ElasticSearch 插件安装及其搜索略解

时间 2019-11-13

原文原文链接

(1) marvel 远程安装方式： bin/plugin -i elasticsearch/marvel/latesthtml

本地安装方式： wget https://download.elasticsearch.org/elasticsearch/marvel/marvel-latest.zip bin/plugin -i marvel -u file:/home/elasticsearch-1.5.1/marvel-latest.zip 在启动后，能够经过如下方式查看elasticsearch运行状况 http://xxx.xxx.xxx.xxx:8765/_plugin/marvel/java

(2) elasticsearch service [很是喜欢] https://github.com/elastic/elasticsearch-servicewrapper 将service文件放置在elasticsearch bin 目录下 mv elasticsearch-servicewrapper-master/service/ bin/ 配置bin/service/elasticsearch.conf vim bin/service/elasticsearch.conf 按需做以下修改 set.default.ES_HOME=/home/elasticsearch-1.5.1 #替换为实际的elasticsearch路径 wrapper.java.command=/usr/lib/jvm/jre-1.7.0-openjdk.x86_64/bin/java #替换为实际的java二进制文件路径git

(3). ElasticHQ [很是喜欢] http://www.elastichq.org/ bin/plugin -i royrusso/elasticsearch-HQ -u file:/home/elasticsearch-1.5.1/royrusso-elasticsearch-HQ-603ae9e.zipgithub

在启动后，能够经过如下方式查看elasticsearch运行状况 http://xxx.xxx.xxx.xxx:8765/_plugin/HQ/算法

(4) elasticsearch-head [比较喜欢] https://github.com/mobz/elasticsearch-head bin/plugin -i mobz/elasticsearch-head -u file:/home/elasticsarch-1.5.1/elasticsearch-head-master.zip数据库

在启动后，能够经过如下方式查看elasticsearch运行状况 http://xxx.xxx.xxx.xxxx:8765/_plugin/headapache

第四步：启动elasticsearch bin/service/elasticsearch start|stop|console|install|removejson

start 在后台运行elasticsearch stop 中止elasticsearch console 在前台运行elasticsearch install elasticsearch自启动 remove elasticsearch取消自启动vim

2、基本操做app

首先咱们批量导入示例数据——莎士比亚全集（参照http://kibana.logstash.es/content/v3/10-minute-walk-through.html kibana 3指南10分钟入门 wget http://www.elasticsearch.org/guide/en/kibana/3.0/snippets/shakespeare.json

curl -XPUT http://localhost:8765/_bulk --data-binary @shakespeare.json more shakespeare.json 察看存储内容 {"index":{"_index":"shakespeare","_type":"act","_id":0}} {"line_id":1,"play_name":"Henry IV","speech_number":"","line_number":"","speaker":"","text_entry":"ACT I"} {"index":{"_index":"shakespeare","_type":"scene","_id":1}}

接下来咱们来经过与熟悉的关系数据库来对比elasticsearch的数据组成（1）数据组成：元数据+实际数据至关于察看数据库的模式定义 http localhost:8765/shakespeare/ 返回 { "shakespeare": { "mappings": { "act": { "properties": { "line_id": { "type": "long" }, "line_number": { "type": "string" }, "play_name": { "type": "string" }, "speaker": { "type": "string" }, "speech_number": { "type": "long" }, "text_entry": { "type": "string" } } }, "line": { "properties": { "line_id": { "type": "long" }, "line_number": { "type": "string" }, "play_name": { "type": "string" }, "speaker": { "type": "string" }, "speech_number": { "type": "long" }, "text_entry": { "type": "string" } } }, "scene": { "properties": { "line_id": { "type": "long" }, "line_number": { "type": "string" }, "play_name": { "type": "string" }, "speaker": { "type": "string" }, "speech_number": { "type": "long" }, "text_entry": { "type": "string" } } } }, "settings": { "index": { "creation_date": "1429691321987", "number_of_replicas": "1", "number_of_shards": "5", "uuid": "rrCmsKKcSDyLSpLFVnQnbg", "version": { "created": "1040299" } } } } }

咱们用熟悉的关系数据库来进行对比，映射关系以下 elasticsearch RDBS indices 索引 databases数据库 types 类型 tables表 documents文档 rows行 fields 字段 columns列

示例中，索引名为shakespeare（等同于数据库名为shakespeare）类型有3个：act, line, scene （等同于表名为act, line, scene）字段组成（等同于表的结构）字段名字段类型 line_id long line_number string play_name string speaker string speech_number long text_entry string

（2）简单检索示例1：经过index+type+文档_id来察看内容格式：host:port/index_name/type_name/_id http localhost:8108/shakespeare/line/2

结果以下： { "_id": "2", "_index": "shakespeare", "_source": { "line_id": 3, "line_number": "", "play_name": "Henry IV", "speaker": "", "speech_number": "", "text_entry": "Enter KING HENRY, LORD JOHN OF LANCASTER, the EARL of WESTMORELAND, SIR WALTER BLUNT, and others" }, "_type": "line", "_version": 1, "found": true } elasticsearch的数据由两部分组成：文档元数据（例如_id）与文档数据名字说明 _index 相似RDBS的“数据库”概念 _type 相似RDBS的“表”概念 _id 文档的惟一编号 _source 字段里的内容为文档数据（真实存储的数据），咱们可使用以下方法只读取实际数据 http localhost:8108/shakespeare/line/2/_source 结果以下：

