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应用 Laradock 装置 ElasticSearch
- ElasticSearch 可视化工具 ElasticHQ / 官网地址
装置和应用
- 应用
docker-compose up命令运行ElasticSearch容器
docker-compose up -d elasticsearch
- 关上浏览器并通过端口
9200拜访本地主机 http://localhost:9200
默认用户是 user，默认明码是 changeme
如果是在 laradock 中应用时
curl http://elasticsearch:9200
装置 ElasticSearch 插件
# 装置一个 ElasticSearch 插件
docker-compose exec elasticsearch /usr/share/elasticsearch/bin/elasticsearch-plugin install {plugin-name}
# 重启容器
docker-compose restart elasticsearch
装置 elasticsearch-analysis-ik 中文分词插件
比方，此时须要装置 elasticsearch-analysis-ik 中文分词插件，须要下载 ik 的 releases 源码 zip 包
# 形式 1，你能够间接在 elasticsearch 容器外，执行以下命令
docker-compose exec elasticsearch /usr/share/elasticsearch/bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.9.1/elasticsearch-analysis-ik-7.9.1.zip
# 形式 2，你能够间接进入到 elasticsearch 容器内，而后执行以下命令
./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.9.1/elasticsearch-analysis-ik-7.9.1.zip
须要留神的是：如果你的 elasticsearch 的版本是 7.9.1 那么，你装置的 ik 插件也必须是 7.9.1 的版本 ，elasticsearch 的版本号能够通过拜访 http://localhost:9200/ 查看 version.number 字段查看，而后 docker-compose restart elasticsearch 重启 elasticsearch 容器即可
装置 elasticsearch-analysis-ik 过程如下所示
[root@f1831cb3b4dd elasticsearch]# ./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.9.1/elasticsearch-analysis-ik-7.9.1.zip
-> Installing https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.9.1/elasticsearch-analysis-ik-7.9.1.zip
-> Downloading https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.9.1/elasticsearch-analysis-ik-7.9.1.zip
[=================================================] 100%??
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
@ WARNING: plugin requires additional permissions @
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
* java.net.SocketPermission * connect,resolve
See http://docs.oracle.com/javase/8/docs/technotes/guides/security/permissions.html
for descriptions of what these permissions allow and the associated risks.
Continue with installation? [y/N]y
-> Installed analysis-ik
[root@f1831cb3b4dd elasticsearch]# ./bin/elasticsearch-plugin list
analysis-ik
查看插件列表
./bin/elasticsearch-plugin list
ElasticSearch 和 mysql 数据库的概念比照
| MySQL | Elasticsearch |
|---|---|
| 表（Table） | 索引（Index） |
| 记录（Row） | 文档（Document） |
| 字段（Column） | 字段（Fields） |
ElasticSearch 的简略应用
新建索引 index（创立表）
curl -XPUT http://localhost:9200/test_index
# 在 Elasticsearch 的返回中如果蕴含了 "acknowledged" : true, 则代表申请胜利。{"acknowledged":true,"shards_acknowledged":true,"index":"test_index"}
查看
curl http://localhost:9200/test_index
{"test_index":{"aliases":{},"mappings":{},"settings":{"index":{"creation_date":"1617069458624","number_of_shards":"1","number_of_replicas":"1","uuid":"XKjqatZTSOu9I_PiwzaNOQ","version":{"created":"7090199"},"provided_name":"test_index"}}}}
# 能够加上 pretty 参数，返回比拟人性化的构造
curl http://localhost:9200/test_index\?pretty
{
"test_index" : {"aliases" : {},
"mappings" : { },
"settings" : {
"index" : {
"creation_date" : "1617069458624",
"number_of_shards" : "1",
"number_of_replicas" : "1",
"uuid" : "XKjqatZTSOu9I_PiwzaNOQ",
"version" : {"created" : "7090199"},
"provided_name" : "test_index"
}
}
}
}
创立类型
对应的接口地址是 /{index_name}/_mapping
curl -H'Content-Type: application/json' -XPUT http://localhost:9200/test_index/_mapping?pretty -d'{"properties": {"title": {"type":"text","analyzer":"ik_smart"},"description": {"type":"text","analyzer":"ik_smart"},"price": {"type":"scaled_float","scaling_factor": 100}
}
}'
# 会返回
{"acknowledged" : true}
