ElasticSearch集群搭建实例

开始研究搜索了，在自己虚拟机上搭建了一个简易ElasticSearch搜索集群，与大家分享一下，希望能有所帮助。

操作系统环境: Red Hat 4.8.2-16

elasticsearch ： elasticsearch-1.4.1

集群搭建方式： 一台虚拟机上2个节点.

集群存放路径：/export/search/elasticsearch-cluster

必备环境:  java运行环境

集群搭建实例展示:

1. 解压tar包,创建集群节点

#进入到集群路径
[root@localhost elasticsearch-cluster]# pwd
/export/search/elasticsearch-cluster
#重命名解压包
[root@localhost elasticsearch-cluster]# ls
elasticsearch-1.4.1
[root@localhost elasticsearch-cluster]# mv elasticsearch-1.4.1 elasticsearch-node1
#进入到节点配置路径
[root@localhost elasticsearch-cluster]# cd elasticsearch-node1/config/
[root@localhost config]# ls
elasticsearch.yml  logging.yml

2.创建集群配置信息:

# elasticsearch-node1配置
# 配置集群名称
cluster.name: elasticsearch-cluster-CentOS
# 配置节点名称
node.name: "es-node1"
# 为节点之间的通信设置一个自定义端口(默认为9300)    
transport.tcp.port: 9300 
# 设置监听HTTP传输的自定义端(默认为9200)
http.port: 9200             

elasticsearch配置文件说明见: http://www.linuxidc.com/Linux/2015-02/114244.htm

3.安装head插件

#进入到节点bin路径
[root@localhost bin]# pwd
/export/search/elasticsearch-cluster/elasticsearch-node1/bin
安装插件
[root@localhost bin]# ./plugin -install mobz/elasticsearch-head

安装完插件之后会在es节点bin路径同级创建一个plugins目录,存放安装的插件

4.复制一份配置好的节点为elasticsearch-node2

[root@localhost elasticsearch-cluster]# ls
elasticsearch-node1  elasticsearch-node2

5.修改节点2中的集群配置信息

# elasticsearch-node2配置
# 配置集群名称
cluster.name: elasticsearch-cluster-centos
# 配置节点名称
node.name: "es-node2"
# 为节点之间的通信设置一个自定义端口(默认为9300)    
transport.tcp.port: 9301 
# 设置监听HTTP传输的自定义端(默认为9200)
http.port: 9201           

说明：
　　上面配置表示集群中有2个节点,节点名为别为,"es-node1"和  "es-node2"，同属于集群"elasticsearch-cluster-centos"
节点二中端口可以不用配置,es在启动时会去检测,如果目标端口被占用,会检测下一个端口.因为两节点部署在同一天虚拟机上为了更好的说明问题,这里手动配置了对应的端口.
我们可以从es对应日志中()查看对应的启动信息,以及端口绑定信息。

6.分别启动节点

[root@localhost bin]# pwd
/export/search/elasticsearch-cluster/elasticsearch-node1/bin
[root@localhost bin]# ./elasticsearch -d -Xms512m -Xmx512m

如上,为启动节点1的命令,es启动配置相关日志查看elasticsearch-cluster-centos.log即可.

[root@localhost logs]# pwd
/export/search/elasticsearch-cluster/elasticsearch-node2/logs
[root@localhost logs]# ls
elasticsearch-cluster-centos_index_indexing_slowlog.log  elasticsearch-cluster-centos.log  elasticsearch-cluster-centos_index_search_slowlog.log

7. 至此我们的简易集群配置完成.查看集群
 因为我们安装了head插件,所以可以通过该插件查看,虚拟机ip为192.168.1.108.

http://192.168.1.108:9200/_plugin/head/ (对应节点1)
http://192.168.1.108:9201/_plugin/head/ (对应节点2)

集群状态如图:

8.安装Marvel插件

Marvel是Elasticsearch的管理和监控工具，对于开发使用免费的。它配备了一个叫做Sense的交互式控制台，方便通过浏览器直接与Elasticsearch交互。
Marvel是一个插件，在Elasticsearch目录中运行以下代码来下载和安装：

