Elasticsearch 6.3.1 地址：

  1. wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-6.3.1.tar.gz

2.安装配置

1.拷贝

拷贝到服务器上，解压：tar -xvzf elasticsearch-6.3.1.tar.gz 。解压后路径：/home/elasticsearch-6.3.1

3.创建用户

创建用户，创建esdata目录，并赋予权限

  1. [root@bogon home]# adduser esuser
  2. [root@bogon home]# cd /home
  3. [root@bogon home]# mkdir -p esdata/data
  4. [root@bogon home]# mkdir -p esdata/log
  5. [root@bogon home]# chown -R esuser elasticsearch-6.3.1
  6. [root@bogon home]# chown -R esuser esdata

4.配置es节点

[root@bogon esdata]# cat /home/elasticsearch-6.3.1/config/elasticsearch.yml
# ======================== Elasticsearch Configuration =========================
#
# NOTE: Elasticsearch comes with reasonable defaults for most settings.
#       Before you set out to tweak and tune the configuration, make sure you
#       understand what are you trying to accomplish and the consequences.
#
# The primary way of configuring a node is via this file. This template lists
# the most important settings you may want to configure for a production cluster.
#
# Please consult the documentation for further information on configuration options:
# https://www.elastic.co/guide/en/elasticsearch/reference/index.html
#
# ---------------------------------- Cluster -----------------------------------
#
# Use a descriptive name for your cluster:
#
cluster.name: my-application
#
# ------------------------------------ Node ------------------------------------
#
# Use a descriptive name for the node:
#
node.name: node-1
#
# Add custom attributes to the node:
#
node.attr.rack: r1
#
# ----------------------------------- Paths ------------------------------------
#
# Path to directory where to store the data (separate multiple locations by comma):
#
path.data: /home/esdata/data
#
# Path to log files:
#
path.logs: /home/esdata/log
#
# ----------------------------------- Memory -----------------------------------
#
# Lock the memory on startup:
#
bootstrap.memory_lock: true
#
# Make sure that the heap size is set to about half the memory available
# on the system and that the owner of the process is allowed to use this
# limit.
#
# Elasticsearch performs poorly when the system is swapping the memory.
#
# ---------------------------------- Network -----------------------------------
#
# Set the bind address to a specific IP (IPv4 or IPv6):
# 允许访问的ip,0.0.0.0表示任意ip可以访问
network.host: 0.0.0.0
#
# Set a custom port for HTTP:
# 对外端口
http.port: 9200
#
# For more information, consult the network module documentation.
#
# --------------------------------- Discovery ----------------------------------
#
# Pass an initial list of hosts to perform discovery when new node is started:
# The default list of hosts is ["127.0.0.1", "[::1]"]
# 集群其他节点IP，只有一个节点写本机ip
discovery.zen.ping.unicast.hosts: ["host1", "host2"]
#
# Prevent the "split brain" by configuring the majority of nodes (total number of master-eligible nodes / 2 + 1):
#
#discovery.zen.minimum_master_nodes:
#
# For more information, consult the zen discovery module documentation.
#
# ---------------------------------- Gateway -----------------------------------
#
# Block initial recovery after a full cluster restart until N nodes are started:
# 集群节点数量
gateway.recover_after_nodes: 1
#
# For more information, consult the gateway module documentation.
#
# ---------------------------------- Various -----------------------------------
#
# Require explicit names when deleting indices:
#
action.destructive_requires_name: true

3.配置系统参数

  1. [root@bogon bin]#  vim /etc/security/limits.conf（在文件最后添加）
  2. esuser hard nofile 65536
  3. esuser soft nofile 65536
  4. esuser soft memlock unlimited
  5. esuser hard memlock unlimited

以上配置解决问题：

  1. max file descriptors [4096] for elasticsearch process is too low, increase to at least [65536]
  2. memory locking requested for elasticsearch process but memory is not locked
  1. 临时设置：sysctl -w vm.max_map_count=262144
    永久修改：
    修改vim /etc/sysctl.conf 文件，添加 “vm.max_map_count”设置
    并执行：sysctl -p

