ElasticSearch
1. 什么是RestFul
REST
: 表现层状态转化(Representational State Transfer)，如果一个架构符合REST原则，就称它为 RESTful 架构风格。
资源
: 所谓”资源”，就是网络上的一个实体，或者说是网络上的一个具体信息
表现层
:我们把”资源”具体呈现出来的形式，叫做它的”表现层”(Representation)。状态转化(State Transfer):如果客户端想要操作服务器，必须通过某种手段，让服务器端发生”状态转 化”(State Transfer)。而这种转化是建立在表现层之上的，所以就是”表现层状态转化”。
REST原则就是指一个URL代表一个唯一资源，并且通过HTTP协议里面四个动词:GET、POST、PUT、DELETE对应四种服务器端的基本操作: GET用来获取资源，POST用来添加资源(也可以用于更新资源)，PUT用来更新资源，DELETE用来删除资源。
2. 什么是全文检索
全文检索是计算机程序通过扫描文章中的每一个词，对每一个词建立一个索引，指明该词在文章中出现的次数和位置。当用户查询时根据建立的索引查找，类似于通过字典的检索字表查字的过程。
全文检索（Full-Text Retrieval(检索)）以文本作为检索对象，找出含有指定词汇的文本。
全面、准确和快速是衡量全文检索系统的关键指标。
关于全文检索，我们要知道：
1. 只处理文本。
2. 不处理语义。
3. 搜索时英文不区分大小写。
4. 结果列表有相关度排序。
3. 什么是ElasticSearch
ElasticSearch
简称
ES
，
是基于Apache Lucene构建的开源搜索引擎，是当前流行的企业级搜索引擎
。Lucene本身就可以被认为迄今为止性能最好的一款开源搜索引擎工具包，但是lucene的API相对复杂，需要深厚的搜索理论。很难集成到实际的应用中去。
同时ES是采用java语言编写，提供了简单易用的RestFul API，开发者可以使用其简单的RestFul API，开发相关的搜索功能，从而避免lucene的复杂性
。
4. ES的诞生
多年前，一个叫做Shay Banon的刚结婚不久的失业开发者，由于妻子要去伦敦学习厨师，他便跟着也去了。在他找工作的过程中，为了给妻子构建一个食谱的搜索引擎，他开始构建一个早期版本的Lucene。
直接基于Lucene工作会比较困难，所以Shay开始抽象Lucene代码以便Java程序员可以在应用中添加搜索功能。他发布了他的第一个开源项目，叫做“Compass”。
后来Shay找到一份工作，这份工作处在高性能和内存数据网格的分布式环境中，因此高性能的、实时的、分布式的搜索引擎也是理所当然需要的。然后他决定重写Compass库使其成为一个独立的服务叫做Elasticsearch。
第一个公开版本出现在2010年2月，在那之后Elasticsearch已经成为Github上最受欢迎的项目之一，代码贡献者超过300人。一家主营Elasticsearch的公司就此成立，他们一边提供商业支持一边开发新功能，不过Elasticsearch将永远开源且对所有人可用。
Shay的妻子依旧等待着她的食谱搜索……
5. ES的应用场景
Es主要以轻量级JSON作为数据存储格式，这点与MongoDB有点类似，但它在读写性能上优于 MongoDB 。同时也支持地理位置查询 ，还方便地理位置和文本混合查询 。 以及在统计、日志类数据存储和分析、可视化这方面是引领者。
国外:
Wikipedia
(维基百科)使用ES提供全文搜索并高亮关键字、
StackOverflow
(IT问答网站)结合全文搜索与地理位置查询、
Github
使用Elasticsearch检索1300亿行的代码。
国内:
百度
(在云分析、网盟、预测、文库、钱包、风控等业务上都应用了ES，单集群每天导入30TB+数据， 总共每天60TB+)、
新浪 、阿里巴巴、腾讯
等公司均有对ES的使用。
使用比较广泛的平台ELK(ElasticSearch, Logstash, Kibana)。
6. ES的安装
0. 安装前准备
centos7 +
java 8 +
elastic 6.2.4+
1. 在官方网站下载ES
wget http://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-6.4.1.tar.gz
2. 安装JDK(必须JDK1.8+)
rpm -ivh jdk-8u181-linux-x64.rpm
/*注意:默认安装位置 /usr/java/jdk1.8.0_171-amd64*/
3. 配置环境变量
vim /etc/profile
在文件末尾加入:
export JAVA_HOME=/usr/java/jdk1.8.0_171-amd64
export PATH=$PATH:$JAVA_HOME/bin
4. 重载系统配置
source /etc/profile
5. 安装elasticsearche
tar -zxvf elasticsearch-6.4.1.tar.gz
6. elasticsearche的目录结构
bin 可执行的二进制文件的目录
config 配置文件的目录
lib 运行时依赖的库
logs modules 运行时日志文件
plugins es中提供的插件
7. 运行es服务
在bin目录中执行 ./elasticsearch
注意:root用户启动[2018-09-19T14:50:04,029][WARN ][o.e.b.ElasticsearchUncaughtExceptionHandler] [] uncaught exception in thread [main]org.elasticsearch.bootstrap.StartupException: java.lang.RuntimeException: can not run elasticsearch as root
8. 不能以root用户身份启动
a.在linux系统中创建新的组
groupadd es
b.创建新的用户es并将es用户放入es组中
useradd es -g es
c.修改es用户密码
passwd es
d.将root用户解压的文件移动到es用户目录中
mv /root/elasticsearch-6.2.4 /home/es/
f.改变文件的所有者
chown -R es:es 当前es的安装目录(这里是:/home/es/elasticsearch)
9. 登录es用户启动ES
./elasticsearch 启动ES
10. 测试ES是否启动成功
在命令终端中执行: curl http://localhost:9200 出现以下信息:
{
"name" : "xQK1cwT",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "t7IYk7LKQ0mXcyyrdFWpLg",
"version" : {
"number" : "6.2.4",
"build_hash" : "ccec39f",
"build_date" : "2018-04-12T20:37:28.497551Z",
"build_snapshot" : false,
"lucene_version" : "7.2.1",
"minimum_wire_compatibility_version" : "5.6.0",
"minimum_index_compatibility_version" : "5.0.0"
},
"tagline" : "You Know, for Search"
}
11. 开启ES远程访问
vim elasticsearch.yml 将原来network修改为以下配置:
network.host: 0.0.0.0
12. 启动时错误解决方案
a.重新启动es出现如下错误
**ERROR: bootstrap checks failed[1]: max file descriptors [4096] for elasticsearch process is too low, increase to at least [65536]**
解决方案:
# 切换到root用户修改
vim /etc/security/limits.conf
# 在最后面追加下面内容
* soft nofile 65536
* hard nofile 65536
* soft nproc 4096
* hard nproc 4096
# 退出重新登录检测配置是否生效:
ulimit -Hn
ulimit -Sn
ulimit -Hu
ulimit -Su
b.重新启动出现如下错误
**ERROR: max number of threads [3802] for user [chenyn] is too low,increase to at least [4096]**
解决方案:
#进入limits.d目录下修改配置文件。
vim /etc/security/limits.d/20-nproc.conf
# 修改为 启动ES用户名 soft nproc 4096
c.重新启动出现如下错误
**ERROR: max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]**
解决方案:
vim /etc/sysctl.conf
vm.max_map_count=655360
#执行以下命令生效：
sysctl -p
13. 关闭网络防火墙
systemctl stop firewalld
systemctl disable firewalld
14. 外部浏览器访问即可
http://es的主机名:9200 出现如下信息说明安装成功:
{
"name" : "xQK1cwT",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "t7IYk7LKQ0mXcyyrdFWpLg",
"version" : {
"number" : "6.2.4",
"build_hash" : "ccec39f",
"build_date" : "2018-04-12T20:37:28.497551Z",
"build_snapshot" : false,
"lucene_version" : "7.2.1",
"minimum_wire_compatibility_version" : "5.6.0",
"minimum_index_compatibility_version" : "5.0.0"
},
"tagline" : "You Know, for Search"
}
7. ES中基本概念
7.1 接近实时(NRT)
Elasticsearch是一个接近实时的搜索平台
。这意味着，
从索引一个文档直到这个文档能够被搜索到有一个轻微的延迟(通常是1秒内)
7.2 索引(index)
一个索引就是一个拥有几分相似特征的文档的集合
。比如说，你可以有一个客户数据的索引，另一个产品目录的索引，还有一个订单数据的索引。
一个索引由一个名字来标识(必须全部是小写字母的)
，
并且当我们要对这个索引中的文档进行索引、搜索、更新和删除的时候，都要使用到这个名字
。
索引类似于关系型数据库中Database 的概念
。在一个集群中，如果你想，可以定义任意多的索引。
7.3 类型(type)
在一个索引中，你可以定义一种或多种类型
。一个类型是你的索引的一个逻辑上的分类/分区，其语义完全由你来定。通常，会为具有一组共同字段的文档定义一个类型。比如说，我们假设你运营一个博客平台并且将你所有的数 据存储到一个索引中。在这个索引中，你可以为用户数据定义一个类型，为博客数据定义另一个类型，当然，也可 以为评论数据定义另一个类型。
类型类似于关系型数据库中Table的概念
。
NOTE: 在5.x版本以前可以在一个索引中定义多个类型,6.x之后版本也可以使用,但是不推荐,在8.x版本中彻底移除一个索引中创建多个类型
7.4 映射(Mapping)
Mapping
是ES中的一个很重要的内容，
它类似于传统关系型数据中table的schema，用于定义一个索引(index)中的类型(type)的数据的结构
。 在ES中，我们可以手动创建type(相当于table)和mapping(相关与schema),也可以采用默认创建方式。
在默认配置下，ES可以根据插入的数据自动地创建type及其mapping。 mapping中主要包括字段名、字段数据类型和字段索引类型
7.5 文档(document)
**一个文档是一个可被索引的基础信息单元，类似于表中的一条记录。**比如，你可以拥有某一个员工的文档,也可以拥有某个商品的一个文档。文档以采用了轻量级的数据交换格式JSON(Javascript Object Notation)来表示。
8. Kibana的安装
Kibana是一个针对Elasticsearch的开源分析及可视化平台，使用Kibana可以查询、查看并与存储在ES索引的数据进行交互操作，使用Kibana能执行高级的数据分析，并能以图表、表格和地图的形式查看数据
1. 下载Kibana
https://www.elastic.co/downloads/kibana
2. 安装下载的kibana
rpm -ivh kibana-6.2.4-x86_64.rpm
3. 查找kibana的安装位置
find / -name kibana
4. 编辑kibana配置文件
[root@localhost /]# vim /etc/kibana/kibana.yml
5. 修改如下配置
server.host: "10.102.115.3" #ES服务器主机名
elasticsearch.url: "http://10.102.115.3:9200" #ES服务器地址
6. 启动kibana
systemctl start kibana
systemctl stop kibana
systemctl status kibana
7. 访问kibana的web界面
http://10.102.115.3:5601/ #kibana默认端口为5601 使用主机:端口直接访问即可
9. Kibana的基本操作
9.1 索引(Index)的基本操作
PUT /dangdang/ 创建索引
DELETE /dangdang 删除索引
DELETE /* 删除所有索引
GET /_cat/indices?v 查看索引信息
9.2 类型(type)的基本操作
创建类型
1.创建/dangdang索引并创建(product)类型
PUT /dangdang
{
"mappings": {
"product": {
"properties": {
"title": { "type": "text" },
"name": { "type": "text" },
"age": { "type": "integer" },
"created": {
"type": "date",
"format": "strict_date_optional_time||epoch_millis"
}
}
}
}
}
注意: 这种方式创建类型要求索引不能存在
Mapping Type:
: text , keyword , date ,integer, long , double , boolean or ip
查看类型
GET /dangdang/_mapping/product # 语法:GET /索引名/_mapping/类型名
9.3 文档(document)的基本操作
添加文档
PUT /ems/emp/1 #/索引/类型/id
{
"name":"赵小六",
"age":23,
"bir":"2012-12-12",
"content":"这是一个好一点的员工"
}
查询文档
GET /ems/emp/1
返回结果:
{
"_index": "ems",
"_type": "emp",
"_id": "1",
"_version": 1,
"found": true,
"_source": {
"name": "赵小六",