./bin/plugin -i elasticsearch/marvel/latest

如果要禁止Marvel,可以通过如下方式

echo 'marvel.agent.enabled: false' >> ./config/elasticsearch.yml

Elasticsearch安装使用教程 http://www.linuxidc.com/Linux/2015-02/113615.htm

分布式搜索ElasticSearch单机与服务器环境搭建  http://www.linuxidc.com/Linux/2012-05/60787.htm

ElasticSearch的工作机制  http://www.linuxidc.com/Linux/2014-11/109922.htm

ElasticSearch 的详细介绍：请点这里
ElasticSearch 的下载地址：请点这里

本文永久更新链接地址：http://www.linuxidc.com/Linux/2015-02/114243.htm

 

 

##################### Elasticsearch Configuration Example #####################

# This file contains an overview of various configuration settings,
# targeted at operations staff. Application developers should
# consult the guide at <http://elasticsearch.org/guide>.
#
# The installation procedure is covered at
# <http://elasticsearch.org/guide/en/elasticsearch/reference/current/setup.html>.
#
# Elasticsearch comes with reasonable defaults for most settings,
# so you can try it out without bothering with configuration.
#
# Most of the time, these defaults are just fine for running a production
# cluster. If you're fine-tuning your cluster, or wondering about the
# effect of certain configuration option, please _do ask_ on the
# mailing list or IRC channel [http://elasticsearch.org/community].

# Any element in the configuration can be replaced with environment variables
# by placing them in ${...} notation. For example:
#
#node.rack: ${RACK_ENV_VAR}

# For information on supported formats and syntax for the config file, see
# <http://elasticsearch.org/guide/en/elasticsearch/reference/current/setup-configuration.html>


################################### Cluster ###################################

# Cluster name identifies your cluster for auto-discovery. If you're running
# multiple clusters on the same network, make sure you're using unique names.
#
cluster.name: search


#################################### Node #####################################

# Node names are generated dynamically on startup, so you're relieved
# from configuring them manually. You can tie this node to a specific name:
#
#node.name: "Franz Kafka"

# Every node can be configured to allow or deny being eligible as the master,
# and to allow or deny to store the data.
#
# Allow this node to be eligible as a master node (enabled by default):
#
#node.master: true
#
# Allow this node to store data (enabled by default):
#
#node.data: true

# You can exploit these settings to design advanced cluster topologies.
#
# 1. You want this node to never become a master node, only to hold data.
#    This will be the "workhorse" of your cluster.
#
#node.master: false
#node.data: true
#
# 2. You want this node to only serve as a master: to not store any data and
#    to have free resources. This will be the "coordinator" of your cluster.
#
#node.master: true
#node.data: false
#
# 3. You want this node to be neither master nor data node, but
#    to act as a "search load balancer" (fetching data from nodes,
#    aggregating results, etc.)
#
#node.master: false
#node.data: false

# Use the Cluster Health API [http://localhost:9200/_cluster/health], the
# Node Info API [http://localhost:9200/_nodes] or GUI tools
# such as <http://www.elasticsearch.org/overview/marvel/>,
# <http://github.com/karmi/elasticsearch-paramedic>,
# <http://github.com/lukas-vlcek/bigdesk> and
# <http://mobz.github.com/elasticsearch-head> to inspect the cluster state.

# A node can have generic attributes associated with it, which can later be used
# for customized shard allocation filtering, or allocation awareness. An attribute
# is a simple key value pair, similar to node.key: value, here is an example:
#
#node.rack: rack314

# By default, multiple nodes are allowed to start from the same installation location
# to disable it, set the following:
#node.max_local_storage_nodes: 1


#################################### Index ####################################

# You can set a number of options (such as shard/replica options, mapping
# or analyzer definitions, translog settings, ...) for indices globally,
# in this file.
#
# Note, that it makes more sense to configure index settings specifically for
# a certain index, either when creating it or by using the index templates API.
#
# See <http://elasticsearch.org/guide/en/elasticsearch/reference/current/index-modules.html> and
# <http://elasticsearch.org/guide/en/elasticsearch/reference/current/indices-create-index.html>
# for more information.