{ "line_id": 3, "line_number": "", "play_name": "Henry IV", "speaker": "", "speech_number": "", "text_entry": "Enter KING HENRY, LORD JOHN OF LANCASTER, the EARL of WESTMORELAND, SIR WALTER BLUNT, and others" }

示例2：指定字段field进行搜索，例如搜索play_name字段为Romeo and Juliet http localhost:8108/shakespeare/_search?q=play_name:"Romeo and Juliet" 结果以下（截取部分）： { "_shards": { "failed": 0, "successful": 5, "total": 5 }, "hits": { "hits": [ { "_id": "86748", "_index": "shakespeare", "_score": 3.3792284, "_source": { "line_id": 86749, "line_number": "", "play_name": "Romeo and Juliet", "speaker": "JULIET", "speech_number": 19, "text_entry": "Exeunt" }, "_type": "line" },

（3）复杂搜索 Elasticsearch支持丰富而灵活的查询语言——Query DSL。在学习以前，咱们能够先熟悉一下Lucene查询语法（其实和使用google搜索引擎区别不大）

支持AND，OR，NOT 查询语句"apache AND lucene"的意思是匹配含apache且含lucene的文档。查询表达式"apache OR lucene"可以匹配包含“apache”的文档，也能匹配包含"lucene"的文档，还能匹配同时包含这两个Term的文档。查询表达式“lucene NOT elasticsearch”就只能匹配包含lucene可是不含elasticsearch的文档

支持+, -符号例如：但愿搜索到包含关键词lucene,可是不含关键词elasticsearch的文档，能够用以下的查询表达式："+lucene -elasticsearch"。

支持指定字段名进行搜索（相似RDBS按列名搜索）例如：查询title域中包含关键词elasticsearch的文档，查询表达式以下：title:elasticsearch

支持通配符 ? (匹配单个字符）

(匹配多个字符）注意默认的通配符不能是关键词的首字母

支持~整数符号一个~符号，后面紧跟一个整数，~后面的整数表示短语中可接收的最大的词编辑距离(短语中替换一个词，添加一个词，删除一个词) "writer~2"可以搜索到含writer和writers的文档。 title:"mastering elasticsearch"~2可以搜匹配title域中含"mastering elasticsearch"的文档与包含"mastering book elasticsearch"的文档

支持^符号进行加权boost设置一个^符号后面接一个浮点数表示权重。若是权重小于1，就会下降关键词的重要程度。同理，若是权重大于1就会增长关键词的重要程度。默认的加权值为1

支持区间搜索 price:[10.00 TO 15.00查询price域的值在10.00到15.00之间的全部文档。 price:[10.00 TO 15.00}查询price域中价格在10.00(10.00要可以被搜索到)到15.00(15.00不能被搜索到)之间的文档

特殊字符需转义 +, -, &&, || , ! , (,) , { } , [ ] , ^, " , ~, *, ?, : , , /

更多，Lucene原理（打分算法，TF-IDF算法必定会在搜索中出境）

咱们能够看到elasticsearch支持丰富的数据查询方式，结果展现方式（按什么方式来排序结果，使用什么图形来展现统计结果）（1）关键词查询term （2）短语查询phrase （3）区间range （4）布尔Boolean （5）模糊fuzzy （6）跨度span （7）通配符wildcard （8）地理位置spatial （9）统计aggregation ——这个功能很是很是赞，好比说生成各类统计图表（10）prospective search

搜索语句支持经过URI提交（上面的例子演示的_search?q= 注意，使用这种方式的要遵循url编码,官方参考) ，也支持经过request body提交，简直就是HTTP RESTFULL最佳实践，官方参考

咱们用熟悉的SQL语句来对比实例1： curl -XPOST 'http://localhost:8108/shakespeare/line/_search?pretty' -d ' { "query":{ "match_all": {} }, "sort": {"line_id": {"order": "desc" }}, "size": 1, "from": 10 }' 等同于 use shakespeare; select * from line order by line_id desc limit 10,1 实例2： curl -XPOST 'http://localhost:8108/shakespeare/line/_search?pretty' -d ' { "query":{ "bool":{ "must":[ {"match_phrase": {"text_entry":"question"}},

{"match_phrase": {"text_entry":"not to be"}} ] } } }' 结果

"took" : 253, "timed_out" : false, "_shards" : { "total" : 3, "successful" : 3, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 4.0433946, "hits" : [ { "_index" : "shakespeare", "_type" : "line", "_id" : "34229", "_score" : 4.0433946, "_source":{"line_id":34230,"play_name":"Hamlet","speech_number":19,"line_number":"3.1.64","speaker":"HAMLET","text_entry":"To be, or not to be: that is the question:"} }, { "_index" : "shakespeare", "_type" : "line", "_id" : "1397", "_score" : 4.0004296, "_source":{"line_id":1398,"play_name":"Henry IV","speech_number":152,"line_number":"2.4.392","speaker":"FALSTAFF","text_entry":"blackberries? a question not to be asked. Shall"} } ] } } 等同于 use shakespeare; select * from line where text_entry like "%question%" and text_entry like "%not to be%"

Search APIs Match Query APIs