1.基础操作
#查看所有的索引(也可以查看文档中的数据量)
GET /_cat/indices
yellow open users_20210827 EWNcM5rSQs64W-UyiWX_-w 5 2 979701 18786 597.2mb 597.2mb
yellow open test1 MUSajDCtQPq5F6bM_G7TTw 1 1 0 0 208b 208b
PUT保存一个索引(更新也可以)
PUT test1
#必须带ID
PUT test1/external/1
{
"name" : "张三"
}
#结果
{
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 2
}
#如果继续点击put方法，就变成了保存
#结果
{
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"_version" : 2, #版本增加了
"result" : "updated",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 1,
"_primary_term" : 2
}
put修改需要注意的是，修改的值如果是单独的字段值，会把其余的字段置为空
GET my_index/_search
#结果
{
"took" : 973,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "user",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name.keyword" : "李四", #目前库里有name和age两个值
"age" : 20
}
}
]
}
}
#修改name为张三
PUT my_index/user/1
{
"name.keyword" : "张三"
}
#结果
{
"took" : 658,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "user",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name.keyword" : "张三" #年龄字段消失了
}
}
]
}
}
==建议==修改需要用post
POST my_index/user/1/_update
{
"doc":{
"name.keyword" : "张三"
}
}
#结果
{
"took" : 99,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "user",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name.keyword" : "张三",
"age" : 20
}
}
]
}
}
POST保存一个索引
POST test1/external
{
"name" : "李四"
}
#结果
{
"_index" : "test1",
"_type" : "external",
"_id" : "xJUkl3wBNEMeGuMKEcKb",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 3,
"_primary_term" : 2
}
#post是一个新增操作，重复点击，添加记录
{
"_index" : "test1",
"_type" : "external",
"_id" : "x5Ukl3wBNEMeGuMK7cJZ",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 6,
"_primary_term" : 2
}
#如果post后面也带id，那么重复点击也是保存
POST test1/external/1
{
"name" : "李四"
}
{
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"_version" : 3,
"result" : "updated",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 7,
"_primary_term" : 2
}
查询文档
GET test1/external/1
{
"_index" : "test1", #索引名称
"_type" : "external", #类型
"_id" : "1", #记录ID
"_version" : 3, #版本号
"_seq_no" : 7, #并发控制字段，每次更新+1，用来做乐观锁
"_primary_term" : 2, #主分片重新分配，如果重启，就会变化
"found" : true,
"_source" : {
"name" : "李四"
}
}
更新文档
_update
POST test1/external/1/_update
{
"doc":{
"name" : "李四1"
}
}
#_update更新重复点击，数据会对比原数据，如果一样，不更新，版本号(_version)和序列号(_seq_no)都不会变更
#结果
{
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"_version" : 4,
"result" : "noop",
"_shards" : {
"total" : 0,
"successful" : 0,
"failed" : 0
},
"_seq_no" : 8,
"_primary_term" : 2
}
POST
POST test1/external/1
{
"name" : "李四2"
}
#重复点击，版本号(_version)和序列号(_seq_no)都会增加,重复更新
#结果
{
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"_version" : 5,
"result" : "updated",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 9,
"_primary_term" : 2
}
PUT
PUT test1/external/1
{
"name" : "李四3"
}
#重复点击，版本号(_version)和序列号(_seq_no)都会增加,重复更新
#结果
{
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"_version" : 6,
"result" : "updated",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 10,
"_primary_term" : 2
}
删除文档和索引
#删除文档
DELETE test1/external/1
{
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"_version" : 13,
"result" : "deleted",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 17,
"_primary_term" : 3
}
#查询1号id的数据，显示没找到
{
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"found" : false
}
#删除索引
DELETE test1
{
"acknowledged" : true
}
bulk 批量操作
POST test1/a/_bulk
{"index":{"_id":1}}
{"name":"zhangsan"}
{"index":{"_id":2}}
{"name":"lisi"}
#结果
{
"took" : 940,
"errors" : false,
"items" : [
{
"index" : {
"_index" : "test1",
"_type" : "external",
"_id" : "1",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 1,
"status" : 201
}
},
{
"index" : {
"_index" : "test1",
"_type" : "external",
"_id" : "2",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 1,
"_primary_term" : 1,
"status" : 201
}
}
]
}
2.查询
查看分词
GET my_index/_analyze
{
"text" : "张三"
}
#结果
{
"tokens" : [
{
"token" : "张",
"start_offset" : 0,
"end_offset" : 1,
"type" : "",
"position" : 0
},
{
"token" : "三",
"start_offset" : 1,
"end_offset" : 2,
"type" : "",
"position" : 1
}
]
}
match_all(匹配所有)
GET bank/_search
{
"query": {"match_all": {}},
"sort": [
{
"account_number": "asc" #两种写法
}
]
}
#可以多个排序
GET bank/_search
{
"query": {"match_all": {}},
"sort": [
{
"account_number": {
"order": "asc"
},
"balance": {
"order": "desc"
}
}
]
}
#结果打印
{
"took" : 13,
"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" : "0",
"_score" : null,
"_source" : {
"account_number" : 0,
"balance" : 16623,
"firstname" : "Bradshaw",
"lastname" : "Mckenzie",
"age" : 29,
"gender" : "F",
"address" : "244 Columbus Place",
"employer" : "Euron",
"email" : "[email protected]",
"city" : "Hobucken",
"state" : "CO"
},
"sort" : [
0
]
},
...