以上配置解决问题：

  1. max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]
  1. [root@bogon logs]# visudo
  2. 。。。。。。。。
  3. ## Allow root to run any commands anywhere
  4. root    ALL=(ALL)       ALL
  5. esuser  ALL=(ALL)       ALL
  6. 。。。。。。。。

以上配置解决某些情况下无法读写的问题

1.ulimit -n和-u可以查看linux的最大进程数和最大文件打开数

1、vim /etc/security/limits.d/90-nproc.conf文件尾添加

  1. * soft nproc 204800
  2. * hard nproc 204800

　　

2、vim /etc/security/limits.d/def.conf文件尾添加

  1. * soft nofile 204800
  2. * hard nofile 204800

　　

这两个文件的设置将会覆盖前面的设置。重启后生效

  1. 以上配置解决问题：max number of threads [3895] for user [esuser] is too low, increase to at least [4096]

问题一：警告提示

[2016-11-06T16:27:21,712][WARN ][o.e.b.JNANatives ] unable to install syscall filter:

java.lang.UnsupportedOperationException: seccomp unavailable: requires kernel 3.5+ with CONFIG_SECCOMP and CONFIG_SECCOMP_FILTER compiled in
at org.elasticsearch.bootstrap.Seccomp.linuxImpl(Seccomp.java:349) ~[elasticsearch-5.0.0.jar:5.0.0]
at org.elasticsearch.bootstrap.Seccomp.init(Seccomp.java:630) ~[elasticsearch-5.0.0.jar:5.0.0]

报了一大串错误，其实只是一个警告。

解决：使用新的centOS版本，centOS7就不会出现此类问题了。

问题二：报错

报错：
ERROR: bootstrap checks failed
system call filters failed to install; check the logs and fix your configuration or disable system call filters at your own risk

原因：
这是在因为Centos6不支持SecComp，而ES5.2.0默认bootstrap.system_call_filter为true进行检测，所以导致检测失败，失败后直接导致ES不能启动。

解决：
在elasticsearch.yml中配置bootstrap.system_call_filter为false，注意要在Memory下面:
bootstrap.memory_lock: false
bootstrap.system_call_filter: false

4.启动

  1. [root@bogon ~]# cd /home/elasticsearch-6.3.1/bin/
  2. [root@bogon bin]# su esuser
  3. [esuser@bogon bin]$ ./elasticsearch
  4. [2018-07-17T10:17:30,139][INFO ][o.e.n.Node               ] [node-1] initializing ...
  5. [2018-07-17T10:17:30,234][INFO ][o.e.e.NodeEnvironment    ] [node-1] using [1] data paths, mounts [[/ (rootfs)]], net usable_space [22.1gb], net total_space [27.6gb], types [rootfs]
  6. [2018-07-17T10:17:30,234][INFO ][o.e.e.NodeEnvironment    ] [node-1] heap size [1007.3mb], compressed ordinary object pointers [true]
  7. [2018-07-17T10:17:30,236][INFO ][o.e.n.Node               ] [node-1] node name [node-1], node ID [cb69e4JjSBKeHJ9y-q-hNA]
  8. [2018-07-17T10:17:30,236][INFO ][o.e.n.Node               ] [node-1] version[6.3.1], pid[26327], build[default/tar/eb782d0/2018-06-29T21:59:26.107521Z], OS[Linux/3.10.0-514.6.1.el7.x86_64/amd64], JVM[Oracle Corporation/Java HotSpot(TM) 64-Bit Server VM/1.8.0_92/25.92-b14]
  9. [2018-07-17T10:17:30,236][INFO ][o.e.n.Node               ] [node-1] 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.F1Jh0AOB, -XX:+HeapDumpOnOutOfMemoryError, -XX:HeapDumpPath=data, -XX:ErrorFile=logs/hs_err_pid%p.log, -XX:+PrintGCDetails, -XX:+PrintGCDateStamps, -XX:+PrintTenuringDistribution, -XX:+PrintGCApplicationStoppedTime, -Xloggc:logs/gc.log, -XX:+UseGCLogFileRotation, -XX:NumberOfGCLogFiles=32, -XX:GCLogFileSize=64m, -Des.path.home=/home/elasticsearch-6.3.1, -Des.path.conf=/home/elasticsearch-6.3.1/config, -Des.distribution.flavor=default, -Des.distribution.type=tar]
  10. [2018-07-17T10:17:33,136][INFO ][o.e.p.PluginsService     ] [node-1] loaded module [aggs-matrix-stats]
  11. [2018-07-17T10:17:33,136][INFO ][o.e.p.PluginsService     ] [node-1] loaded module [analysis-common]
  12. [2018-07-17T10:17:33,137][INFO ][o.e.p.PluginsService     ] [node-1] loaded module [ingest-common]
  13. 。。。。。。

