Elasticsearch入门教程之安装与基本使用

Elasticsearch入门教程之安装与基本使用

ubuntu16.04+elasticsearch6.5为例，参考官网文档.html

安装java

参考文章：

$ sudo apt-get update
$ sudo apt-get install -y default-jre
$ sudo add-apt-repository ppa:webupd8team/java && sudo apt-get update
$ sudo apt-get install oracle-java8-installer
$ export JAVA_HOME="/usr/lib/jvm/java-8-oracle"
$ java -version     #测试java
$ echo $JAVA_HOME   #测试java_home

Elasticsearch

安装(6.5.4)

$ wget .5.4.zip
$ unzip elasticsearch-6.5.4.zip

启动

$ cd elasticsearch-6.5.4/bin
$ ./elasticsearch   

启动时，如果报错vm.maxmapcount [65530] is too low执行下面

$ sudo sysctl -w vm.max_map_count=262144

curl测试，出现以下信息表示启动成功，安装正常

$ curl 127.0.0.1:9200   
{"name" : "c5skAub","cluster_name" : "elasticsearch","cluster_uuid" : "bdkUuVtQSvWOiY_vXEFnvw","version" : {"number" : "6.5.4","build_flavor" : "default","build_type" : "tar","build_hash" : "d2ef93d","build_date" : "2018-12-17T21:17:40.758843Z","build_snapshot" : false,"lucene_version" : "7.5.0","minimum_wire_compatibility_version" : "5.6.0","minimum_index_compatibility_version" : "5.0.0"},"tagline" : "You Know, for Search"
}   

基础概念

Elastic是目前全文搜索引擎的首选，本质上是非关系型数据库，与mysql一些概念对比如下。

Mysql	Elastic
database(数据库)	index(索引)
table(表)	type(类型，7.x将废弃)
row(记录)	document(文档)
column(字段)	fileds(字段)

基本操作

Elastic的操作通过rest api来完成，以下操作都将省去curl -XMETHOD "localhost:9200" -H 'Content-Type: application/json' [-d 'request body']，如果想远程访问，修改/path-to-elastic/l中的network.host: 0.0.0.0后重启即可

操作索引

新建一个名为customer的index，?pretty返回友好的json

$ PUT /customer?pretty  

列出所有索引

$ GET /_cat/indices?v 

删除索引

$ DELETE /customer

操作文档

新建id为1的document，由于type将被废除，所以规定每个index只包含一个type，统一为_doc

$ PUT /customer/_doc/1?pretty
{"name": "luke"
}

如果使用post并且id留空将会生成一个随机的id

$ POST /customer/_doc?pretty {"name": "php"}
{"_index": "customer","_type": "_doc","_id": "hIkkLGgBFVhvdLuiNNGD",  ##返回的id"_version": 1,"result": "created","_shards": {"total": 2,"successful": 1,"failed": 0},"_seq_no": 0,"_primary_term": 3
}

更新文档与新建相同，改变数据即可，或者

$ POST /customer/_doc/1/_update?pretty
{"doc": { "name": "luke44", "age": 24 }
}

使用简单的脚本更新，这里的ctx._source指向将被修改的文档

$ POST /customer/_doc/1/_update?pretty
{"script" : "ctx._source.age += 5"
}

查询id为1的文档

$ GET /customer/_doc/1?pretty
{"_index": "customer","_type": "_doc","_id": "1","_version": 1,"found": true,"_source": {"name": "luke"}
}

删除文档

$ DELETE /customer/_doc/2?pretty

批量操作，批量更新id为1和2的文档，注意在postman中body最后必须空一行

$ POST /customer/_doc/_bulk?pretty
{"index":{"_id":"1"}}
{"name": "luke" }
{"index":{"_id":"2"}}
{"name": "php", "age": "20" }

先更新id为1的文档，然后删除id为2的文档

$ POST /customer/_doc/_bulk?pretty
{"update":{"_id":"1"}}
{"doc":{"name":"php best"}}
{"delete":{"_id":"2"}}

