1.创立索引
创立一个名为 products 的索引,用来存储商品数据。
分片和正本参数阐明:
number_of_shards
:分片数量,默认值是 5number_of_replicas
:正本数量,默认值是 1
咱们有三个节点,在每个节点上都创立一个分片。每个分片在另两个节点上各创立一个正本。
# 创立索引,命名为 products
PUT /products
{
"settings": {
"number_of_shards": 3,
"number_of_replicas": 2
}
}
2.创立映射
在 products 索引中创立映射。
# 定义mapping,数据结构
PUT /products/_mapping
{
"properties": {
"id": {
"type": "long"
},
"title": {
"type": "text"
},
"category": {
"type": "text"
},
"price": {
"type": "float"
},
"city": {
"type": "text"
},
"barcode": {
"type": "keyword"
}
}
}
查看映射
GET /products/_mapping
映射(数据结构)
相似于数据库表构造,索引数据也被分为多个数据字段,并且须要设置数据类型和其余属性。
映射,是对索引中字段构造的定义和形容。
罕用类型:
-
数字类型:
- byte、short、integer、long
- float、double
- unsigned_long
-
字符串类型:
- text : 会进行分词
- keyword : 不会进行分词,实用于email、主机地址、邮编等
-
日期和工夫类型:
- date
3.增加文档
增加的文档会有一个名为_id
的文档id,这个文档id能够主动生成,也能够手动指定,通常能够应用数据的id作为文档id。
# 增加文档
PUT /products/_doc/10033
{
"id":"10033",
"title":"新一代PLAY:5无线智能音响系统",
"category":"潮酷数码会场",
"price":"3980.01",
"city":"上海",
"barcode":"527848718459"
}
PUT /products/_doc/10034
{
"id":"10034",
"title":" 高清电视盒子wifi 64位硬盘播放器",
"category":"潮酷数码会场",
"price":"398.00",
"city":"浙江杭州",
"barcode":"522994634119"
}
PUT /products/_doc/10035
{
"id":"10035",
"title":" 重低音入耳式防脱降噪音乐耳机",
"category":"潮酷数码会场",
"price":"860.00",
"city":"浙江杭州",
"barcode":"526558749068"
}
PUT /products/_doc/10036
{
"id":"10036",
"title":"2.0无线蓝牙录音师头戴式耳机",
"category":"潮酷数码会场",
"price":"2889.00",
"city":"上海",
"barcode":"37147009748"
}
PUT /products/_doc/10037
{
"id":"10037",
"title":"美国原创WiFi连贯 家庭桌面音箱",
"category":"潮酷数码会场",
"price":"1580.01",
"city":"上海",
"barcode":"527783392239"
}
也能够主动生成 _id
值:
POST /products/_doc
{
"id":"10027",
"title":"vivo X9前置双摄全网通4Gvivox9",
"category":"手机会场",
"price":"2798.00",
"city":"广东东莞",
"barcode":"541396973568"
}
查看文档:
GET /products/_doc/10037`
查看指定文档title字段的分词后果:
GET /products/_doc/10037/_termvectors?fields=title
4.批改文档
底层索引数据无奈批改,批改数据实际上是先删除再从新增加。
两种批改形式:
- PUT:对文档进行残缺的替换
- POST:能够批改一部分字段
批改价格字段的值:
# 批改文档 - 替换
PUT /products/_doc/10037
{
"id":"10037",
"title":"美国原创WiFi连贯 家庭桌面音箱",
"category":"潮酷数码会场",
"price":"9999.99",
"city":"上海",
"barcode":"527783392239"
}
查看文档:
GET /products/_doc/10037
批改价格和城市字段的值:
# 批改文档 - 更新局部字段
POST /products/_update/10037
{
"doc": {
"price":"8888.88",
"city":"深圳"
}
}
查看文档:
GET /products/_doc/10037
5.删除文档
`DELETE /products/_doc/10037`
清空
POST /products/_delete_by_query
{
"query": {
"match_all": {}
}
}
6.删除索引
# 删除 products 索引
DELETE /products
7.复合查问
创立索引
PUT /pditems
{
"settings": {
"number_of_shards": 3,
"number_of_replicas": 2
},
"mappings": {
"properties": {
"id": {
"type": "long"
},
"brand": {
"type": "text"
},
"title": {
"type": "text"
},
"sell_point": {
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"price": {
"type": "float"
},
"image": {
"type": "keyword"
},
"cid": {
"type": "long"
},
"status": {
"type": "byte"
},
"created": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss"
},
"updated": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss"
}
}
}
}
查看数据
搜寻 pditems
索引中全副 3160 条数据:
GET /pditems/_search
{
"query": {
"match_all": {}
},
"size": 3160
}
8.搜寻文档
搜寻所有数据
# 搜寻 pditems 索引中全副数据
POST /pditems/_search
{
"query": {
"match_all": {}
}
}
关键词搜寻
# 查问 pditems 索引中title中蕴含"电脑"的商品
POST /pditems/_search
{
"query": {
"match": {
"title": "电脑"
}
}
}
搜寻后果过滤器
# 价格大于2000,并且title中蕴含"电脑"的商品
POST /pditems/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": "电脑"
}
}
],
"filter": [
{
"range": {
"price": {
"gte": "2000"
}
}
}
]
}
}
}
搜寻后果高亮显示
POST /pditems/_search
{
"query": {
"multi_match":{
"query": "手机",
"fields": ["title", "sell_point"]
}
},
"highlight" : {
"pre_tags" : ["<i class="highlight">"],
"post_tags" : ["</i>"],
"fields" : {
"title" : {},
"sell_point" : {
"pre_tags": "<em>",
"post_tags": "</em>"
}
}
}
}
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