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,resolveSee http://docs.oracle.com/javase/8/docs/technotes/guides/security/permissions.htmlfor 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 listanalysis-ik查看插件列表
./bin/elasticsearch-plugin listElasticSearch 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