# Set the number of shards (splits) of an index (5 by default):
#
index.number_of_shards: 10

# Set the number of replicas (additional copies) of an index (1 by default):
#
#index.number_of_replicas: 1

# Note, that for development on a local machine, with small indices, it usually
# makes sense to "disable" the distributed features:
#
#index.number_of_shards: 1
#index.number_of_replicas: 0

# These settings directly affect the performance of index and search operations
# in your cluster. Assuming you have enough machines to hold shards and
# replicas, the rule of thumb is:
#
# 1. Having more *shards* enhances the _indexing_ performance and allows to
#    _distribute_ a big index across machines.
# 2. Having more *replicas* enhances the _search_ performance and improves the
#    cluster _availability_.
#
# The "number_of_shards" is a one-time setting for an index.
#
# The "number_of_replicas" can be increased or decreased anytime,
# by using the Index Update Settings API.
#
# Elasticsearch takes care about load balancing, relocating, gathering the
# results from nodes, etc. Experiment with different settings to fine-tune
# your setup.

# Use the Index Status API (<http://localhost:9200/A/_status>) to inspect
# the index status.


#################################### Paths ####################################

# Path to directory containing configuration (this file and logging.yml):
#
#path.conf: /path/to/conf

# Path to directory where to store index data allocated for this node.
#
path.data: /data/esdata
#
# Can optionally include more than one location, causing data to be striped across
# the locations (a la RAID 0) on a file level, favouring locations with most free
# space on creation. For example:
#
#path.data: /path/to/data1,/path/to/data2

# Path to temporary files:
#
#path.work: /path/to/work

# Path to log files:
#
#path.logs: /path/to/logs

# Path to where plugins are installed:
#
#path.plugins: /path/to/plugins


#################################### Plugin ###################################

# If a plugin listed here is not installed for current node, the node will not start.
#
#plugin.mandatory: mapper-attachments,lang-groovy


################################### Memory ####################################

# Elasticsearch performs poorly when JVM starts swapping: you should ensure that
# it _never_ swaps.
#
# Set this property to true to lock the memory:
#
#bootstrap.mlockall: true

# Make sure that the ES_MIN_MEM and ES_MAX_MEM environment variables are set
# to the same value, and that the machine has enough memory to allocate
# for Elasticsearch, leaving enough memory for the operating system itself.
#
# You should also make sure that the Elasticsearch process is allowed to lock
# the memory, eg. by using `ulimit -l unlimited`.


############################## Network And HTTP ###############################

# Elasticsearch, by default, binds itself to the 0.0.0.0 address, and listens
# on port [9200-9300] for HTTP traffic and on port [9300-9400] for node-to-node
# communication. (the range means that if the port is busy, it will automatically
# try the next port).

# Set the bind address specifically (IPv4 or IPv6):
#
#network.bind_host: 192.168.0.1

# Set the address other nodes will use to communicate with this node. If not
# set, it is automatically derived. It must point to an actual IP address.
#
network.publish_host: 192.168.2.99

# Set both 'bind_host' and 'publish_host':
#
#network.host: 192.168.0.1

# Set a custom port for the node to node communication (9300 by default):
#
transport.tcp.port: 4300

# Enable compression for all communication between nodes (disabled by default):
#
#transport.tcp.compress: true

# Set a custom port to listen for HTTP traffic:
#
http.port: 4200

# Set a custom allowed content length:
#
#http.max_content_length: 100mb

# Disable HTTP completely:
#
#http.enabled: false


################################### Gateway ###################################

# The gateway allows for persisting the cluster state between full cluster
# restarts. Every change to the state (such as adding an index) will be stored
# in the gateway, and when the cluster starts up for the first time,
# it will read its state from the gateway.

# There are several types of gateway implementations. For more information, see
# <http://elasticsearch.org/guide/en/elasticsearch/reference/current/modules-gateway.html>.

# The default gateway type is the "local" gateway (recommended):
#
#gateway.type: local

# Settings below control how and when to start the initial recovery process on
# a full cluster restart (to reuse as much local data as possible when using shared
# gateway).

# Allow recovery process after N nodes in a cluster are up:
#
#gateway.recover_after_nodes: 1

# Set the timeout to initiate the recovery process, once the N nodes
# from previous setting are up (accepts time value):
#
#gateway.recover_after_time: 5m

# Set how many nodes are expected in this cluster. Once these N nodes
# are up (and recover_after_nodes is met), begin recovery process immediately
# (without waiting for recover_after_time to expire):
#
#gateway.expected_nodes: 2


############################# Recovery Throttling #############################

# These settings allow to control the process of shards allocation between
# nodes during initial recovery, replica allocation, rebalancing,
# or when adding and removing nodes.