5.验证

浏览器访问：http://192.168.20.115:9200/  （192.168.20.115是es服务器的IP，另外请确保9200端口能够被外部访问），返回：

  1. {
  2.   "name" : "node-1",
  3.   "cluster_name" : "my-application",
  4.   "cluster_uuid" : "_na_",
  5.   "version" : {
  6.     "number" : "6.3.1",
  7.     "build_flavor" : "default",
  8.     "build_type" : "tar",
  9.     "build_hash" : "eb782d0",
  10.     "build_date" : "2018-06-29T21:59:26.107521Z",
  11.     "build_snapshot" : false,
  12.     "lucene_version" : "7.3.1",
  13.     "minimum_wire_compatibility_version" : "5.6.0",
  14.     "minimum_index_compatibility_version" : "5.0.0"
  15.   },
  16.   "tagline" : "You Know, for Search"
  17. }

当然最方便的安装方法还是下载docker镜像，官方安装手册：https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html  步骤：

1）下载镜像：docker pull docker.elastic.co/elasticsearch/elasticsearch:6.3.1

2）运行容器：docker run -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:6.3.1

6.ElasticSearch Head安装

官方的模拟工具是控制台的curl，不是很直观，可以在chrome浏览器中安装head插件来作为请求的工具：head插件的地址：Cenos7安装ES head6.3.1

七、集成集成Ikanalyzer分词器

1. 获取 ES-IKAnalyzer插件

一定和ES的版本一致（ 6.3.1)

地址： https://github.com/medcl/elasticsearch-analysis-ik/releases

2. 安装插件

将 ik 的压缩包解压到 ES安装目录的plugins/目录下（最好把解出的目录名改一下，防止安装别的插件时同名冲突），然后重启ES。

3. 扩展词库

扩展词典可以修改配置文件config/IKAnalyzer.cfg.xml

  1. <?xml version="1.0" encoding="UTF-8"?>
  2. <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd">
  3. <properties>
  4.     <comment>IK Analyzer 扩展配置</comment>
  5.     <!--用户可以在这里配置自己的扩展字典 -->
  6.     <entry key="ext_dict">custom/mydict.dic;custom/single_word_low_freq.dic</entry>
  7.      <!--用户可以在这里配置自己的扩展停止词字典-->
  8.     <entry key="ext_stopwords">custom/ext_stopword.dic</entry>
  9.     <!--用户可以在这里配置远程扩展字典 远程词库，可热更新，在一处地方维护-->
  10.     <!-- <entry key="remote_ext_dict">words_location</entry> -->
  11.     <!--用户可以在这里配置远程扩展停止词字典-->
  12.     <!-- <entry key="remote_ext_stopwords">words_location</entry> -->
  13. </properties>