]
}
}
获取具体的字段
GET bank/_search
{
"query": {
"match_all": {}
},
"_source": ["lastname", "address"]
}
#结果打印
{
...
"hits" : {
...
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"address" : "880 Holmes Lane",
"lastname" : "Duke"
}
},
...
]
}
}
#另一种
GET bank/_search
{
"query": {
"match_all": { }
},
"fields": [
"account_number","lastname"
]
}
#结果打印
{
...
"hits" : {
...
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "1",
"_score" : 1.0,
"fields" : {
"account_number" : [
1
],
"lastname" : [
"Duke"
]
}
},
...
]
}
}
基本分页
GET bank/_search
{
"query": {
"match_all": {}
},
"from": 5,
"size": 5
}
match(精确匹配)
GET bank/_search
{
"query": {
"match": {
"address": "Holmes"
}
}
}
#结果打印
{
...
"hits" : {
...
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "1",
"_score" : 6.501515,
"_source" : {
"account_number" : 1,
"balance" : 39225,
"firstname" : "Amber",
"lastname" : "Duke",
"age" : 32,
"gender" : "M",
"address" : "880 Holmes Lane",
"employer" : "Pyrami",
"email" : "[email protected]",
"city" : "Brogan",
"state" : "IL"
}
}
]
}
}
==如果类型设置为keyword，必须得精确匹配，不然检索不到数据==
image-20211020145627369.png
match_phrase(短语匹配)
#将需要匹配的值当成一个整体单词(不分词)进行检索（包含短语）
GET bank/_search
{
"query":{
"match_phrase":{
"address":"mill road"
}
}
}
#另一种办法（用keyword的意思是地址就是mill road,等同于mysql中的name='北京'）
GET bank/_search
{
"query":{
"match":{
"address.keyword":"mill road"
}
}
}
multi_match(多字段匹配-----类似mysql的or)
#state或者address包含mill的
GET bank/_search
{
"query":{
"multi_match":{
"query":"mill",
"fields":["state", "address"]
}
}
}
#结果
{
"took" : 143,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : 5.4032025,
"hits" : [
{
"_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" : "[email protected]",
"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" : "[email protected]",
"city" : "Urie",
"state" : "IL"
}
}
]
}
}
bool(复合查询)
#并且的关系（gender=F and employer=Comverges and age != 30）
{
"query": {
"bool": {
"must" : [
{
"match": {
"gender": "F"
}
},
{
"match": {
"employer": "Comverges"
}
}
],
"must_not": [
{
"match": {
"age": "30"
}
}
],
"should":[ #应该有Li，没有也能查出来，只是有Li的_score分值高
{
"match": {
"lastname": "Li"
}
}
]
}
}
}
#范围查询
GET bank/_search
{
"query": {
"bool": {
"must": [
{
"range": {
"age": {
"gte": 30,
"lte": 40
}
}
},
{
"match": {
"address": "mill"
}
}
]
}
}
}
filter(过滤)
GET bank/_search
{
"query": {
"bool": {
"filter": [
{
"range": {
"age": {
"gte": 30,
"lte": 40
}
}
},
{
"match": {
"address": "mill"
}
}
]
}
}
}
#结果
{
...
"hits" : {
...
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "136",
"_score" : 0.0, #filter查询完，相关性得分为0
"_source" : {
"account_number" : 136,
"balance" : 45801,
"firstname" : "Winnie",
"lastname" : "Holland",
"age" : 38,
"gender" : "M",
"address" : "198 Mill Lane",
"employer" : "Neteria",
"email" : "[email protected]",
"city" : "Urie",
"state" : "IL"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "345",
"_score" : 0.0,
"_source" : {
"account_number" : 345,
"balance" : 9812,
"firstname" : "Parker",
"lastname" : "Hines",
"age" : 38,
"gender" : "M",
"address" : "715 Mill Avenue",
"employer" : "Baluba",
"email" : "[email protected]",
"city" : "Blackgum",
"state" : "KY"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "472",
"_score" : 0.0,
"_source" : {
"account_number" : 472,
"balance" : 25571,
"firstname" : "Lee",
"lastname" : "Long",
"age" : 32,
"gender" : "F",
"address" : "288 Mill Street",
"employer" : "Comverges",
"email" : "[email protected]",
"city" : "Movico",
"state" : "MT"
}
}
]
}
}
term(和match功能差不多，是包含操作，不是等值操作)
#和match一样，匹配某个属性的值，全文检索字段用match，其他非text(全文检索)字段匹配用term
#term 查询对于查找单个值非常有用，但通常我们可能想搜索多个值。 如果我们想要查找价格字段值为 $20 或 $30 的文档(注意s)
"query" : {
"bool" : {
"filter" : {