"age": 23,
"bir": "2012-12-12",
"content": "这是一个好一点的员工"
}
}
删除文档
DELETE /ems/emp/1
{
"_index": "ems",
"_type": "emp",
"_id": "1",
"_version": 2,
"result": "deleted", #删除成功
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 1,
"_primary_term": 1
}
更新文档
1.第一种方式 更新原有的数据
POST /dangdang/emp/1/_update
{
"doc":{
"name":"xiaohei"
}
}
2.第二种方式 添加新的数据
POST /ems/emp/1/_update
{
"doc":{
"name":"xiaohei",
"age":11,
"dpet":"你好部门"
}
}
3.第三种方式 在原来数据基础上更新
POST /ems/emp/1/_update
{
"script": "ctx._source.age += 5"
}
ES的使用语法风格为:
<REST Verb> /<Index>/<Type>/<ID>
REST操作 /索引/类型/文档id
批量操作
1. 批量索引两个文档
PUT /dangdang/emp/_bulk
{"index":{"_id":"1"}}
{"name": "John Doe","age":23,"bir":"2012-12-12"}
{"index":{"_id":"2"}}
{"name": "Jane Doe","age":23,"bir":"2012-12-12"}
2. 更新文档同时删除文档
POST /dangdang/emp/_bulk
{"update":{"_id":"1"}}
{"doc":{"name":"lisi"}}
{"delete":{"_id":2}}
{"index":{}}
{"name":"xxx","age":23}
注意:批量时不会因为一个失败而全部失败,二十继续执行后续操作,批量在返回时按照执行的状态开始返回
10. ES中高级检索
10.1 检索方式
ES官方提供了两中检索方式:
一种是通过 URL 参数进行搜索,另一种是通过 DSL(Domain Specified Language) 进行搜索
。
官方更推荐使用第二种方式第二种方式是基于传递JSON作为请求体(request body)格式与ES进行交互，这种方式更强大，更简洁
。
10.2 测试数据
1.删除索引
DELETE /ems
2.创建索引并指定类型
PUT /ems
{
"mappings":{
"emp":{
"properties":{
"name":{
"type":"text"
},
"age":{
"type":"integer"
},
"bir":{
"type":"date"
},
"content":{
"type":"text"
},
"address":{
"type":"keyword"
}
}
}
}
}
3.插入测试数据
PUT /ems/emp/_bulk
{"index":{}}
{"name":"小黑","age":23,"bir":"2012-12-12","content":"为开发团队选择一款优秀的MVC框架是件难事儿，在众多可行的方案中决择需要很高的经验和水平","address":"北京"}
{"index":{}}
{"name":"王小黑","age":24,"bir":"2012-12-12","content":"Spring 框架是一个分层架构，由 7 个定义良好的模块组成。Spring 模块构建在核心容器之上，核心容器定义了创建、配置和管理 bean 的方式","address":"上海"}
{"index":{}}
{"name":"张小五","age":8,"bir":"2012-12-12","content":"Spring Cloud 作为Java 语言的微服务框架，它依赖于Spring Boot，有快速开发、持续交付和容易部署等特点。Spring Cloud 的组件非常多，涉及微服务的方方面面，井在开源社区Spring 和Netflix 、Pivotal 两大公司的推动下越来越完善","address":"无锡"}
{"index":{}}
{"name":"win7","age":9,"bir":"2012-12-12","content":"Spring的目标是致力于全方位的简化Java开发。 这势必引出更多的解释， Spring是如何简化Java开发的？","address":"南京"}
{"index":{}}
{"name":"梅超风","age":43,"bir":"2012-12-12","content":"Redis是一个开源的使用ANSI C语言编写、支持网络、可基于内存亦可持久化的日志型、Key-Value数据库，并提供多种语言的API","address":"杭州"}
{"index":{}}
{"name":"张无忌","age":59,"bir":"2012-12-12","content":"ElasticSearch是一个基于Lucene的搜索服务器。它提供了一个分布式多用户能力的全文搜索引擎，基于RESTful web接口","address":"北京"}
10.2 URL检索
GET /ems/emp/_search?q=*&sort=age:asc
_search 搜索的API
q=* 匹配所有文档
sort 以结果中的指定字段排序
10.3 DSL检索
NOTE: 以下重点讲解DSL语法
GET /ems/emp/_search
{
"query": {"match_all": {}},
"sort": [
{
"age": {
"order": "desc"
}
}
]
}
10.4 DSL高级检索(Query)
0. 查询所有(match_all)
match_all关键字:
返回索引中的全部文档
GET /ems/emp/_search
{
"query": { "match_all": {} }
}
1. 查询结果中返回指定条数(size)
size 关键字
: 指定查询结果中返回指定条数。
默认返回值10条
GET /ems/emp/_search
{
"query": { "match_all": {} },
"size": 1
}
2. 分页查询(from)
from 关键字
: 用来指定起始返回位置，和
size关键字连用可实现分页效果
GET /ems/emp/_search
{
"query": {"match_all": {}},
"sort": [
{
"age": {
"order": "desc"
}
}
],
"size": 2,
"from": 1
}
3. 查询结果中返回指定字段(_source)
_source 关键字
: 是一个数组,在数组中用来指定展示那些字段
GET /ems/emp/_search
{
"query": { "match_all": {} },
"_source": ["account_number", "balance"]
}
4. 关键词查询(term)
term 关键字
: 用来使用关键词查询
GET /ems/emp/_search
{
"query": {
"term": {
"address": {
"value": "北京"
}
}
}
}
NOTE1: 通过使用term查询得知ES中默认使用分词器为标准分词器(StandardAnalyzer),标准分词器对于英文单词分词,对于中文单字分词
。
NOTE2: 通过使用term查询得知,在ES的Mapping Type 中 keyword , date ,integer, long , double , boolean or ip 这些类型不分词
，
只有text类型分词
。
5. 范围查询(range)
range 关键字
: 用来指定查询指定范围内的文档
GET /ems/emp/_search
{
"query": {
"range": {
"age": {
"gte": 8,
"lte": 30
}
}
}
}
6. 前缀查询(prefix)
prefix 关键字
: 用来检索含有指定前缀的关键词的相关文档
GET /ems/emp/_search
{
"query": {
"prefix": {
"content": {
"value": "redis"
}
}
}
}
7. 通配符查询(wildcard)
wildcard 关键字
: 通配符查询
? 用来匹配一个任意字符 * 用来匹配多个任意字符
GET /ems/emp/_search
{
"query": {
"wildcard": {
"content": {
"value": "re*"
}
}
}
}
8. 多id查询(ids)
ids 关键字
: 值为数组类型,用来根据一组id获取多个对应的文档
GET /ems/emp/_search
{
"query": {
"ids": {
"values": ["lg5HwWkBxH7z6xax7W3_","lQ5HwWkBxH7z6xax7W3_"]
}
}
}
9. 模糊查询(fuzzy)
fuzzy 关键字
: 用来模糊查询含有指定关键字的文档
GET /ems/emp/_search
{
"query": {
"fuzzy": {
"content":"spring"
}
}
}
10. 布尔查询(bool)
bool 关键字
: 用来组合多个条件实现复杂查询
must: 相当于&& 同时成立
should: 相当于|| 成立一个就行
must_not: 相当于! 不能满足任何一个
GET /ems/emp/_search
{
"query": {
"bool": {
"must": [
{
"range": {
"age": {
"gte": 0,
"lte": 30
}
}
}
],
"must_not": [
{"wildcard": {
"content": {
"value": "redi?"
}
}}
]
}
},
"sort": [
{
"age": {
"order": "desc"
}
}
]
}
11. 高亮查询(highlight)
highlight 关键字
: 可以让符合条件的文档中的关键词高亮
GET /ems/emp/_search
{
"query": {
"term": {
"content": {
"value": "redis"
}
}
},
"highlight": {
"fields": {
"*": {}
}
}
}
自定义高亮html标签
: 可以在highlight中使用
pre_tags
和
post_tags
GET /ems/emp/_search
{
"query":{
"term":{
"content":"框架"
}
},
"highlight": {
"pre_tags": ["<span style='color:red'>"],
"post_tags": ["</span>"],
"fields": {
"*":{}
}
}
}
多字段高亮 使用
require_field_match
开启多个字段高亮
GET /ems/emp/_search
{
"query":{
"term":{
"content":"框架"
}
},
"highlight": {
"pre_tags": ["<span style='color:red'>"],
"post_tags": ["</span>"],
"require_field_match":false,
"fields": {
"*":{}
}
}
}
12. 多字段查询(multi_match)
GET /ems/emp/_search
{
"query": {
"multi_match": {
"query": "中国",
"fields": ["name","content"] #这里写要检索的指定字段
}
}
}
13. 多字段分词查询(query_String)
GET /dangdang/book/_search
{
"query": {
"query_string": {
"query": "中国声音",
"analyzer": "ik_max_word",
"fields": ["name","content"]
}
}
}
11. IK分词器
NOTE: 默认ES中采用标准分词器进行分词,这种方式并不适用于中文网站,因此需要修改ES对中文友好分词,从而达到更好的搜索的效果。
11.1 在线安装IK
在线安装IK (v5.5.1版本后开始支持在线安装 )
1. 在es安装目录中执行如下命令
[es@linux elasticsearch-6.2.4]$ ./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.2.4/elasticsearch-analysis-ik-6.2.4.zip
-> Downloading https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.2.4/elasticsearch-analysis-ik-6.2.4.zip
[=================================================] 100%
-> Installed analysis-ik
[es@linux elasticsearch-6.2.4]$ ls plugins/
analysis-ik
[es@linux elasticsearch-6.2.4]$ cd plugins/analysis-ik/
[es@linux analysis-ik]$ ls
commons-codec-1.9.jar elasticsearch-analysis-ik-6.2.4.jar httpcore-4.4.4.jar
commons-logging-1.2.jar httpclient-4.5.2.jar plugin-descriptor.properties
2. 重启es生效
NOTE: 要求版本严格与当前使用版本一致,如需使用其他版本替换
6.2.4
为使用的版本号
11.2 本地安装IK
可以将对应的IK分词器下载到本地,然后再安装
NOTE: 本课程使用本地安装
1. 下载对应版本
[es@linux ~]$ wget https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.2.4/elasticsearch-analysis-ik-6.2.4.zip
2. 解压
[es@linux ~]$ unzip elasticsearch-analysis-ik-6.2.4.zip #先使用yum install -y unzip
3. 移动到es安装目录的plugins目录中
[es@linux ~]$ ls elasticsearch-6.2.4/plugins/
[es@linux ~]$ mv elasticsearch elasticsearch-6.2.4/plugins/
[es@linux ~]$ ls elasticsearch-6.2.4/plugins/
elasticsearch
[es@linux ~]$ ls elasticsearch-6.2.4/plugins/elasticsearch/
commons-codec-1.9.jar config httpclient-4.5.2.jar plugin-descriptor.properties
commons-logging-1.2.jar elasticsearch-analysis-ik-6.2.4.jar httpcore-4.4.4.jar
4. 重启es生效
11.3 测试IK分词器
NOTE: IK分词器提供了两种mapping类型用来做文档的分词分别是
ik_max_word
和
ik_smart
ik_max_word 和 ik_smart 什么区别?