curl -H'Content-Type: application/json' -XPUT http://localhost:9200/products/_mapping/?pretty -d'{"properties": {"brand_id": {"type":"integer"},"type": {"type":"integer"},"title": {"type":"text","analyzer":"ik_smart"},"unit": {"type":"keyword"},"sketch": {"type":"text","analyzer":"ik_smart"},"keywords": {"type":"text","analyzer":"ik_smart"},"tags": {"type":"keyword"},"barcode": {"type":"keyword"},"price": {"type":"scaled_float","scaling_factor": 100},"market_price": {"type":"scaled_float","scaling_factor": 100},"rating": {"type":"float"},"sold_count": {"type":"integer"},"review_count": {"type":"integer"},"virtual_retail_num": {"type":"integer"},"description": {"type":"text","analyzer":"ik_smart"},"stock": {"type":"integer"},"warning_stock": {"type":"integer"},"main_image": {"type":"keyword"},"slider_image": {"type":"keyword"},"status": {"type":"integer"},"is_hot": {"type":"integer"},"sort": {"type":"integer"},"categories": {"type":"nested","properties": {"id": {"type":"integer","copy_to":"categories_id"},"pid": {"type":"integer"},"name": {"type":"text","analyzer":"ik_smart","copy_to":"categories_name"},"description": {"type":"text","analyzer":"ik_smart","copy_to":"categories_description"},"status": {"type":"integer"},"level": {"type":"integer"},"img": {"type":"keyword"}
}
},
"brand": {
"type": "nested",
"properties": {"id": { "type": "integer"},
"name": {"type": "text", "analyzer": "ik_smart", "copy_to": "brand_name"},
"description": {"type": "text", "analyzer": "ik_smart", "copy_to": "brand_description"},
"log_url": {"type": "keyword"},
"img": {"type": "keyword"}
}
},
"attrs": {
"type": "nested",
"properties": {"id": { "type": "integer"},
"name": {"type": "keyword", "copy_to": "attrs_name"}
}
},
"skus": {
"type": "nested",
"properties": {"id": { "type": "integer"},
"name": {"type": "text", "analyzer": "ik_smart"},
"main_url": {"type": "keyword"},
"price": {"type": "scaled_float", "scaling_factor": 100},
"sold_count": {"type": "integer"}
}
}
}
}'
- 提交数据中的
properties代表这个索引中各个字段的定义，其中 key 为字段名称，value 是字段的类型定义 -
type定义了字段的数据类型，罕用的有text/integer/date/boolean，还有更多类型keyword，这是字符串类型的一种，这种类型是通知 Elasticsearch 不须要对这个字段做分词，通常用于邮箱、标签、属性等字段。scaled_float代表一个小数位固定的浮点型字段，与 Mysql 的 decimal 类型相似。scaling_factor用来指定小数位精度，100 就代表准确到小数点后两位。nested代表这个字段是一个简单对象，由下一级的 properties 字段定义这个对象的字段。
analyzer是一个新的概念，这是通知 Elasticsearch 应该用什么形式去给这个字段做分词，这里咱们用了ik_smart，是一个中文分词器。copy_to，Elasticsearch 的多字段匹配查问是不反对查问 Nested 对象的字段，然而咱们又必须查问categories.name字段，因而咱们能够应用copy_to参数，能够将categories.name字段复制到下层，咱们就能够通过categories_name字段做多字段匹配查问
创立文档
对应的接口地址是 /{index_name}/_doc/{id} 这里的 id 和 mysql 中的 id 不一样，不是自增的，须要咱们手动指定。
# 创立 id 为 1 的文档
curl -H'Content-Type: application/json' -XPUT http://localhost:9200/test_index/_doc/1?pretty -d'{"title":"iPhone 7P","description":"iphone 第一批双摄像头 ","price": 6799}'
# 会返回如下内容
{
"_index" : "test_index",
"_type" : "_doc",
"_id" : "1",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 2
}
# 创立 id 为 2 的文档
curl -H'Content-Type: application/json' -XPUT http://localhost:9200/test_index/_doc/2?pretty -d'{"title":"OPPO find x","description":" 高清像素 ","price": 3499}'
# 会返回如下内容
{
"_index" : "test_index",
"_type" : "_doc",
"_id" : "2",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 1,
"_primary_term" : 2
}
读取文档数据
curl http://localhost:9200/test_index/_doc/1\?pretty
# 会返回如下内容
{
"_index" : "test_index",
"_type" : "_doc",
"_id" : "1",
"_version" : 1,
"_seq_no" : 0,
"_primary_term" : 2,
"found" : true,
"_source" : {
"title" : "iPhone 7P",
"description" : "iphone 第一批双摄像头",
"price" : 6799
}
}
查看 Elasticsearch 索引中有多少条数据
对应的接口地址为 /{index_name}/_doc/_count
curl http://localhost:9200/test_index/_doc/_count\?pretty
# 会返回如下内容
{
"count" : 3,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
}
}
简略搜寻
curl -XPOST -H'Content-Type:application/json' http://localhost:9200/test_index/_doc/_search\?pretty -d'{"query": {"match": {"description":"iphone"}}
}'
# 会返回如下内容
{
"took" : 16,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 0.60996956,
"hits" : [
{
"_index" : "test_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 0.60996956,
"_source" : {
"title" : "iPhone 7P",
"description" : "iphone 第一批双摄像头",
"price" : 6799
}
}
]
}
}
原文链接地址
正文完