4. 测试 IK

1、创建一个索引

  1. http://start.com:9200/iktest
  2. {
  3.     "mappings":{
  4.         "_doc":{
  5.                 "properties": {
  6.                 "content": {
  7.                 "type": "text",
  8.                 "analyzer": "ik_max_word",
  9.                 "search_analyzer": "ik_max_word"
  10.                 }
  11.             }
  12.         }
  13.  
  14.     }
  15. }

2.分词测试

  1. http://start.com:9200/_analyze
  2. {
  3.   "analyzer":"ik_smart",
  4.   "text":"天团S.H.E昨在两厅院艺文广场举办17万人露天音乐会，3人献唱多首经典好歌，让现场粉丝听得如痴如醉"
  5. }

结果：

  1. {
  2.     "tokens": [
  3.         {
  4.             "token": "天",
  5.             "start_offset": ,
  6.             "end_offset": ,
  7.             "type": "CN_CHAR",
  8.             "position":
  9.         },
  10.         {
  11.             "token": "团",
  12.             "start_offset": ,
  13.             "end_offset": ,
  14.             "type": "CN_CHAR",
  15.             "position":
  16.         },
  17.         {
  18.             "token": "s.h.e",
  19.             "start_offset": ,
  20.             "end_offset": ,
  21.             "type": "LETTER",
  22.             "position":
  23.         },
  24.         {
  25.             "token": "昨在",
  26.             "start_offset": ,
  27.             "end_offset": ,
  28.             "type": "CN_WORD",
  29.             "position":
  30.         },
  31.         {
  32.             "token": "两厅",
  33.             "start_offset": ,
  34.             "end_offset": ,
  35.             "type": "CN_WORD",
  36.             "position":
  37.         },
  38.         {
  39.             "token": "院",
  40.             "start_offset": ,
  41.             "end_offset": ,
  42.             "type": "CN_CHAR",
  43.             "position":
  44.         },
  45.         {
  46.             "token": "艺文",
  47.             "start_offset": ,
  48.             "end_offset": ,
  49.             "type": "CN_WORD",
  50.             "position":
  51.         },
  52.         {
  53.             "token": "广场",
  54.             "start_offset": ,
  55.             "end_offset": ,
  56.             "type": "CN_WORD",
  57.             "position":
  58.         },
  59.         {
  60.             "token": "举办",
  61.             "start_offset": ,
  62.             "end_offset": ,
  63.             "type": "CN_WORD",
  64.             "position":
  65.         },
  66.         {
  67.             "token": "",
  68.             "start_offset": ,
  69.             "end_offset": ,
  70.             "type": "ARABIC",
  71.             "position":
  72.         },
  73.         {
  74.             "token": "万人",
  75.             "start_offset": ,
  76.             "end_offset": ,
  77.             "type": "CN_WORD",
  78.             "position":
  79.         },
  80.         {
  81.             "token": "露天",
  82.             "start_offset": ,
  83.             "end_offset": ,
  84.             "type": "CN_WORD",
  85.             "position":
  86.         },
  87.         {
  88.             "token": "音乐会",
  89.             "start_offset": ,
  90.             "end_offset": ,
  91.             "type": "CN_WORD",
  92.             "position":
  93.         },
  94.         {
  95.             "token": "3人",
  96.             "start_offset": ,
  97.             "end_offset": ,
  98.             "type": "TYPE_CQUAN",
  99.             "position":
  100.         },
  101.         {
  102.             "token": "献",
  103.             "start_offset": ,
  104.             "end_offset": ,
  105.             "type": "CN_CHAR",
  106.             "position":
  107.         },
  108.         {
  109.             "token": "唱",
  110.             "start_offset": ,
  111.             "end_offset": ,
  112.             "type": "CN_CHAR",
  113.             "position":
  114.         },
  115.         {
  116.             "token": "多首",
  117.             "start_offset": ,
  118.             "end_offset": ,
  119.             "type": "CN_WORD",
  120.             "position":
  121.         },
  122.         {
  123.             "token": "经典",
  124.             "start_offset": ,
  125.             "end_offset": ,
  126.             "type": "CN_WORD",
  127.             "position":
  128.         },
  129.         {
  130.             "token": "好歌",
  131.             "start_offset": ,
  132.             "end_offset": ,
  133.             "type": "CN_WORD",
  134.             "position":
  135.         },
  136.         {
  137.             "token": "让",
  138.             "start_offset": ,
  139.             "end_offset": ,
  140.             "type": "CN_CHAR",
  141.             "position":
  142.         },
  143.         {
  144.             "token": "现场",
  145.             "start_offset": ,
  146.             "end_offset": ,
  147.             "type": "CN_WORD",
  148.             "position":
  149.         },
  150.         {
  151.             "token": "粉丝",
  152.             "start_offset": ,
  153.             "end_offset": ,
  154.             "type": "CN_WORD",
  155.             "position":
  156.         },
  157.         {
  158.             "token": "听得",
  159.             "start_offset": ,
  160.             "end_offset": ,
  161.             "type": "CN_WORD",
  162.             "position":
  163.         },
  164.         {
  165.             "token": "如痴如醉",
  166.             "start_offset": ,
  167.             "end_offset": ,
  168.             "type": "CN_WORD",
  169.             "position":
  170.         }
  171.     ]
  172. }