ik_max_word: 会将文本做最细粒度的拆分
，比如会将“中华人民共和国国歌”拆分为“中华人民共和国,中华人民,中华,华人,人民共和国,人民,人,民,共和国,共和,和,国国,国歌”，会穷尽各种可能的组合；
ik_smart: 会做最粗粒度的拆分
，比如会将“中华人民共和国国歌”拆分为“中华人民共和国,国歌”。
测试数据
DELETE /ems
PUT /ems
{
"mappings":{
"emp":{
"properties":{
"name":{
"type":"text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_max_word"
},
"age":{
"type":"integer"
},
"bir":{
"type":"date"
},
"content":{
"type":"text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_max_word"
},
"address":{
"type":"keyword"
}
}
}
}
}
PUT /ems/emp/_bulk
{"index":{}}
{"name":"小黑","age":23,"bir":"2012-12-12","content":"为开发团队选择一款优秀的MVC框架是件难事儿，在众多可行的方案中决择需要很高的经验和水平","address":"北京"}
{"index":{}}
{"name":"王小黑","age":24,"bir":"2012-12-12","content":"Spring 框架是一个分层架构，由 7 个定义良好的模块组成。Spring 模块构建在核心容器之上，核心容器定义了创建、配置和管理 bean 的方式","address":"上海"}
{"index":{}}
{"name":"张小五","age":8,"bir":"2012-12-12","content":"Spring Cloud 作为Java 语言的微服务框架，它依赖于Spring Boot，有快速开发、持续交付和容易部署等特点。Spring Cloud 的组件非常多，涉及微服务的方方面面，井在开源社区Spring 和Netflix 、Pivotal 两大公司的推动下越来越完善","address":"无锡"}
{"index":{}}
{"name":"win7","age":9,"bir":"2012-12-12","content":"Spring的目标是致力于全方位的简化Java开发。 这势必引出更多的解释， Spring是如何简化Java开发的？","address":"南京"}
{"index":{}}
{"name":"梅超风","age":43,"bir":"2012-12-12","content":"Redis是一个开源的使用ANSI C语言编写、支持网络、可基于内存亦可持久化的日志型、Key-Value数据库，并提供多种语言的API","address":"杭州"}
{"index":{}}
{"name":"张无忌","age":59,"bir":"2012-12-12","content":"ElasticSearch是一个基于Lucene的搜索服务器。它提供了一个分布式多用户能力的全文搜索引擎，基于RESTful web接口","address":"北京"}
GET /ems/emp/_search
{
"query":{
"term":{
"content":"框架"
}
},
"highlight": {
"pre_tags": ["<span style='color:red'>"],
"post_tags": ["</span>"],
"fields": {
"*":{}
}
}
}
11.4 配置扩展词
IK支持自定义
扩展词典
和
停用词典
,所谓**
扩展词典
就是有些词并不是关键词,但是也希望被ES用来作为检索的关键词,可以将这些词加入扩展词典。
停用词典
**就是有些词是关键词,但是出于业务场景不想使用这些关键词被检索到，可以将这些词放入停用词典。如何定义扩展词典和停用词典可以修改IK分词器中
config
目录中
IKAnalyzer.cfg.xml
这个文件。
NOTE：词典的编码必须为UTF-8，否则无法生效
1. 修改vim IKAnalyzer.cfg.xml
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd">
<properties>
<comment>IK Analyzer 扩展配置</comment>
<!--用户可以在这里配置自己的扩展字典 -->
<entry key="ext_dict">ext_dict.dic</entry>
<!--用户可以在这里配置自己的扩展停止词字典-->
<entry key="ext_stopwords">ext_stopword.dic</entry>
</properties>
2. 在ik分词器目录下config目录中创建ext_dict.dic文件 编码一定要为UTF-8才能生效
vim ext_dict.dic 加入扩展词即可
3. 在ik分词器目录下config目录中创建ext_stopword.dic文件
vim ext_stopword.dic 加入停用词即可
4.重启es生效
12. (过滤查询) Filter Query
12.1 过滤查询
其实准确来说，ES中的查询操作分为2种:
查询(query)
和
过滤(filter)
。
查询即是之前提到的query查询，它 (查询)默认会计算每个返回文档的得分，然后根据得分排序
。
而过滤(filter)只会筛选出符合的文档，并不计算 得分，且它可以缓存文档 。所以，单从性能考虑，过滤比查询更快
。换句话说，过滤适合在大范围筛选数据，而查询则适合精确匹配数据。一般应用时， 应先使用过滤操作过滤数据， 然后使用查询匹配数据。
12.2 过滤语法
GET /ems/emp/_search
{
"query": {
"bool": {
"must": [
{"match_all": {}}
],
"filter": {
"range": {
"age": {
"gte": 10
}
}
}
}
}
}
NOTE: 在执行filter和query时,先执行filter在执行query
NOTE:Elasticsearch会自动缓存经常使用的过滤器，以加快性能。
12.3 常见的过滤器类型
term 、 terms Filter
GET /ems/emp/_search # 使用term过滤
{
"query": {
"bool": {
"must": [
{"term": {
"name": {
"value": "小黑"
}
}}
],
"filter": {
"term": {
"content":"框架"
}
}
}
}
}
GET /dangdang/book/_search #使用terms过滤
{
"query": {
"bool": {
"must": [
{"term": {
"name": {
"value": "中国"
}
}}
],
"filter": {
"terms": {
"content":[
"科技",
"声音"
]
}
}
}
}
}
ranage filter
GET /ems/emp/_search
{
"query": {
"bool": {
"must": [
{"term": {
"name": {
"value": "中国"
}
}}
],
"filter": {
"range": {
"age": {
"gte": 7,
"lte": 20
}
}
}
}
}
}
exists filter
过滤存在指定字段,获取字段不为空的索引记录使用
GET /ems/emp/_search
{
"query": {
"bool": {
"must": [
{"term": {
"name": {
"value": "中国"
}
}}
],
"filter": {
"exists": {
"field":"aaa"
}
}
}
}
}
ids filter
过滤含有指定字段的索引记录
GET /ems/emp/_search
{
"query": {
"bool": {
"must": [
{"term": {
"name": {
"value": "中国"
}
}}
],
"filter": {
"ids": {
"values": ["1","2","3"]
}
}
}
}
}
13. Java操作ES
13.1 引入maven依赖
<dependency>
<groupId>org.elasticsearch</groupId>
<artifactId>elasticsearch</artifactId>
<version>6.2.4</version>
</dependency>
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>transport</artifactId>
<version>6.2.4</version>
</dependency>
13.2创建索引和类型
Rest的创建方式
// 1.在restful的创建方式
PUT /dangdang
{
"mappings": {
"book":{
"properties": {
"name":{
"type":"text",
"analyzer": "ik_max_word"
},
"age":{
"type":"integer"
},
"sex":{
"type":"keyword"
},
"content":{
"type":"text",
"analyzer": "ik_max_word"
}
}
}
}
}
Java中创建方式
/**
* 创建索引并创建类型同时指定映射
*/
@Test
public void testCreateIndexAndTypeAndMapping() throws IOException, ExecutionException, InterruptedException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
System.out.println("=======创建索引=======");
CreateIndexResponse indexResponse = transportClient.admin().indices().prepareCreate("dangdang").execute().get();
System.out.println(indexResponse.index());
System.out.println("=======创建类型指定映射=======");
XContentBuilder mappingBuilder = XContentFactory.jsonBuilder();
mappingBuilder.startObject()
.startObject("properties")
.startObject("name")
.field("type", "text")
.field("analyzer", "ik_max_word")
.endObject()
.startObject("age")
.field("type", "integer")
.endObject()
.startObject("sex")
.field("type", "keyword")
.endObject()
.startObject("content")
.field("type", "text")
.field("analyzer", "ik_max_word")
.endObject()
.endObject()
.endObject();
PutMappingRequest putMappingRequest = new PutMappingRequest("dangdang").type("book").source(mappingBuilder);
transportClient.admin().indices().putMapping(putMappingRequest).get();
}
13.3 索引一条记录
/**
* 创建索引(自动生成文档id)
* @throws IOException
*/
@Test
public void testCreate() throws IOException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
XContentBuilder xContentBuilder = XContentFactory.jsonBuilder().startObject()
.field("name","中国人")
.field("age",23)
.field("sex","男")
.field("content","他是一个中国人,这个中国人怎么样,挺好的").endObject();
IndexResponse indexResponse = transportClient.prepareIndex("dangdang", "book").setSource(xContentBuilder).get();
System.out.println(indexResponse.status());
}
/**
* 创建索引(指定生成文档id)
*
* @throws IOException
*/
@Test
public void testCreate() throws IOException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
XContentBuilder xContentBuilder = XContentFactory.jsonBuilder().startObject()
.field("name", "中国人")
.field("age", 23)
.field("sex", "男")
.field("content", "他是一个中国人,这个中国人怎么样,挺好的").endObject();
IndexResponse indexResponse = transportClient.prepareIndex("dangdang", "book","1").setSource(xContentBuilder).get();
System.out.println(indexResponse.status());
}
13.3 更新一条索引
/**
* 更新一条记录
*
*/
@Test
public void testUpdate() throws IOException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
XContentBuilder source = XContentFactory.jsonBuilder();
source.startObject().field("name","小黑是中国人").endObject();
UpdateResponse updateResponse = transportClient.prepareUpdate("dangdang", "book", "1")
.setDoc(source).get();
System.out.println(updateResponse.status());
}
13.4 删除一条索引
/**
* 删除一条索引记录
* @throws UnknownHostException
*/
@Test
public void testDelete() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
DeleteResponse deleteResponse = transportClient.prepareDelete("dangdang", "book", "1").get();
System.out.println(deleteResponse.status());
}
13.5 批量更新
/**
* 批量更新
*/
@Test
public void testBulk() throws IOException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
//添加第一条记录
IndexRequest request1 = new IndexRequest("dangdang","book","1");
request1.source(XContentFactory.jsonBuilder().startObject().field("name","中国科技").field("age",23).field("sex","男").field("content","这是个好人").endObject());
//添加第二条记录
IndexRequest request2 = new IndexRequest("dangdang","book","2");
request2.source(XContentFactory.jsonBuilder().startObject().field("name","中国之声").field("age",23).field("sex","男").field("content","这是一个好的声音").endObject());
//更新记录
UpdateRequest updateRequest = new UpdateRequest("dangdang","book","1");
updateRequest.doc(XContentFactory.jsonBuilder().startObject().field("name","中国力量").endObject());
//删除一条记录
DeleteRequest deleteRequest = new DeleteRequest("dangdang","book","1");
BulkResponse bulkItemResponses = transportClient.prepareBulk().add(request1).add(request2).add(updateRequest).add(deleteRequest).get();
BulkItemResponse[] items = bulkItemResponses.getItems();
for (BulkItemResponse item : items) {
System.out.println(item.status());
}
}
13.6 检索记录
查询所有并排序
/**
* 查询所有并排序
* ASC 升序 DESC 降序
* addSort("age", SortOrder.ASC) 指定排序字段以及使用哪种方式排序
* addSort("age", SortOrder.DESC) 指定排序字段以及使用哪种方式排序
*/
@Test
public void testMatchAllQuery() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(QueryBuilders.matchAllQuery()).addSort("age", SortOrder.DESC).get();
SearchHits hits = searchResponse.getHits();
System.out.println("符合条件的记录数: "+hits.totalHits);