# Set the number of concurrent recoveries happening on a node:
#
# 1. During the initial recovery
#
#cluster.routing.allocation.node_initial_primaries_recoveries: 4
#
# 2. During adding/removing nodes, rebalancing, etc
#
#cluster.routing.allocation.node_concurrent_recoveries: 2

# Set to throttle throughput when recovering (eg. 100mb, by default 20mb):
#
#indices.recovery.max_bytes_per_sec: 20mb

# Set to limit the number of open concurrent streams when
# recovering a shard from a peer:
#
#indices.recovery.concurrent_streams: 5


################################## Discovery ##################################

# Discovery infrastructure ensures nodes can be found within a cluster
# and master node is elected. Multicast discovery is the default.

# Set to ensure a node sees N other master eligible nodes to be considered
# operational within the cluster. Its recommended to set it to a higher value
# than 1 when running more than 2 nodes in the cluster.
#
#discovery.zen.minimum_master_nodes: 1

# Set the time to wait for ping responses from other nodes when discovering.
# Set this option to a higher value on a slow or congested network
# to minimize discovery failures:
#
#discovery.zen.ping.timeout: 3s

# For more information, see
# <http://elasticsearch.org/guide/en/elasticsearch/reference/current/modules-discovery-zen.html>

# Unicast discovery allows to explicitly control which nodes will be used
# to discover the cluster. It can be used when multicast is not present,
# or to restrict the cluster communication-wise.
#
# 1. Disable multicast discovery (enabled by default):
#
discovery.zen.ping.multicast.enabled: false
#
# 2. Configure an initial list of master nodes in the cluster
#    to perform discovery when new nodes (master or data) are started:
#
discovery.zen.ping.unicast.hosts: ["hdslave5", "hdslave1", "hdslave6", "hdslave3", "hdslave4"]
# EC2 discovery allows to use AWS EC2 API in order to perform discovery.
#
# You have to install the cloud-aws plugin for enabling the EC2 discovery.
#
# For more information, see
# <http://elasticsearch.org/guide/en/elasticsearch/reference/current/modules-discovery-ec2.html>
#
# See <http://elasticsearch.org/tutorials/elasticsearch-on-ec2/>
# for a step-by-step tutorial.

# GCE discovery allows to use Google Compute Engine API in order to perform discovery.
#
# You have to install the cloud-gce plugin for enabling the GCE discovery.
#
# For more information, see <https://github.com/elasticsearch/elasticsearch-cloud-gce>.

# Azure discovery allows to use Azure API in order to perform discovery.
#
# You have to install the cloud-azure plugin for enabling the Azure discovery.
#
# For more information, see <https://github.com/elasticsearch/elasticsearch-cloud-azure>.

################################## Slow Log ##################################

# Shard level query and fetch threshold logging.

#index.search.slowlog.threshold.query.warn: 10s
#index.search.slowlog.threshold.query.info: 5s
#index.search.slowlog.threshold.query.debug: 2s
#index.search.slowlog.threshold.query.trace: 500ms

#index.search.slowlog.threshold.fetch.warn: 1s
#index.search.slowlog.threshold.fetch.info: 800ms
#index.search.slowlog.threshold.fetch.debug: 500ms
#index.search.slowlog.threshold.fetch.trace: 200ms

#index.indexing.slowlog.threshold.index.warn: 10s
#index.indexing.slowlog.threshold.index.info: 5s
#index.indexing.slowlog.threshold.index.debug: 2s
#index.indexing.slowlog.threshold.index.trace: 500ms

################################## GC Logging ################################

#monitor.jvm.gc.young.warn: 1000ms
#monitor.jvm.gc.young.info: 700ms
#monitor.jvm.gc.young.debug: 400ms
index.cache.filter.expire: 1m
index.cache.filter.max_size: 20
index.cache.field.max_size: 50000
index.cache.field.expire: 5m
index.cache.field.type: soft
#monitor.jvm.gc.old.warn: 10s
#monitor.jvm.gc.old.info: 5s
#monitor.jvm.gc.old.debug: 2s
index:
  analysis:
    analyzer:
      ik:
          alias: [news_analyzer_ik,ik_analyzer]
          type: org.elasticsearch.index.analysis.IkAnalyzerProvider

index.analysis.analyzer.default.type : "ik"