批量操作时其中一个操作失败时，其他操作任然会继续执行，结束时根据执行顺序返回状态。

浏览数据

先准备一个虚拟的银行客户帐户信息数据集，类似这种格式，请右键下载数据集另存为accounts.json

{"account_number": 0,"balance": 16623,"firstname": "Bradshaw","lastname": "Mckenzie","age": 29,"gender": "F","address": "244 Columbus Place","employer": "Euron","email": "bradshawmckenzie@euron","city": "Hobucken","state": "CO"
}

导入数据集

$ POST /bank/_doc/_bulk?pretty&refresh --data-binary "@accounts.json"
$ GET /_cat/indices?v
health status index    uuid                   pri unt docs.deleted store.size pri.store.size
yellow open   bank     3inMmuQzRqaTpMkzfh07_A   5   1       1000            0     95.9kb         95.9kb
yellow open   customer gSRgPG9cScKHcuycJE2drw   5   1          2            0      7.7kb          7.7kb

match_all查询

使用URI搜索，q=*匹配所有，sort=account_number:asc表示按account_number升序排列

$ GET /bank/_search?q=*&sort=account_number:asc&pretty
{"took" : 63,  //耗时，毫秒"timed_out" : false,  //是否超时"_shards" : {     //碎片"total" : 5,"successful" : 5,"skipped" : 0,"failed" : 0},"hits" : {    //命中"total" : 1000,"max_score" : null,"hits" : [ {"_index" : "bank","_type" : "_doc","_id" : "0","sort": [0],"_score" : null,"_source" : {"account_number":0,"balance":16623,"firstname":"Bradshaw","lastname":"Mckenzie","age":29,"gender":"F","address":"244 Columbus Place","employer":"Euron","email":"bradshawmckenzie@euron","city":"Hobucken","state":"CO"}}, {"_index" : "bank","_type" : "_doc","_id" : "1","sort": [1],"_score" : null,"_source" : {"account_number":1,"balance":39225,"firstname":"Amber","lastname":"Duke","age":32,"gender":"M","address":"880 Holmes Lane","employer":"Pyrami","email":"amberduke@pyrami","city":"Brogan","state":"IL"}}, ...]}
}

使用json请求体搜索，获取跟上面相同的效果

$ GET /bank/_search
{"query": { "match_all": {} },"sort": [{ "account_number": "asc" }]
}

使用size和from限制结果条数，类似mysql的limit和from；使用_source查询指定字段

$ GET /bank/_search
{"query": { "match_all": {} },"sort": { "balance": { "order": "desc" } },"from": 10,"size": 15,    //默认10"_source": ["account_number", "balance"]
}

match查询

查询account_number为20的所有账户

$ GET /bank/_search
{"query": { "match": { "account_number": 20 } }
}

查询address中包含mill单词的所有账户

$ GET /bank/_search
{"query": { "match": { "address": "mill" } }
}

查询address中包含mill或者lane单词的所有账户

$ GET /bank/_search
{"query": { "match": { "address": "mill lane" } }
}

match_phrase查询，match的变种，查询address中包含mill lane的所有账户

$ GET /bank/_search
{"query": { "match_phrase": { "address": "mill lane" } }
}

bool查询

查询address中包含mill和lane单词的所有账户，bool must子句指定所有必须为true的查询才能将文档视为匹配项

$ GET /bank/_search
{"query": {"bool": {"must": [{ "match": { "address": "mill" } },{ "match": { "address": "lane" } }]//"should": [...] 或查询//"must_not": [...] 都不是}}
}

组合查询，查询年龄为40并且不住在ID省的客户账户

$ GET /bank/_search
{"query": {"bool": {"must": [{ "match": { "age": "40" } }],"must_not": [{ "match": { "state": "ID" } }]}}
}

bool过滤器

查询余额在20000到30000(包含)的客户账户

$ GET /bank/_search
{"query": {"bool": {"must": { "match_all": {} },"filter": {"range": {"balance": {"gte": 20000,"lte": 30000}}}}}
}

Elasticsearch是一个既简单又复杂的工具。以上，已经了解了它的基础知识，如何查看它，以及如何使用一些REST API来处理它，以后再慢慢了解一些更高级的知识点。