for (SearchHit hit : hits) {
System.out.print("当前索引的分数: "+hit.getScore());
System.out.print(", 对应结果:=====>"+hit.getSourceAsString());
System.out.println(", 指定字段结果:"+hit.getSourceAsMap().get("name"));
System.out.println("=================================================");
}
}
分页查询
/**
* 分页查询
* From 从那条记录开始 默认从0 开始 form = (pageNow-1)*size
* Size 每次返回多少条符合条件的结果 默认10
*/
@Test
public void testMatchAllQueryFormAndSize() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(QueryBuilders.matchAllQuery()).setFrom(0).setSize(2).get();
SearchHits hits = searchResponse.getHits();
System.out.println("符合条件的记录数: "+hits.totalHits);
for (SearchHit hit : hits) {
System.out.print("当前索引的分数: "+hit.getScore());
System.out.print(", 对应结果:=====>"+hit.getSourceAsString());
System.out.println(", 指定字段结果:"+hit.getSourceAsMap().get("name"));
System.out.println("=================================================");
}
}
查询返回字段
/**
* 查询返回指定字段(source) 默认返回所有
* setFetchSource 参数1:包含哪些字段 参数2:排除哪些字段
* setFetchSource("*","age") 返回所有字段中排除age字段
* setFetchSource("name","") 只返回name字段
* setFetchSource(new String[]{},new String[]{})
*/
@Test
public void testMatchAllQuerySource() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(QueryBuilders.matchAllQuery()).setFetchSource("*","age").get();
SearchHits hits = searchResponse.getHits();
System.out.println("符合条件的记录数: "+hits.totalHits);
for (SearchHit hit : hits) {
System.out.print("当前索引的分数: "+hit.getScore());
System.out.print(", 对应结果:=====>"+hit.getSourceAsString());
System.out.println(", 指定字段结果:"+hit.getSourceAsMap().get("name"));
System.out.println("=================================================");
}
}
term查询
/**
* term查询
*/
@Test
public void testTerm() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
TermQueryBuilder queryBuilder = QueryBuilders.termQuery("name","中国");
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(queryBuilder).get();
}
range查询
/**
* rang查询
* lt 小于
* lte 小于等于
* gt 大于
* gte 大于等于
*/
@Test
public void testRange() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("age").lt(45).gte(8);
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(rangeQueryBuilder).get();
}
prefix查询
/**
* prefix 前缀查询
*
*/
@Test
public void testPrefix() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
PrefixQueryBuilder prefixQueryBuilder = QueryBuilders.prefixQuery("name", "中");
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(prefixQueryBuilder).get();
}
wildcard查询
/**
* wildcardQuery 通配符查询
*
*/
@Test
public void testwildcardQuery() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
WildcardQueryBuilder wildcardQueryBuilder = QueryBuilders.wildcardQuery("name", "中*");
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(wildcardQueryBuilder).get();
}
Ids查询
/**
* ids 查询
*/
@Test
public void testIds() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
IdsQueryBuilder idsQueryBuilder = QueryBuilders.idsQuery().addIds("1","2");
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(idsQueryBuilder).get();
}
fuzzy模糊查询
/**
* fuzzy 查询
*/
@Test
public void testFuzzy() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
FuzzyQueryBuilder fuzzyQueryBuilder = QueryBuilders.fuzzyQuery("content", "国人");
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(fuzzyQueryBuilder).get();
}
bool 查询
/**
* bool 查询
*/
@Test
public void testBool() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
boolQueryBuilder.should(QueryBuilders.matchAllQuery());
boolQueryBuilder.mustNot(QueryBuilders.rangeQuery("age").lte(8));
boolQueryBuilder.must(QueryBuilders.termQuery("name","中国"));
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").setQuery(boolQueryBuilder).get();
}
高亮查询
/**
* 高亮查询
* .highlighter(highlightBuilder) 用来指定高亮设置
* requireFieldMatch(false) 开启多个字段高亮
* field 用来定义高亮字段
* preTags("<span style='color:red'>") 用来指定高亮前缀
* postTags("</span>") 用来指定高亮后缀
*/
@Test
public void testHighlight() throws UnknownHostException {
TransportClient transportClient = new PreBuiltTransportClient(Settings.EMPTY).addTransportAddress(new TransportAddress(InetAddress.getByName("172.16.251.142"), 9300));
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("name", "中国");
HighlightBuilder highlightBuilder = new HighlightBuilder();
highlightBuilder.requireFieldMatch(false).field("name").field("content").preTags("<span style='color:red'>").postTags("</span>");
SearchResponse searchResponse = transportClient.prepareSearch("dangdang").setTypes("book").highlighter(highlightBuilder).highlighter(highlightBuilder).setQuery(termQueryBuilder).get();
SearchHits hits = searchResponse.getHits();
System.out.println("符合条件的记录数: "+hits.totalHits);
for (SearchHit hit : hits) {
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
Map<String, HighlightField> highlightFields = hit.getHighlightFields();
System.out.println("================高亮之前==========");
for(Map.Entry<String,Object> entry:sourceAsMap.entrySet()){
System.out.println("key: "+entry.getKey() +" value: "+entry.getValue());
}
System.out.println("================高亮之后==========");
for (Map.Entry<String,Object> entry:sourceAsMap.entrySet()){
HighlightField highlightField = highlightFields.get(entry.getKey());
if (highlightField!=null){
System.out.println("key: "+entry.getKey() +" value: "+ highlightField.fragments()[0]);
}else{
System.out.println("key: "+entry.getKey() +" value: "+entry.getValue());
}
}
}
}
多字段查询
MultiMatchQueryBuilder queryBuilder
= QueryBuilders.multiMatchQuery("框架","content","name");
多字段分词查询
QueryStringQueryBuilder queryStringQueryBuilder =
QueryBuilders.queryStringQuery("框架张无忌")
.analyzer("ik_max_word") //定义分词器
.field("name")//定义字段
.field("content");//字段
14. SpringBoot Data操作ES
14.1 引入依赖
<!--注意:升级原有项目中springboot版本-->
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.0.6.RELEASE</version>
</parent>
<!--springboot web -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<!--通过spring data 操作Es-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>
<!--springboot 继承test-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<!--引入lombook-->
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.16.20</version>
<scope>provided</scope>
</dependency>
14.2 编写yml配置
spring:
data:
elasticsearch:
cluster-nodes: 172.16.251.142:9300
14.3 编写entity
@Document(indexName = "dangdang",type = "book")
@Data
@AllArgsConstructor
@NoArgsConstructor
public class Book {
@Id
private String id;
@Field(type = FieldType.Text,analyzer ="ik_max_word")
private String name;
@Field(type = FieldType.Date)
private Date createDate;
@Field(type = FieldType.Keyword)
private String author;
@Field(type = FieldType.Text,analyzer ="ik_max_word")
private String content;
}
@Document
: 代表一个文档记录
indexName
: 用来指定索引名称
type
: 用来指定索引类型
@Id
: 用来将对象中id和ES中_id映射
@Field
: 用来指定ES中的字段对应Mapping
type
: 用来指定ES中存储类型
analyzer
: 用来指定使用哪种分词器
14.4 编写BookRepository
public interface BookRepository extends ElasticsearchRepository<Book,String> {
}
14.5 索引or更新一条记录
NOTE:这种方式根据实体类中中配置自动在ES创建索引,类型以及映射
@SpringBootTest(classes = Application.class)
@RunWith(SpringRunner.class)
public class TestSpringBootDataEs {
@Autowired
private BookRepository bookRespistory;
/**
* 添加索引和更新索引 id 存在更新 不存在添加
*/
@Test
public void testSaveOrUpdate(){
Book book = new Book();
book.setId("21");
book.setName("小陈");
book.setCreateDate(new Date());
book.setAuthor("李白");
book.setContent("这是中国的好人,这真的是一个很好的人,李白很狂");
bookRespistory.save(book);
}
}
14.6 删除一条记录
/**
* 删除一条索引
*/
@Test
public void testDelete(){
Book book = new Book();
book.setId("21");
bookRespistory.delete(book);
}
14.7 查询
/**
* 查询所有
*/
@Test
public void testFindAll(){
Iterable<Book> books = bookRespistory.findAll();
for (Book book : books) {
System.out.println(book);
}
}
/**
* 查询一个
*/
@Test
public void testFindOne(){
Optional<Book> byId = bookRespistory.findById("21");
System.out.println(byId.get());
}
14.8 查询排序
/**
* 排序查询
*/
@Test
public void testFindAllOrder(){
Iterable<Book> books = bookRespistory.findAll(Sort.by(Sort.Order.asc("createDate")));
books.forEach(book -> System.out.println(book) );
}
14.9 自定义基本查询
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public interface BookRepository extends ElasticsearchRepository<Book,String> {
//根据作者查询
List<Book> findByAuthor(String keyword);
//根据内容查询
List<Book> findByContent(String keyword);
//根据内容和名字查
List<Book> findByNameAndContent(String name,String content);
//根据内容或名称查询
List<Book> findByNameOrContent(String name,String content);
//范围查询
List<Book> findByPriceBetween(Double start,Double end);
//查询名字以xx开始的
List<Book> findByNameStartingWith(String name);
//查询某个字段值是否为false
List<Book> findByNameFalse();
//.......