"terms" : {
"age" : [20, 38]
}
}
}
}
highlight（高亮搜索）
GET bank/_search
{
"query":{
"match_phrase":{
"address":"mill road"
}
},
"highlight": {
"fields": {
"address" : {}
}
}
}
image-20211020153900644.png
自定义高亮样式
image-20211020162634416.png
aggregations(聚合)
#搜索address中包含mill的所有人的年龄分布以及平均年龄
GET bank/_search
{
"query": {
"match": {
"address": "mill"
}
},
"aggs": { #aggs和aggregations可以，别的名称不行
"ageAgg": { #自定义名称
"terms": {
"field": "age",
"size" : 10 #取10条
}
}
}
}
//年龄分布的结果
{
"took" : 6,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : 5.4032025,
"hits" : [
{
"_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" : "[email protected]",
"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" : "[email protected]",
"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" : "[email protected]",
"city" : "Blackgum",
"state" : "KY"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "472",
"_score" : 5.4032025,
"_source" : {
"account_number" : 472,
"balance" : 25571,
"firstname" : "Lee",
"lastname" : "Long",
"age" : 32,
"gender" : "F",
"address" : "288 Mill Street",
"employer" : "Comverges",
"email" : "[email protected]",
"city" : "Movico",
"state" : "MT"
}
}
]
},
"aggregations" : {
"ageAgg" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : 38, #年龄38的有两个
"doc_count" : 2
},
{
"key" : 28, #年龄28的有一个
"doc_count" : 1
},
{
"key" : 32, #年龄32的有一个
"doc_count" : 1
}
]
}
}
}
image-20211020103545045.png
如果不想看命中结果数据可以设置size为0
image-20211020104055949.png
按照年龄段聚合，并且请求这些年龄段的人的平均薪资(==基于上一次的聚合结果继续字聚合==)
image-20211020105039170.png
查出所有年龄分布，并且这些年龄段的性别中为M的平均薪资和性别为F的平均薪资以及这个年龄段的总体平均薪资
image-20211020111801365.png
实例
#Is not null 不为空
//mysql查询返回某个字段为空值的结果写法是select * from 表名 where 字段名 is not null and where channel_level in("P3", "P2", "P1");
#在elasticsearch中查询语句为
#http://10.3.232.11:8000/users/_search
{
"query":{
"bool":{
"must":[
{
"exists":{
"field":"solution_id"
}
}
],
"filter":[
{
"terms":{
"channel_level":[
"P3",
"P2",
"P1"
]
}
}
]
}
}
}
#is null 为空
//mysql查询返回某个字段为空值的结果写法是select * from 表名 where 字段名 is null
#在elasticsearch中查询语句为
#http://10.3.232.11:8000/users/_search
{
"query":{
"bool":{
"must_not":[
{
"exists":{
"field":"solution_id"
}
}
],
"filter":[
{
"terms":{
"channel_level":[
"P3",
"P2",
"P1"
]
}
}
]
}
}
}
#Where code=xxx orwhere name=xxx
{
"query": {
"bool": {
"filter": [
{
"term": {
"cycle_id": 89
}
},
{
"multi_match": {
"query": "张三",
"fields": [
"name",
"code"
]
}
}
]
}
}
}
3.映射
查看索引的映射
GET users_20210827/_mapping
image-20211020140718707.png
创建映射
PUT /my_index
{
"mappings": {
"properties": {
"age" : {
"type" : "integer"
},
"name":{
"type":"keyword"
},
"email":{
"type": "text"
}
}
}
}
image-20211020140557227.png
添加新的字段映射
PUT /my_index/_mapping
{
"properties":{
"user_id":{
"type":"keyword",
"index":false #默认index都是true，表示当前字段可以被检索，如果为false，代表这个字段不可被检索，
}
}
}
image-20211020141222474.png
更新映射
对于已经存在的映射字段，我们不能更新，更新必须创建新的索引进行==数据迁移==
数据迁移
#目的：修改bank索引中的一些字段类型，因为无法更新，所以只能迁移
#创建新的new_bank索引，然后执行bank和new_bank的数据迁移
PUT new_bank/_mapping
{
"properties" : {
"account_number" : {
"type" : "long"
},
"address" : {
"type" : "text"
},
"age" : {
"type" : "long"
},
"balance" : {
"type" : "long"
},
"city" : {
"type" : "text"
},
"email" : {
"type" : "text"
},
"employer" : {
"type" : "text"
},
"firstname" : {
"type" : "text"
},
"gender" : {
"type" : "text"
},
"lastname" : {
"type" : "text"
},
"state" : {
"type" : "text"
}
}
}
#数据迁移(es6.0以后这么操作，因为6.0以后没有类型)
POST _reindex
{
"source":{
"index":"twitter"
},
"dest":{
"index":"new_twitter"
}
}
#数据迁移(如果当前的es库里有类型，需要按下面的方式迁移)
POST _reindex
{
"source":{
"index":"bank",
"type" : "account"
},
"dest":{
"index":"new_bank"
}
}
image-20211020143455898.png
迁移完成的数据类型变成_doc，老数据也可以完成迁移了