ES基础-基于Kibana增删改查
ElasticSearch增删改查
#创建索引
PUT shopping
#查看索引
GET shopping/_mapping
#产看所有信息
GET _cat/indices?v
#删除索引
DELETE employee
#创建文档添加数据
POST shopping/_doc
{
"title":"小米手机",
"category":"小米",
"images":"http://wwww.xiaomi.com",
"price":119999
}
#创建文档添加数据 带id
POST shopping/_doc/1002
{
"title":"小米手机",
"category":"小米",
"images":"http://wwww.xiaomi.com",
"price":"1999"
}
#创建文档添加数据 带id
POST shopping/_create/1003
{
"title":"小米手机",
"category":"小米",
"images":"http://wwww.xiaomi.com",
"price":"19999"
}
#创建文档添加数据 带id
PUT shopping/_create/1005
{
"title":"小米手机",
"category":"华为",
"images":"http://wwww.xiaomi.com",
"price":"19999"
}
#全量数据更新
PUT shopping/_doc/1001
{
"title":"小米手机",
"category":"小米",
"images":"http://wwww.xiaomi.com",
"price":"4999"
}
#局部数据更新
POST shopping/_update/1002
{
"doc":{
"title":"华为手机"
}
}
#产看指定id信息
GET shopping/_doc/1002
#产看所有信息
GET shopping/_search
#条件查询
GET shopping/_search?q=category:小米
GET shopping/_search
{
"query": {
"match": {
"category": "小米"
}
}
}
#不添加条件查询所有数据
GET shopping/_search
{
"query": {
"match_all": {}
}
}
#分页查询 (页码-1 * 每页数据条数)
GET shopping/_search
{
"query": {
"match_all": {
}
},
"from": 0,
"size": 2
}
#分页查询查询指定字段
GET shopping/_search
{
"query": {
"match_all": {
}
},
"from": 0,
"size": 2,
"_source": "title"
}
#对查询结果排序
GET shopping/_search
{
"query": {
"match_all": {
}
},
"from": 0,
"size": 2,
"_source": "title",
"sort": [
{
"category": {
"order": "desc"
}
}
]
}
#针对报错：Text fields are not optimised for operations that require per-document field data like aggregations and sorting, so these operations are #disabled by default. Please use a keyword field instead. Alternatively, set fielddata=true on [category] in order to load field data by uninverting the #inverted index. Note that this can use significant memory #经过查证是字段category类型为Text格式，然后涉及到了聚合排序等功能。没有进行优化，也类似没有加索引。没有优化的字段es默认是禁止聚合/排序操作的。所以需要将要聚合的字段添加优化。如下操作
PUT shopping/_mapping
{
"properties": {
"category": {
"type": "text",
"fielddata": true
}
}
}
PUT shopping/_mapping
{
"properties": {
"price": {
"type": "text",
"fielddata": true
}
}
}
#多条件查询 must 是必须相当and
#1
GET shopping/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"category": "小米"
}
}
]
}
}
}
#2
GET shopping/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"category": "小米"
}
},
{
"match": {
"price": "1999"
}
}
]
}
}
}
#多条件查询 should 可以是---也可以是---必须相当or
GET shopping/_search
{
"query": {
"bool": {
"should": [
{
"match": {
"category": "小米"
}
},
{
"match": {
"category": "华为"
}
}
]
}
}
}
#多条件查询 范围查询 gt 大于 lt 小于
GET shopping/_search
{
"query": {
"bool": {
"should": [
{
"match": {
"category": "小米"
}
},
{
"match": {
"category": "华为"
}
}
],
"filter": {
"range": {
"price": {
"gt": 1999,
"lt": 20000
}
}
}
}
}
}
#全文检索 （match会将es查询内容进行分词检索查询）
GET shopping/_search
{
"query": {
"match": {
"category": "小华"
}
}
}
#全文检索 （通过highlight 对查询的结果对category进行 高亮显示）
GET shopping/_search
{
"query": {
"match_phrase": {
"category": "小米"
}
},
"highlight": {
"fields": {
"category": {}
}
}
}
#聚合操作 (aggs：聚合操作；price_group ：查询结果名称，随意起名；terms：分组；field：分组字段 )
GET shopping/_search
{
"aggs": {
"price_group": {
"terms": {
"field": "price"
}
}
}
}
#聚合操作 (size : 0 不显示原始数据只显示聚合结果)
GET shopping/_search
{
"aggs": {
"price_group": {
"terms": {
"field": "price"
}
}
},
"size": 0
}
##
#聚合操作 (平均值)
GET shopping/_search
{
"aggs": {
"price_avg": {
"avg": {
"field": "price"
}
}
},
"size": 0
}
#--------------------------------------------------------------------------- #报错 ：Field [price] of type [text] is not supported for aggregation [avg] #解决办法如下 GET shopping/_mapping
PUT shopping1 PUT shopping1/_mapping {
"properties" : {
"category" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"images" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"price" : {
"type" : "long"
},
"title" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
POST _reindex
{
"source": {
"index": "shopping"
},
"dest": {
"index": "shopping1"
}
}
DELETE shopping
POST _reindex
{
"source": {
"index": "shopping1"
},
"dest": {
"index": "shopping"
}
}
DELETE shopping1
#--------------------------------------------------------------
#映射关系
#先创建一个user 索引
PUT user
#创建映射关系
PUT user/_mapping
{
"properties":{
"name":{
"type":"text",
"index":true
},
"sex":{
"type":"keyword",
"index":true
},
"tel":{
"type":"keyword",
"index":false
}
}
}
#查看user的映射关系
GET user/_mapping
#插入一条数据
PUT user/_create/1001
{
"name":"嚣张的小张",
"sex":"男的",
"tel":123123121231111
}
#全局查询 （name类型为text 可以分词查询）
GET user/_search
{
"query": {
"match": {
"name": "小"
}
}
}
#全局查询 （sex类型为keyword 为关键字，不能够 被分开）
GET user/_search
{
"query": {
"match": {
"sex": "男"
}
}
}
#全局查询 （tel 为关键字，不能被索引，所以不能被查询）
GET user/_search
{
"query": {
"match": {
"tel": "123"
}
}
}