}
14.10 实现复杂查询
自定义接口
public interface CustomerBookRepository {
//实现分页的方法
List<Book> findByPageable(int page,int size);
//term查询高亮
List<Book> findByNameAndHighlightAdnPageable(String name,int page,int size,String filter);
}
自定义实现
package com.baizhi.es.dao;
import com.baizhi.es.entity.Book;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightField;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.domain.PageRequest;
import org.springframework.data.domain.Pageable;
import org.springframework.data.elasticsearch.core.ElasticsearchTemplate;
import org.springframework.data.elasticsearch.core.SearchResultMapper;
import org.springframework.data.elasticsearch.core.aggregation.AggregatedPage;
import org.springframework.data.elasticsearch.core.aggregation.impl.AggregatedPageImpl;
import org.springframework.data.elasticsearch.core.query.NativeSearchQuery;
import org.springframework.data.elasticsearch.core.query.NativeSearchQueryBuilder;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import static org.elasticsearch.index.query.QueryBuilders.*;
@Configuration
public class CustomerBookRepositoryImpl implements CustomerBookRepository{
@Autowired
private ElasticsearchTemplate elasticsearchTemplate;
@Override
public List<Book> findByNameAndHighlightAdnPageable(String name, int page, int size,String filter) {
HighlightBuilder.Field nameField = new HighlightBuilder
.Field("*")
.preTags("<span style='color:red'>")
.postTags("</span>").requireFieldMatch(false);
NativeSearchQuery nativeSearchQuery = new NativeSearchQueryBuilder()
.withQuery(QueryBuilders.multiMatchQuery(name,"name","content"))
.withPageable(PageRequest.of(page,size))
.withHighlightFields(nameField)
.withFilter(boolQuery().mustNot(termQuery("name",filter)))
.build();
AggregatedPage<Book> books = elasticsearchTemplate.queryForPage(nativeSearchQuery, Book.class, new SearchResultMapper() {
@Override
public <T> AggregatedPage<T> mapResults(SearchResponse response, Class<T> clazz, Pageable pageable) {
SearchHits searchHits = response.getHits();
SearchHit[] hits = searchHits.getHits();
ArrayList<Book> books = new ArrayList<Book>();
for (SearchHit hit : hits) {
Book book = new Book();
//原始map
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
book.setId(sourceAsMap.get("id").toString());
book.setAuthor(sourceAsMap.get("author").toString());
book.setPrice(Double.parseDouble(sourceAsMap.get("price").toString()));
book.setCreateDate(new Date(Long.valueOf(sourceAsMap.get("createDate").toString())));
book.setName(sourceAsMap.get("name").toString());
book.setContent(sourceAsMap.get("content").toString());
//高亮
Map<String, HighlightField> highlightFields = hit.getHighlightFields();
System.out.println(highlightFields);
if (highlightFields.get("name") != null) {
String nameHighlight = highlightFields.get("name").getFragments()[0].toString();
book.setName(nameHighlight);
}
if (highlightFields.get("content") != null) {
String contentHighlight = highlightFields.get("content").getFragments()[0].toString();
book.setContent(contentHighlight);
}
books.add(book);
}
return new AggregatedPageImpl<T>((List<T>)books);
}
});
return books.getContent();
}
@Override
public List<Book> findByPageable(int page, int size) {
NativeSearchQuery searchQuery = new NativeSearchQueryBuilder()
.withIndices("dangdang")
.withTypes("book")
.withQuery(matchAllQuery())
.withPageable(PageRequest.of(page,size))
.build();
return elasticsearchTemplate.queryForList(searchQuery,Book.class);
}
}
15. ES中集群
15.1 相关概念
集群(cluster)
一个集群就是由一个或多个节点组织在一起，它们共同持有你整个的数据，并一起提供索引和搜索功能。一个集群 由一个唯一的名字标识，这个名字默认就是
elasticsearch
。这个名字是重要的，因为一个节点只能通过指定某个集群的名字，来加入这个集群。在产品环境中显式地设定这个名字是一个好习惯，但是使用默认值来进行测试/开发也是不错的。
节点(node)
一个节点是你集群中的一个服务器，作为集群的一部分，它存储你的数据，参与集群的索引和搜索功能。和集群类似，一个节点也是由一个名字来标识的，默认情况下，这个名字是一个随机的漫威漫画角色的名字，这个名字会在启动的时候赋予节点。这个名字对于管理工作来说挺重要的，因为在这个管理过程中，你会去确定网络中的哪些服务器对应于Elasticsearch集群中的哪些节点。
一个节点可以通过配置集群名称的方式来加入一个指定的集群。默认情况下，每个节点都会被安排加入到一个叫 做“elasticsearch”的集群中，这意味着，如果你在你的网络中启动了若干个节点，并假定它们能够相互发现彼此，它们将会自动地形成并加入到一个叫做“elasticsearch”的集群中。
在一个集群里，只要你想，可以拥有任意多个节点。而且，如果当前你的网络中没有运行任何Elasticsearch节点， 这时启动一个节点，会默认创建并加入一个叫做“elasticsearch”的集群。
分片和复制(shards & replicas)
一个索引可以存储超出单个结点硬件限制的大量数据。比如，一个具有10亿文档的索引占据1TB的磁盘空间，而任一节点都没有这样大的磁盘空间;或者单个节点处理搜索请求，响应太慢。为了解决这个问题，Elasticsearch提供了将索引划分成多份的能力，这些份就叫做分片。当你创建一个索引的时候，你可以指定你想要的分片的数量。每个分片本身也是一个功能完善并且独立的“索引”，这个“索引”可以被放置 到集群中的任何节点上。 分片之所以重要，主要有两方面的原因:
允许你水平分割/扩展你的内容容量允许你在分片(潜在地，位于多个节点上)之上进行分布式的、并行的操作，进而提高性能/吞吐量 至于一个分片怎样分布，它的文档怎样聚合回搜索请求，是完全由Elasticsearch管理的，对于作为用户的你来说，这些都是透明的。
在一个网络/云的环境里，失败随时都可能发生，在某个分片/节点不知怎么的就处于离线状态，或者由于任何原因 消失了。这种情况下，有一个故障转移机制是非常有用并且是强烈推荐的。为此目的，Elasticsearch允许你创建分 片的一份或多份拷贝，这些拷贝叫做复制分片，或者直接叫复制。复制之所以重要，主要有两方面的原因:
在分片/节点失败的情况下，提供了高可用性。因为这个原因，注意到复制分片从不与原/主要 (original/primary)分片置于同一节点上是非常重要的。 扩展你的搜索量/吞吐量，因为搜索可以在所有的复制上并行运行
总之，每个索引可以被分成多个分片。一个索引也可以被复制0次(意思是没有复制)或多次。一旦复制了，每个 索引就有了主分片(作为复制源的原来的分片)和复制分片(主分片的拷贝)之别。分片和复制的数量可以在索引创建的时候指定。在索引创建之后，你可以在任何时候动态地改变复制数量，但是不能改变分片的数量。
默认情况下，
Elasticsearch中的每个索引被分片5个主分片和1个复制
，这意味着，如果你的集群中至少有两个节点，你的索引将会有5个主分片和另外5个复制分片(1个完全拷贝)，这样的话每个索引总共就有10个分片。一个 索引的多个分片可以存放在集群中的一台主机上，也可以存放在多台主机上，这取决于你的集群机器数量。主分片和复制分片的具体位置是由ES内在的策略所决定的。
15.2 快速搭建集群
1. 将原有ES安装包复制三份
cp -r elasticsearch-6.2.4/ master/
cp -r elasticsearch-6.2.4/ slave1/
cp -r elasticsearch-6.2.4/ slave2/
2. 删除复制目录中data目录
#注意:由于复制目录之前使用过因此需要在创建集群时将原来数据删除
rm -rf master/data
rm -rf slave1/data
rm -rf slave2/data
3. 编辑es文件夹中config目录中jvm.options文件跳转启动内存
vim master/config/jvm.options
vim slave1/config/jvm.options
vim slave2/config/jvm.options
#分别加入: -Xms512m -Xmx512m
4. 分别修改三个文件夹中config目录中elasticsearch.yml文件
vim master/config/elasticsearch.yml
vim salve1/config/elasticsearch.yml
vim slave2/config/elasticsearch.yml
#分别修改如下配置:
cluster.name: my-es #集群名称(集群名称必须一致)
node.name: es-03 #节点名称(节点名称不能一致)
network.host: 0.0.0.0 #监听地址(必须开启远程权限,并关闭防火墙)
http.port: 9200 #监听端口(在一台机器时服务端口不能一致)
discovery.zen.ping.unicast.hosts: ["172.30.2.175:9301", "172.30.2.201:9302"] #另外两个节点的ip
gateway.recover_after_nodes: 3 #集群可做master的最小节点数
transport.tcp.port: 9300 #集群TCP端口(在一台机器搭建必须修改)
5. 启动多个es
./master/bin/elasticsearch
./slave1/bin/elasticsearch
./slave2/bin/elasticsearch
6. 查看节点状态
curl http://10.102.115.3:9200
curl http://10.102.115.3:8200
curl http://10.102.115.3:7200
7. 查看集群健康
http://10.102.115.3:9200/_cat/health?v
15.3 安装head插件
1. 访问github网站
搜索: elasticsearch-head 插件
2. 安装git
yum install git
3. 将elasticsearch-head下载到本地
git clone git://github.com/mobz/elasticsearch-head.git
4. 安装nodejs
#注意: 没有wget的请先安装yum install -y wget
wget http://cdn.npm.taobao.org/dist/node/latest-v8.x/node-v8.1.2-linux-x64.tar.xz
5. 解压缩nodejs
xz -d node-v10.15.3-linux-arm64.tar.xz
tar -xvf node-v10.15.3-linux-arm64.tar
6. 配置环境变量
mv node-v10.15.3-linux-arm64 nodejs
mv nodejs /usr/nodejs
vim /etc/profile
export NODE_HOME=/usr/nodejs
export PATH=$PATH:$JAVA_HOME/bin:$NODE_HOME/bin
7. 进入elasticsearch-head的目录
npm config set registry https://registry.npm.taobao.org
npm install
npm run start
8. 编写elastsearch.yml配置文件开启head插件的访问
http.cors.enabled: true
http.cors.allow-origin: "*"
9. 启动访问head插件 默认端口9100
http://ip:9100 查看集群状态
#ES复习复习
[es@localhost elasticsearch-6.2.4]$ ls
bin data LICENSE.txt modules plugins
config lib logs NOTICE.txt README.textile
[es@localhost elasticsearch-6.2.4]$ ll
总用量 224
drwxr-xr-x. 2 es es 4096 10月 21 19:26 bin
drwxr-xr-x. 2 es es 75 10月 21 19:33 config
drwxrwxr-x. 3 es es 19 10月 21 19:30 data
drwxr-xr-x. 2 es es 4096 4月 13 2018 lib
-rw-r--r--. 1 es es 11358 4月 13 2018 LICENSE.txt
drwxr-xr-x. 2 es es 227 10月 22 15:52 logs
drwxr-xr-x. 16 es es 4096 4月 13 2018 modules
-rw-r--r--. 1 es es 191887 4月 13 2018 NOTICE.txt
drwxr-xr-x. 3 es es 27 10月 21 20:49 plugins
-rw-r--r--. 1 es es 9268 4月 13 2018 README.textile
[es@localhost elasticsearch-6.2.4]$ cd bin/
[es@localhost bin]$ ll
总用量 256
-rwxr-xr-x. 1 es es 1557 4月 13 2018 elasticsearch
-rw-r--r--. 1 es es 1431 4月 13 2018 elasticsearch.bat
-rwxr-xr-x. 1 es es 2238 4月 13 2018 elasticsearch-env
-rw-r--r--. 1 es es 1713 4月 13 2018 elasticsearch-env.bat
-rwxr-xr-x. 1 es es 239 4月 13 2018 elasticsearch-keystore
-rw-r--r--. 1 es es 329 4月 13 2018 elasticsearch-keystore.bat
-rwxr-xr-x. 1 es es 229 4月 13 2018 elasticsearch-plugin
-rw-r--r--. 1 es es 319 4月 13 2018 elasticsearch-plugin.bat
-rw-r--r--. 1 es es 8018 4月 13 2018 elasticsearch-service.bat
-rw-r--r--. 1 es es 104448 4月 13 2018 elasticsearch-service-mgr.exe
-rw-r--r--. 1 es es 103936 4月 13 2018 elasticsearch-service-x64.exe
-rwxr-xr-x. 1 es es 242 4月 13 2018 elasticsearch-translog
-rw-r--r--. 1 es es 332 4月 13 2018 elasticsearch-translog.bat
[es@localhost bin]$ ./elasticsearch
2019-12-08 10:16:48,182 main ERROR RollingFileManager (/home/es/elasticsearch-6.2.4/logs/elasticsearch.log) java.io.FileNotFoundException: /home/es/elasticsearch-6.2.4/logs/elasticsearch.log (权限不够) java.io.FileNotFoundException: /home/es/elasticsearch-6.2.4/logs/elasticsearch.log (权限不够)
at java.io.FileOutputStream.open0(Native Method)
at java.io.FileOutputStream.open(FileOutputStream.java:270)
at java.io.FileOutputStream.<init>(FileOutputStream.java:213)
at java.io.FileOutputStream.<init>(FileOutputStream.java:133)
at org.apache.logging.log4j.core.appender.rolling.RollingFileManager$RollingFileManagerFactory.createManager(RollingFileManager.java:640)
at org.apache.logging.log4j.core.appender.rolling.RollingFileManager$RollingFileManagerFactory.createManager(RollingFileManager.java:608)
at org.apache.logging.log4j.core.appender.AbstractManager.getManager(AbstractManager.java:113)
at org.apache.logging.log4j.core.appender.OutputStreamManager.getManager(OutputStreamManager.java:115)
at org.apache.logging.log4j.core.appender.rolling.RollingFileManager.getFileManager(RollingFileManager.java:188)
at org.apache.logging.log4j.core.appender.RollingFileAppender$Builder.build(RollingFileAppender.java:144)
at org.apache.logging.log4j.core.appender.RollingFileAppender$Builder.build(RollingFileAppender.java:60)
at org.apache.logging.log4j.core.config.plugins.util.PluginBuilder.build(PluginBuilder.java:122)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createPluginObject(AbstractConfiguration.java:958)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createConfiguration(AbstractConfiguration.java:898)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createConfiguration(AbstractConfiguration.java:890)
at org.apache.logging.log4j.core.config.AbstractConfiguration.doConfigure(AbstractConfiguration.java:513)
