
]
},
"balanceAvg": {
"value": 28273.882352941175
}
},
{
"key": 33,
"doc_count": 50,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 26,
"balanceAvg": {
"value": 26437.615384615383
}
},
{
"key": "M",
"doc_count": 24,
"balanceAvg": {
"value": 23638.291666666668
}
}
]
},
"balanceAvg": {
"value": 25093.94
}
},
{
"key": 34,
"doc_count": 49,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 30,
"balanceAvg": {
"value": 26039.166666666668
}
},
{
"key": "M",
"doc_count": 19,
"balanceAvg": {
"value": 28027.0
}
}
]
},
"balanceAvg": {
"value": 26809.95918367347
}
},
{
"key": 30,
"doc_count": 47,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 25,
"balanceAvg": {
"value": 25316.16
}
},
{
"key": "M",
"doc_count": 22,
"balanceAvg": {
"value": 20028.545454545456
}
}
]
},
"balanceAvg": {
"value": 22841.106382978724
}
},
{
"key": 21,
"doc_count": 46,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 24,
"balanceAvg": {
"value": 28210.916666666668
}
},
{
"key": "M",
"doc_count": 22,
"balanceAvg": {
"value": 25640.18181818182
}
}
]
},
"balanceAvg": {
"value": 26981.434782608696
}
},
{
"key": 40,
"doc_count": 45,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 24,
"balanceAvg": {
"value": 26474.958333333332
}
},
{
"key": "F",
"doc_count": 21,
"balanceAvg": {
"value": 27992.571428571428
}
}
]
},
"balanceAvg": {
"value": 27183.17777777778
}
},
{
"key": 20,
"doc_count": 44,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 27,
"balanceAvg": {
"value": 29047.444444444445
}
},
{
"key": "F",
"doc_count": 17,
"balanceAvg": {
"value": 25666.647058823528
}
}
]
},
"balanceAvg": {
"value": 27741.227272727272
}
},
{
"key": 23,
"doc_count": 42,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 24,
"balanceAvg": {
"value": 27730.75
}
},
{
"key": "F",
"doc_count": 18,
"balanceAvg": {
"value": 26758.833333333332
}
}
]
},
"balanceAvg": {
"value": 27314.214285714286
}
},
{
"key": 24,
"doc_count": 42,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 23,
"balanceAvg": {
"value": 29414.521739130436
}
},
{
"key": "M",
"doc_count": 19,
"balanceAvg": {
"value": 27435.052631578947
}
}
]
},
"balanceAvg": {
"value": 28519.04761904762
}
},
{
"key": 25,
"doc_count": 42,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 23,
"balanceAvg": {
"value": 29336.08695652174
}
},
{
"key": "F",
"doc_count": 19,
"balanceAvg": {
"value": 25156.263157894737
}
}
]
},
"balanceAvg": {
"value": 27445.214285714286
}
},
{
"key": 37,
"doc_count": 42,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 23,
"balanceAvg": {
"value": 25015.739130434784
}
},
{
"key": "F",
"doc_count": 19,
"balanceAvg": {
"value": 29451.21052631579
}
}
]
},
"balanceAvg": {
"value": 27022.261904761905
}
},
{
"key": 27,
"doc_count": 39,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 21,
"balanceAvg": {
"value": 21618.85714285714
}
},
{
"key": "M",
"doc_count": 18,
"balanceAvg": {
"value": 21300.38888888889
}
}
]
},
"balanceAvg": {
"value": 21471.871794871793
}
},
{
"key": 38,
"doc_count": 39,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "F",
"doc_count": 20,
"balanceAvg": {
"value": 27931.65
}
},
{
"key": "M",
"doc_count": 19,
"balanceAvg": {
"value": 24350.894736842107
}
}
]
},
"balanceAvg": {
"value": 26187.17948717949
}
},
{
"key": 29,
"doc_count": 35,
"genderAgg": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "M",
"doc_count": 23,
"balanceAvg": {
"value": 29943.17391304348
}
},
{
"key": "F",
"doc_count": 12,
"balanceAvg": {
"value": 28601.416666666668
}
}
]
},
"balanceAvg": {
"value": 29483.14285714286
}
}
]
}
}
}
2.4 映射
2.4.1 查看映射关系
GET http://127.0.0.1:9200/bank/_mapping
{
"bank": {
"mappings": {
"properties": {
"account_number": {
"type": "long"
},
"address": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"age": {
"type": "long"
},
"balance": {
"type": "long"
},
"city": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"email": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"employer": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"firstname": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"gender": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"lastname": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"state": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
}
}
}
}
2.4.2 创建时指定映射
PUT http://127.0.0.1:9200/my_index
{
"mappings": {
"properties": {
"age": {"type": "integer"},
"email": {"type": "keyword"},
"name": {"type": "text"}
}
}
}
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "my_index"
}
2.4.3 添加新字段
PUT http://127.0.0.1:9200/my_index/_mapping
{
"properties": {
"employee-id": {
"type": "keyword",
"index": false
}
}
}
{
"acknowledged": true
}
2.4.4 修改映射
本质:创建一个新的索引,然后进行数据迁移
PUT http://127.0.0.1:9200/my_index2
{
"mappings": {
"properties": {
"account_number": {
"type": "long"
},
"address": {
"type": "text"
},
"age": {
"type": "integer"
},
"balance": {
"type": "long"
},
"city": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"email": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"employer": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"firstname": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"gender": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"lastname": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"state": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
}
}
}
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "my_index2"
}
2.4.5 数据迁移
POST http://127.0.0.1:9200/_reindex
{
"source": {
"index": "my_index",
"type": "table"
},
"dest": {
"index": "my_index3"
}
}
{
"took": 1,
"timed_out": false,
"total": 0,
"updated": 0,
"created": 0,
"deleted": 0,
"batches": 0,
"version_conflicts": 0,
"noops": 0,
"retries": {
"bulk": 0,
"search": 0
},
"throttled_millis": 0,
"requests_per_second": -1.0,
"throttled_until_millis": 0,
"failures": []
}
2.5 分词器
2.5.1 测试分词器
POST http://127.0.0.1:9200/_analyze
{
"analyzer": "standard",
"text": "I am huangzhen,come from China"
}
{
"tokens": [
{
"token": "i",
"start_offset": 0,
"end_offset": 1,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "am",
"start_offset": 2,
"end_offset": 4,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "huangzhen",
"start_offset": 5,
"end_offset": 14,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "come",
"start_offset": 15,
"end_offset": 19,
"type": "<ALPHANUM>",
"position": 3
},
{
"token": "from",
"start_offset": 20,
"end_offset": 24,
"type": "<ALPHANUM>",
"position": 4
},
{
"token": "china",
"start_offset": 25,
"end_offset": 30,
"type": "<ALPHANUM>",
"position": 5
}
]
}
2.5.2 中文分词器
需要安装ik分词器
POST http://127.0.0.1:9200/_analyze
{
"analyzer": "ik_max_word",
"text": "我是中国人"
}
{
"tokens": [
{
"token": "我",
"start_offset": 0,
"end_offset": 1,
"type": "CN_CHAR",
"position": 0
},
{
"token": "是",
"start_offset": 1,
"end_offset": 2,
"type": "CN_CHAR",
"position": 1
},
{
"token": "中国人",
"start_offset": 2,
"end_offset": 5,
"type": "CN_WORD",
"position": 2
},
{
"token": "中国",
"start_offset": 2,
"end_offset": 4,
"type": "CN_WORD",
"position": 3
},
{
"token": "国人",
"start_offset": 3,
"end_offset": 5,
"type": "CN_WORD",
"position": 4
}
]
}
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