对比standard分词器：

  1. http://start.com:9200/_analyze
  2. {
  3.   "analyzer":"standard",
  4.   "text":"天团S.H.E昨在两厅院艺文广场 举办17万人露 天音乐会，3人献唱多首 经典好歌，让现场 粉丝听得如痴如醉"
  5. }

结果：

  1. {
  2.     "tokens": [
  3.         {
  4.             "token": "天",
  5.             "start_offset": ,
  6.             "end_offset": ,
  7.             "type": "<IDEOGRAPHIC>",
  8.             "position":
  9.         },
  10.         {
  11.             "token": "团",
  12.             "start_offset": ,
  13.             "end_offset": ,
  14.             "type": "<IDEOGRAPHIC>",
  15.             "position":
  16.         },
  17.         {
  18.             "token": "s.h.e",
  19.             "start_offset": ,
  20.             "end_offset": ,
  21.             "type": "<ALPHANUM>",
  22.             "position":
  23.         },
  24.         {
  25.             "token": "昨",
  26.             "start_offset": ,
  27.             "end_offset": ,
  28.             "type": "<IDEOGRAPHIC>",
  29.             "position":
  30.         },
  31.         {
  32.             "token": "在",
  33.             "start_offset": ,
  34.             "end_offset": ,
  35.             "type": "<IDEOGRAPHIC>",
  36.             "position":
  37.         },
  38.         {
  39.             "token": "两",
  40.             "start_offset": ,
  41.             "end_offset": ,
  42.             "type": "<IDEOGRAPHIC>",
  43.             "position":
  44.         },
  45.         {
  46.             "token": "厅",
  47.             "start_offset": ,
  48.             "end_offset": ,
  49.             "type": "<IDEOGRAPHIC>",
  50.             "position":
  51.         },
  52.         {
  53.             "token": "院",
  54.             "start_offset": ,
  55.             "end_offset": ,
  56.             "type": "<IDEOGRAPHIC>",
  57.             "position":
  58.         },
  59.         {
  60.             "token": "艺",
  61.             "start_offset": ,
  62.             "end_offset": ,
  63.             "type": "<IDEOGRAPHIC>",
  64.             "position":
  65.         },
  66.         {
  67.             "token": "文",
  68.             "start_offset": ,
  69.             "end_offset": ,
  70.             "type": "<IDEOGRAPHIC>",
  71.             "position":
  72.         }
  73. 　　　　　　。。。
  74.     ]
  75. }

standard分词器把中文都拆分成了单个字。IK分词器拆分成了字和词语。

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