at org.apache.logging.log4j.core.config.AbstractConfiguration.initialize(AbstractConfiguration.java:237)
at org.apache.logging.log4j.core.config.AbstractConfiguration.start(AbstractConfiguration.java:249)
at org.apache.logging.log4j.core.LoggerContext.setConfiguration(LoggerContext.java:545)
at org.apache.logging.log4j.core.LoggerContext.start(LoggerContext.java:261)
at org.elasticsearch.common.logging.LogConfigurator.configure(LogConfigurator.java:163)
at org.elasticsearch.common.logging.LogConfigurator.configure(LogConfigurator.java:119)
at org.elasticsearch.bootstrap.Bootstrap.init(Bootstrap.java:291)
at org.elasticsearch.bootstrap.Elasticsearch.init(Elasticsearch.java:121)
at org.elasticsearch.bootstrap.Elasticsearch.execute(Elasticsearch.java:112)
at org.elasticsearch.cli.EnvironmentAwareCommand.execute(EnvironmentAwareCommand.java:86)
at org.elasticsearch.cli.Command.mainWithoutErrorHandling(Command.java:124)
at org.elasticsearch.cli.Command.main(Command.java:90)
at org.elasticsearch.bootstrap.Elasticsearch.main(Elasticsearch.java:92)
at org.elasticsearch.bootstrap.Elasticsearch.main(Elasticsearch.java:85)
2019-12-08 10:16:48,190 main ERROR Could not create plugin of type class org.apache.logging.log4j.core.appender.RollingFileAppender for element RollingFile: java.lang.IllegalStateException: ManagerFactory [org.apache.logging.log4j.core.appender.rolling.RollingFileManager$RollingFileManagerFactory@1623b78d] unable to create manager for [/home/es/elasticsearch-6.2.4/logs/elasticsearch.log] with data [org.apache.logging.log4j.core.appender.rolling.RollingFileManager$FactoryData@c8c12ac[pattern=/home/es/elasticsearch-6.2.4/logs/elasticsearch-%d{yyyy-MM-dd}-%i.log.gz, append=true, bufferedIO=true, bufferSize=8192, policy=CompositeTriggeringPolicy(policies=[TimeBasedTriggeringPolicy(nextRolloverMillis=0, interval=1, modulate=true), SizeBasedTriggeringPolicy(size=134217728)]), strategy=DefaultRolloverStrategy(min=-2147483648, max=2147483647, useMax=false), advertiseURI=null, layout=[%d{ISO8601}][%-5p][%-25c{1.}] %marker%.-10000m%n, filePermissions=null, fileOwner=null]] java.lang.IllegalStateException: ManagerFactory [org.apache.logging.log4j.core.appender.rolling.RollingFileManager$RollingFileManagerFactory@1623b78d] unable to create manager for [/home/es/elasticsearch-6.2.4/logs/elasticsearch.log] with data [org.apache.logging.log4j.core.appender.rolling.RollingFileManager$FactoryData@c8c12ac[pattern=/home/es/elasticsearch-6.2.4/logs/elasticsearch-%d{yyyy-MM-dd}-%i.log.gz, append=true, bufferedIO=true, bufferSize=8192, policy=CompositeTriggeringPolicy(policies=[TimeBasedTriggeringPolicy(nextRolloverMillis=0, interval=1, modulate=true), SizeBasedTriggeringPolicy(size=134217728)]), strategy=DefaultRolloverStrategy(min=-2147483648, max=2147483647, useMax=false), advertiseURI=null, layout=[%d{ISO8601}][%-5p][%-25c{1.}] %marker%.-10000m%n, filePermissions=null, fileOwner=null]]
at org.apache.logging.log4j.core.appender.AbstractManager.getManager(AbstractManager.java:115)
at org.apache.logging.log4j.core.appender.OutputStreamManager.getManager(OutputStreamManager.java:115)
at org.apache.logging.log4j.core.appender.rolling.RollingFileManager.getFileManager(RollingFileManager.java:188)
at org.apache.logging.log4j.core.appender.RollingFileAppender$Builder.build(RollingFileAppender.java:144)
at org.apache.logging.log4j.core.appender.RollingFileAppender$Builder.build(RollingFileAppender.java:60)
at org.apache.logging.log4j.core.config.plugins.util.PluginBuilder.build(PluginBuilder.java:122)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createPluginObject(AbstractConfiguration.java:958)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createConfiguration(AbstractConfiguration.java:898)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createConfiguration(AbstractConfiguration.java:890)
at org.apache.logging.log4j.core.config.AbstractConfiguration.doConfigure(AbstractConfiguration.java:513)
at org.apache.logging.log4j.core.config.AbstractConfiguration.initialize(AbstractConfiguration.java:237)
at org.apache.logging.log4j.core.config.AbstractConfiguration.start(AbstractConfiguration.java:249)
at org.apache.logging.log4j.core.LoggerContext.setConfiguration(LoggerContext.java:545)
at org.apache.logging.log4j.core.LoggerContext.start(LoggerContext.java:261)
at org.elasticsearch.common.logging.LogConfigurator.configure(LogConfigurator.java:163)
at org.elasticsearch.common.logging.LogConfigurator.configure(LogConfigurator.java:119)
at org.elasticsearch.bootstrap.Bootstrap.init(Bootstrap.java:291)
at org.elasticsearch.bootstrap.Elasticsearch.init(Elasticsearch.java:121)
at org.elasticsearch.bootstrap.Elasticsearch.execute(Elasticsearch.java:112)
at org.elasticsearch.cli.EnvironmentAwareCommand.execute(EnvironmentAwareCommand.java:86)
at org.elasticsearch.cli.Command.mainWithoutErrorHandling(Command.java:124)
at org.elasticsearch.cli.Command.main(Command.java:90)
at org.elasticsearch.bootstrap.Elasticsearch.main(Elasticsearch.java:92)
at org.elasticsearch.bootstrap.Elasticsearch.main(Elasticsearch.java:85)
2019-12-08 10:16:48,217 main ERROR Unable to invoke factory method in class org.apache.logging.log4j.core.appender.RollingFileAppender for element RollingFile: java.lang.IllegalStateException: No factory method found for class org.apache.logging.log4j.core.appender.RollingFileAppender java.lang.IllegalStateException: No factory method found for class org.apache.logging.log4j.core.appender.RollingFileAppender
at org.apache.logging.log4j.core.config.plugins.util.PluginBuilder.findFactoryMethod(PluginBuilder.java:229)
at org.apache.logging.log4j.core.config.plugins.util.PluginBuilder.build(PluginBuilder.java:134)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createPluginObject(AbstractConfiguration.java:958)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createConfiguration(AbstractConfiguration.java:898)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createConfiguration(AbstractConfiguration.java:890)
at org.apache.logging.log4j.core.config.AbstractConfiguration.doConfigure(AbstractConfiguration.java:513)
at org.apache.logging.log4j.core.config.AbstractConfiguration.initialize(AbstractConfiguration.java:237)
at org.apache.logging.log4j.core.config.AbstractConfiguration.start(AbstractConfiguration.java:249)
at org.apache.logging.log4j.core.LoggerContext.setConfiguration(LoggerContext.java:545)
at org.apache.logging.log4j.core.LoggerContext.start(LoggerContext.java:261)
at org.elasticsearch.common.logging.LogConfigurator.configure(LogConfigurator.java:163)
at org.elasticsearch.common.logging.LogConfigurator.configure(LogConfigurator.java:119)
at org.elasticsearch.bootstrap.Bootstrap.init(Bootstrap.java:291)
at org.elasticsearch.bootstrap.Elasticsearch.init(Elasticsearch.java:121)
at org.elasticsearch.bootstrap.Elasticsearch.execute(Elasticsearch.java:112)
at org.elasticsearch.cli.EnvironmentAwareCommand.execute(EnvironmentAwareCommand.java:86)
at org.elasticsearch.cli.Command.mainWithoutErrorHandling(Command.java:124)
at org.elasticsearch.cli.Command.main(Command.java:90)
at org.elasticsearch.bootstrap.Elasticsearch.main(Elasticsearch.java:92)
at org.elasticsearch.bootstrap.Elasticsearch.main(Elasticsearch.java:85)
2019-12-08 10:16:48,289 main ERROR Null object returned for RollingFile in Appenders.
2019-12-08 10:16:48,289 main ERROR Unable to locate appender "rolling" for logger config "root"
[2019-12-08T10:16:49,058][INFO ][o.e.n.Node ] [] initializing ...
[2019-12-08T10:16:49,169][INFO ][o.e.e.NodeEnvironment ] [0aMwy_g] using [1] data paths, mounts [[/ (rootfs)]], net usable_space [12.3gb], net total_space [16.9gb], types [rootfs]
[2019-12-08T10:16:49,169][INFO ][o.e.e.NodeEnvironment ] [0aMwy_g] heap size [1015.6mb], compressed ordinary object pointers [true]
[2019-12-08T10:16:49,197][INFO ][o.e.n.Node ] node name [0aMwy_g] derived from node ID [0aMwy_giSjiGAWQl5DIGzg]; set [node.name] to override
[2019-12-08T10:16:49,197][INFO ][o.e.n.Node ] version[6.2.4], pid[9541], build[ccec39f/2018-04-12T20:37:28.497551Z], OS[Linux/3.10.0-862.el7.x86_64/amd64], JVM[Oracle Corporation/Java HotSpot(TM) 64-Bit Server VM/1.8.0_171/25.171-b11]
[2019-12-08T10:16:49,197][INFO ][o.e.n.Node ] JVM arguments [-Xms1g, -Xmx1g, -XX:+UseConcMarkSweepGC, -XX:CMSInitiatingOccupancyFraction=75, -XX:+UseCMSInitiatingOccupancyOnly, -XX:+AlwaysPreTouch, -Xss1m, -Djava.awt.headless=true, -Dfile.encoding=UTF-8, -Djna.nosys=true, -XX:-OmitStackTraceInFastThrow, -Dio.netty.noUnsafe=true, -Dio.netty.noKeySetOptimization=true, -Dio.netty.recycler.maxCapacityPerThread=0, -Dlog4j.shutdownHookEnabled=false, -Dlog4j2.disable.jmx=true, -Djava.io.tmpdir=/tmp/elasticsearch.kPokvNFT, -XX:+HeapDumpOnOutOfMemoryError, -XX:+PrintGCDetails, -XX:+PrintGCDateStamps, -XX:+PrintTenuringDistribution, -XX:+PrintGCApplicationStoppedTime, -Xloggc:logs/gc.log, -XX:+UseGCLogFileRotation, -XX:NumberOfGCLogFiles=32, -XX:GCLogFileSize=64m, -Des.path.home=/home/es/elasticsearch-6.2.4, -Des.path.conf=/home/es/elasticsearch-6.2.4/config]
[2019-12-08T10:16:51,012][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [aggs-matrix-stats]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [analysis-common]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [ingest-common]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [lang-expression]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [lang-mustache]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [lang-painless]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [mapper-extras]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [parent-join]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [percolator]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [rank-eval]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [reindex]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [repository-url]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [transport-netty4]
[2019-12-08T10:16:51,013][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [tribe]
[2019-12-08T10:16:51,014][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded plugin [analysis-ik]
[2019-12-08T10:16:57,443][INFO ][o.e.d.DiscoveryModule ] [0aMwy_g] using discovery type [zen]
[2019-12-08T10:16:58,538][INFO ][o.e.n.Node ] initialized
[2019-12-08T10:16:58,538][INFO ][o.e.n.Node ] [0aMwy_g] starting ...
[2019-12-08T10:16:58,803][INFO ][o.e.t.TransportService ] [0aMwy_g] publish_address {192.168.89.14:9300}, bound_addresses {[::]:9300}
[2019-12-08T10:16:58,834][INFO ][o.e.b.BootstrapChecks ] [0aMwy_g] bound or publishing to a non-loopback address, enforcing bootstrap checks
[2019-12-08T10:17:01,939][INFO ][o.e.c.s.MasterService ] [0aMwy_g] zen-disco-elected-as-master ([0] nodes joined), reason: new_master {0aMwy_g}{0aMwy_giSjiGAWQl5DIGzg}{UBW98KnsRU2VhJetwC0FpA}{192.168.89.14}{192.168.89.14:9300}
[2019-12-08T10:17:01,946][INFO ][o.e.c.s.ClusterApplierService] [0aMwy_g] new_master {0aMwy_g}{0aMwy_giSjiGAWQl5DIGzg}{UBW98KnsRU2VhJetwC0FpA}{192.168.89.14}{192.168.89.14:9300}, reason: apply cluster state (from master [master {0aMwy_g}{0aMwy_giSjiGAWQl5DIGzg}{UBW98KnsRU2VhJetwC0FpA}{192.168.89.14}{192.168.89.14:9300} committed version [1] source [zen-disco-elected-as-master ([0] nodes joined)]])
[2019-12-08T10:17:01,995][INFO ][o.e.h.n.Netty4HttpServerTransport] [0aMwy_g] publish_address {192.168.89.14:9200}, bound_addresses {[::]:9200}
[2019-12-08T10:17:01,995][INFO ][o.e.n.Node ] [0aMwy_g] started
[2019-12-08T10:17:02,278][INFO ][o.w.a.d.Monitor ] try load config from /home/es/elasticsearch-6.2.4/config/analysis-ik/IKAnalyzer.cfg.xml
[2019-12-08T10:17:02,282][INFO ][o.w.a.d.Monitor ] try load config from /home/es/elasticsearch-6.2.4/plugins/elasticsearch/config/IKAnalyzer.cfg.xml
[2019-12-08T10:17:03,160][INFO ][o.e.g.GatewayService ] [0aMwy_g] recovered [1] indices into cluster_state
[2019-12-08T10:17:03,589][INFO ][o.e.c.r.a.AllocationService] [0aMwy_g] Cluster health status changed from [RED] to [YELLOW] (reason: [shards started [[dangdang][1]] ...]).
#复习
#查看创建的组合用户
[root@localhost es]# cd /home/
[root@localhost home]# ll
总用量 0
drwx------. 4 es es 114 10月 21 19:30 es
#复习
#ES的一个目录
#普通用户的家目录是home下ES
#超级用户的家目录目录的/root
[root@localhost home]# cd es/
[root@localhost es]# pwd
/home/es
[root@localhost es]#
#复习
#超级用户的家目录是/root
[root@localhost es]# cd ..
[root@localhost home]# cd /root/
[root@localhost ~]# ll
总用量 484484
drwxr-xr-x. 2 root root 6 10月 21 19:22 3000soft
drwxr-xr-x. 2 root root 222 10月 21 19:22 360极速浏览器下载
drwxr-xr-x. 2 root root 53 10月 2 19:45 apache-maven-3.6.1
drwxr-xr-x. 2 root root 75 10月 2 19:45 apache-tomcat-6.0.36
-rw-r--r--. 1 root root 9138957 4月 3 2019 apache-tomcat-7.0.93.tar.gz
drwxr-xr-x. 2 root root 75 10月 2 19:45 apache-tomcat-8.5.30
drwxr-xr-x. 2 root root 6 10月 2 19:45 BaiduNetdiskDownload
drwxr-xr-x. 2 root root 6 10月 2 19:45 baiduyudisk
drwxr-xr-x. 2 root root 4096 10月 21 19:24 CentOS_Hadoop1
drwxr-xr-x. 2 root root 184 10月 21 19:24 CentOS_Hadoop3
drwxr-xr-x. 2 root root 6 10月 21 19:24 client
drwxr-xr-x. 2 root root 6 10月 2 19:45 Config.Msi
-rw-r--r--. 1 root root 29056810 4月 3 2019 elasticsearch-6.2.4.tar.gz
-rw-r--r--. 1 root root 4501977 4月 3 2019 elasticsearch-analysis-ik-6.2.4.z ip
-rw-r--r--. 1 root root 425 10月 2 09:41 HelloWorld.class
-rw-r--r--. 1 root root 112 10月 12 21:42 HelloWorld.java
-rw-r--r--. 1 root root 175262413 4月 3 2019 jdk-8u171-linux-x64.rpm
-rw-r--r--. 1 root root 190890122 4月 3 2019 jdk-8u171-linux-x64.tar.gz
-rw-r--r--. 1 root root 87218216 4月 3 2019 kibana-6.2.4-x86_64.rpm
-rw-r--r--. 1 root root 186 10月 12 16:34 mby.txt
drwxr-xr-x. 2 root root 4096 10月 2 21:23 mysql
drwxr-xr-x. 2 root root 6 10月 2 19:45 $RECYCLE.BIN
-rw-r--r--. 1 root root 0 10月 3 13:36 Speed.log
-rw-r--r--. 1 root root 49 10月 10 15:57 suns.txt
-rw-r--r--. 1 root root 30 10月 10 16:04 xiaojr.txt
#复习
#设置用户的新密码
#设置的密码为es
[root@localhost ~]# passwd es
更改用户 es 的密码 。
新的 密码：
无效的密码： 密码少于 8 个字符
重新输入新的 密码：
passwd：所有的身份验证令牌已经成功更新。
#复习
#以es用户的身份登录
login as: es
es@192.168.89.129's password:
┌────────────────────────────────────────────────────────────────────┐
│ • MobaXterm 11.0 • │
│ (SSH client, X-server and networking tools) │
│ │
│ ➤ SSH session to es@192.168.89.129 │
│ • SSH compression : ✔ │
│ • SSH-browser : ✔ │
│ • X11-forwarding : ✘ (disabled or not supported by server) │
│ • DISPLAY : 192.168.43.55:0.0 │
│ │
│ ➤ For more info, ctrl+click on help or visit our website │
└────────────────────────────────────────────────────────────────────┘
Last login: Sun Dec 8 10:05:09 2019
[es@localhost ~]$
#复习
#更改权限
[root@localhost home]# chown -R es:es /home/es/elasticsearch-6.2.4/
#复习
#启动ES
[es@localhost bin]$ ./elasticsearch
[2019-12-08T10:52:05,076][INFO ][o.e.n.Node ] [] initializing ...
[2019-12-08T10:52:05,213][INFO ][o.e.e.NodeEnvironment ] [0aMwy_g] using [1] data paths, mounts [[/ (rootfs)]], net usable_space [12.3gb], net total_space [16.9gb], types [rootfs]
[2019-12-08T10:52:05,213][INFO ][o.e.e.NodeEnvironment ] [0aMwy_g] heap size [1015.6mb], compressed ordinary object pointers [true]
[2019-12-08T10:52:05,244][INFO ][o.e.n.Node ] node name [0aMwy_g] derived from node ID [0aMwy_giSjiGAWQl5DIGzg]; set [node.name] to override
[2019-12-08T10:52:05,244][INFO ][o.e.n.Node ] version[6.2.4], pid[23861], build[ccec39f/2018-04-12T20:37:28.497551Z], OS[Linux/3.10.0-862.el7.x86_64/amd64], JVM[Oracle Corporation/Java HotSpot(TM) 64-Bit Server VM/1.8.0_171/25.171-b11]
[2019-12-08T10:52:05,244][INFO ][o.e.n.Node ] JVM arguments [-Xms1g, -Xmx1g, -XX:+UseConcMarkSweepGC, -XX:CMSInitiatingOccupancyFraction=75, -XX:+UseCMSInitiatingOccupancyOnly, -XX:+AlwaysPreTouch, -Xss1m, -Djava.awt.headless=true, -Dfile.encoding=UTF-8, -Djna.nosys=true, -XX:-OmitStackTraceInFastThrow, -Dio.netty.noUnsafe=true, -Dio.netty.noKeySetOptimization=true, -Dio.netty.recycler.maxCapacityPerThread=0, -Dlog4j.shutdownHookEnabled=false, -Dlog4j2.disable.jmx=true, -Djava.io.tmpdir=/tmp/elasticsearch.Grgu6zkr, -XX:+HeapDumpOnOutOfMemoryError, -XX:+PrintGCDetails, -XX:+PrintGCDateStamps, -XX:+PrintTenuringDistribution, -XX:+PrintGCApplicationStoppedTime, -Xloggc:logs/gc.log, -XX:+UseGCLogFileRotation, -XX:NumberOfGCLogFiles=32, -XX:GCLogFileSize=64m, -Des.path.home=/home/es/elasticsearch-6.2.4, -Des.path.conf=/home/es/elasticsearch-6.2.4/config]
[2019-12-08T10:52:07,116][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [aggs-matrix-stats]
[2019-12-08T10:52:07,116][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [analysis-common]
[2019-12-08T10:52:07,116][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [ingest-common]
[2019-12-08T10:52:07,116][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [lang-expression]
[2019-12-08T10:52:07,116][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [lang-mustache]
[2019-12-08T10:52:07,117][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [lang-painless]
[2019-12-08T10:52:07,117][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [mapper-extras]
[2019-12-08T10:52:07,117][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [parent-join]
[2019-12-08T10:52:07,117][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [percolator]
[2019-12-08T10:52:07,117][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [rank-eval]
[2019-12-08T10:52:07,117][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [reindex]
[2019-12-08T10:52:07,118][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [repository-url]
[2019-12-08T10:52:07,118][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [transport-netty4]
[2019-12-08T10:52:07,118][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded module [tribe]
[2019-12-08T10:52:07,119][INFO ][o.e.p.PluginsService ] [0aMwy_g] loaded plugin [analysis-ik]
[2019-12-08T10:52:13,279][INFO ][o.e.d.DiscoveryModule ] [0aMwy_g] using discovery type [zen]
[2019-12-08T10:52:14,480][INFO ][o.e.n.Node ] initialized
[2019-12-08T10:52:14,480][INFO ][o.e.n.Node ] [0aMwy_g] starting ...
[2019-12-08T10:52:14,755][INFO ][o.e.t.TransportService ] [0aMwy_g] publish_address {192.168.89.14:9300}, bound_addresses {[::]:9300}
[2019-12-08T10:52:14,795][INFO ][o.e.b.BootstrapChecks ] [0aMwy_g] bound or publishing to a non-loopback address, enforcing bootstrap checks
[2019-12-08T10:52:17,904][INFO ][o.e.c.s.MasterService ] [0aMwy_g] zen-disco-elected-as-master ([0] nodes joined), reason: new_master {0aMwy_g}{0aMwy_giSjiGAWQl5DIGzg}{Ls22wg8LR1iDZopBh5Dz7g}{192.168.89.14}{192.168.89.14:9300}
[2019-12-08T10:52:17,911][INFO ][o.e.c.s.ClusterApplierService] [0aMwy_g] new_master {0aMwy_g}{0aMwy_giSjiGAWQl5DIGzg}{Ls22wg8LR1iDZopBh5Dz7g}{192.168.89.14}{192.168.89.14:9300}, reason: apply cluster state (from master [master {0aMwy_g}{0aMwy_giSjiGAWQl5DIGzg}{Ls22wg8LR1iDZopBh5Dz7g}{192.168.89.14}{192.168.89.14:9300} committed version [1] source [zen-disco-elected-as-master ([0] nodes joined)]])
[2019-12-08T10:52:17,982][INFO ][o.e.h.n.Netty4HttpServerTransport] [0aMwy_g] publish_address {192.168.89.14:9200}, bound_addresses {[::]:9200}
[2019-12-08T10:52:17,982][INFO ][o.e.n.Node ] [0aMwy_g] started #观察此处，表示已经启动
[2019-12-08T10:52:18,021][INFO ][o.w.a.d.Monitor ] try load config from /home/es/elasticsearch-6.2.4/config/analysis-ik/IKAnalyzer.cfg.xml
[2019-12-08T10:52:18,025][INFO ][o.w.a.d.Monitor ] try load config from /home/es/elasticsearch-6.2.4/plugins/elasticsearch/config/IKAnalyzer.cfg.xml
[2019-12-08T10:52:18,971][INFO ][o.e.g.GatewayService ] [0aMwy_g] recovered [1] indices into cluster_state
[2019-12-08T10:52:19,616][INFO ][o.e.c.r.a.AllocationService] [0aMwy_g] Cluster health status changed from [RED] to [YELLOW] (reason: [shards started [[dangdang][3]] ...]).
#复习
#启动
#crul 利用黑窗口测试
#curl http://localhost:9200
# 和浏览器写这个玩意是一样的
login as: es
┌────────────────────────────────────────────────────────────────────┐
│ • MobaXterm 11.0 • │
│ (SSH client, X-server and networking tools) │
│ │
│ ➤ SSH session to es@192.168.89.129 │
│ • SSH compression : ✔ │
│ • SSH-browser : ✔ │
│ • X11-forwarding : ✘ (disabled or not supported by server) │
│ • DISPLAY : 192.168.43.55:0.0 │
│ │
│ ➤ For more info, ctrl+click on help or visit our website │
└────────────────────────────────────────────────────────────────────┘
Last login: Sun Dec 8 10:35:25 2019 from 192.168.89.1
[es@localhost ~]$ curl http://localhost:9200
{
"name" : "0aMwy_g",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "o_iFmaxwQcSVILmTpARJZQ",
"version" : {
"number" : "6.2.4",
"build_hash" : "ccec39f",
"build_date" : "2018-04-12T20:37:28.497551Z",
"build_snapshot" : false,
"lucene_version" : "7.2.1",
"minimum_wire_compatibility_version" : "5.6.0",
"minimum_index_compatibility_version" : "5.0.0"
},
"tagline" : "You Know, for Search"
}
#复习
[root@localhost home]# systemctl status firewalld
● firewalld.service - firewalld - dynamic firewall daemon
Loaded: loaded (/usr/lib/systemd/system/firewalld.service; disabled; vendor preset: enabled)
Active: inactive (dead)
Docs: man:firewalld(1)
[root@localhost home]# systemctl stop firewalld
[root@localhost home]# systemctl status firewalld
● firewalld.service - firewalld - dynamic firewall daemon
Loaded: loaded (/usr/lib/systemd/system/firewalld.service; disabled; vendor preset: enabled)
Active: inactive (dead)
Docs: man:firewalld(1)
#复习
#WEBUI 界面访问 --- 需要·修改一个·配置·文件·
http://192.168.89.129:9200/
{
"name" : "0aMwy_g",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "o_iFmaxwQcSVILmTpARJZQ",
"version" : {
"number" : "6.2.4",
"build_hash" : "ccec39f",
"build_date" : "2018-04-12T20:37:28.497551Z",
"build_snapshot" : false,
"lucene_version" : "7.2.1",
"minimum_wire_compatibility_version" : "5.6.0",
"minimum_index_compatibility_version" : "5.0.0"
},
"tagline" : "You Know, for Search"
}
#复习
#找到kibana 并且启动它
[root@localhost usr]# find / -name kibana
/etc/rc.d/init.d/kibana
/etc/default/kibana
/etc/kibana
/var/lib/kibana
/usr/share/kibana
/usr/share/kibana/bin/kibana
/usr/share/kibana/node_modules/@elastic/eui/src-docs/src/views/kibana
/usr/share/kibana/src/core_plugins/kibana
[root@localhost usr]# cd
[root@localhost ~]# \
>
[root@localhost ~]#
[root@localhost ~]# clear
[root@localhost ~]# cd /usr/
[root@localhost usr]# ls
bin games java lib libexec sbin src tomcat7
etc include jdk1.8.0_171 lib64 local share tmp
[root@localhost usr]# cd share/
[root@localhost share]# ls
aclocal games kdump polkit-1
alsa gcc-4.8.2 kibana redhat-release
anaconda gcc-4.8.5 libdrm selinux
applications gdb licenses sounds
augeas GeoIP locale systemd
authconfig gettext lua systemtap
awk gettext-0.19.8 magic tabset
backgrounds ghostscript man terminfo
bash-completion glib-2.0 mime themes
centos-logos gnome mime-info tuned
centos-release gnome-background-properties misc vim
cracklib gnupg mysql wallpapers
dbus-1 groff omf X11
desktop-directories grub os-prober xsessions
dict hwdata p11-kit yum-cli
doc i18n perl5 yum-plugins
empty icons pixmaps zoneinfo
file idl pkgconfig zsh
firewalld info pki
firstboot kde4 plymouth
[root@localhost share]# cd kibana/
[root@localhost kibana]# ls
bin node NOTICE.txt package.json README.txt ui_framework
LICENSE.txt node_modules optimize plugins src webpackShims
[root@localhost kibana]# systemctl start kibana
[root@localhost kibana]# jps
23861 Elasticsearch
37871 Jps
#复习
#修改配置文件
[root@localhost kibana]# more kibana.yml
# Kibana is served by a back end server. This setting specifies the port to use.
#server.port: 5601
# Specifies the address to which the Kibana server will bind. IP addresses and h
ost names are both valid values.
# The default is 'localhost', which usually means remote machines will not be ab
le to connect.
# To allow connections from remote users, set this parameter to a non-loopback a
ddress.
server.host: "192.168.89.129" #修改连接es的主机名，极其重要
# Enables you to specify a path to mount Kibana at if you are running behind a p
roxy. This only affects
# the URLs generated by Kibana, your proxy is expected to remove the basePath va
lue before forwarding requests
# to Kibana. This setting cannot end in a slash.
#server.basePath: ""
# The maximum payload size in bytes for incoming server requests.
#server.maxPayloadBytes: 1048576
# The Kibana server's name. This is used for display purposes.
#server.name: "your-hostname"
# The URL of the Elasticsearch instance to use for all your queries.
#elasticsearch.url: "http://192.168.89.14:9200" #极其重要
# When this setting's value is true Kibana uses the hostname specified in the server.host
# setting. When the value of this setting is false, Kibana uses the hostname of the host
# that connects to this Kibana instance.
#elasticsearch.preserveHost: true
# Kibana uses an index in Elasticsearch to store saved searches, visualizations and
# dashboards. Kibana creates a new index if the index doesn't already exist.
#kibana.index: ".kibana"
# The default application to load.
#kibana.defaultAppId: "home"
# If your Elasticsearch is protected with basic authentication, these settings provide
# the username and password that the Kibana server uses to perform maintenance on the Kibana
# index at startup. Your Kibana users still need to authenticate with Elasticsearch, which
# is proxied through the Kibana server.
#elasticsearch.username: "user"
#elasticsearch.password: "pass"
# Enables SSL and paths to the PEM-format SSL certificate and SSL key files, respectively.
# These settings enable SSL for outgoing requests from the Kibana server to the browser.
#server.ssl.enabled: false
#server.ssl.certificate: /path/to/your/server.crt
#server.ssl.key: /path/to/your/server.key
# Optional settings that provide the paths to the PEM-format SSL certificate and key files.
# These files validate that your Elasticsearch backend uses the same key files.
#elasticsearch.ssl.certificate: /path/to/your/client.crt
#elasticsearch.ssl.key: /path/to/your/client.key
# Optional setting that enables you to specify a path to the PEM file for the certificate
# authority for your Elasticsearch instance.
#elasticsearch.ssl.certificateAuthorities: [ "/path/to/your/CA.pem" ]
# To disregard the validity of SSL certificates, change this setting's value to 'none'.
#elasticsearch.ssl.verificationMode: full
# Time in milliseconds to wait for Elasticsearch to respond to pings. Defaults to the value of
# the elasticsearch.requestTimeout setting.
#elasticsearch.pingTimeout: 1500
# Time in milliseconds to wait for responses from the back end or Elasticsearch. This value
# must be a positive integer.
#elasticsearch.requestTimeout: 30000
# List of Kibana client-side headers to send to Elasticsearch. To send *no* client-side
# headers, set this value to [] (an empty list).
#elasticsearch.requestHeadersWhitelist: [ authorization ]
# Header names and values that are sent to Elasticsearch. Any custom headers cannot be overwritten
# by client-side headers, regardless of the elasticsearch.requestHeadersWhitelist configuration.
#elasticsearch.customHeaders: {}
# Time in milliseconds for Elasticsearch to wait for responses from shards. Set to 0 to disable.
#elasticsearch.shardTimeout: 0
# Time in milliseconds to wait for Elasticsearch at Kibana startup before retrying.
#elasticsearch.startupTimeout: 5000
# Specifies the path where Kibana creates the process ID file.
#pid.file: /var/run/kibana.pid
# Enables you specify a file where Kibana stores log output.
#logging.dest: stdout
# Set the value of this setting to true to suppress all logging output.
#logging.silent: false
# Set the value of this setting to true to suppress all logging output other than error messages.
#logging.quiet: false
# Set the value of this setting to true to log all events, including system usage information
# and all requests.
#logging.verbose: false
# Set the interval in milliseconds to sample system and process performance
# metrics. Minimum is 100ms. Defaults to 5000.
#ops.interval: 5000
# The default locale. This locale can be used in certain circumstances to substitute any missing
# translations.
#i18n.defaultLocale: "en"
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