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LogStash的安装(传统方式&Docker)与使用

2021-12-05 15:04:52 作者：互联网

Logstash 是一个实时数据收集引擎，可收集各类型数据并对其进行分析，过滤和归纳。按照自己条件分析过滤出符合数据导入到可视化界面。它可以实现多样化的数据源数据全量或增量传输，数据标准格式处理，数据格式化输出等的功能，常用于日志处理。工作流程分为三个阶段：

　　（1）input数据输入阶段，可接收oracle、mysql、postgresql、file等多种数据源；
　　（2）filter数据标准格式化阶段，可过滤、格式化数据，如格式化时间、字符串等；
　　（3）output数据输出阶段，可输出到elasticsearch、mongodb、kafka等接收终端。

传统方式

1、下载安装包

https://artifacts.elastic.co/downloads/logstash/logstash-7.15.2-linux-x86_64.tar.gz

2、解压缩，移动重命名

[root@localhost ~]# tar -zxvf logstash-7.15.2-linux-x86_64.tar.gz 

[root@localhost ~]# mv logstash-7.15.2 /usr/local/logstash

3、配置

注意一下所有的配置文件请设置成utf-8格式，不然启动可能会报错！！！

pipelines.yml

配置方式有三种

1、直接写input,output这样，使用config.string字段
 - pipeline.id: test
   pipeline.workers: 1
   pipeline.batch.size: 1
   config.string: "input { generator {} } filter { sleep { time => 1 } } output { stdout { codec => dots } }"

2、使用配置文件的路径 使用path.config字段

 - pipeline.id: another_test
   queue.type: persisted
   path.config: "/tmp/logstash/a.config"

3、使用通配符格式 path.config=/tmp/logstash/conf.d/*.conf

 - pipeline.id: another_test
   queue.type: persisted
   path.config: "/tmp/logstash/conf.d/*.conf"


#多个路径分开写

  - pipeline.id: kafka
    pipeline.workers: 2 #线程数默认与cpu核数一致
    pipeline.batch.size: 1 #批量处理的条数默认125
    path.config: "/usr/local/logstash/config/logstash-kafka.conf"
  - pipeline.id: es
    queue.type: persisted #队列持久化，防止丢失数据，默认不开启
    path.config: "/usr/local/logstash/config/logstash-es.conf"

log-es.conf

# Sample Logstash configuration for creating a simple
# Beats -> Logstash -> Elasticsearch pipeline.

input{
  file{
    # 日志文件路径
    path => "/usr/local/es/logs/my-es.log"
    type => "elasticsearch"
    start_position => "beginning" #从文件开始处读写
  }
}
 
 #过滤器，正则表达式
filter {

  #定义数据的格式
  grok {
    match => { "message" => "%{DATA:timestamp}\|%{IP:serverIp}\|%{IP:clientIp}\|%{DATA:logSource}\|%{DATA:userId}\|%{DATA:reqUrl}\|%{DATA:reqUri}\|%{DATA:refer}\|%{DATA:device}\|%{DATA:textDuring}\|%{DATA:duringTime:int}\|\|"}
  }

 #定义时间戳的格式
  date {
    match => [ "timestamp", "yyyy-MM-dd-HH:mm:ss" ]
    locale => "cn"
  }

  #定义客户端的IP是哪个字段（上面定义的数据格式）
  geoip {
    source => "clientIp"
  }
}

output{
  elasticsearch{
    hosts => ["192.168.139.160:9200","192.168.139.161:9200","192.168.139.162:9200"] # es地址
    index => "es-message-%{+YYYY.MM.dd}" 
    #如果es没有设置密码则不需要设置密码
    user => "elastic"
    password => "cGKuMaWGZLBaSSDW7qKX"
  }
  stdout{
    codec => rubydebug
  }
}

logstash-kafka.conf

input {
  kafka {
    bootstrap_servers => "192.168.139.162:9092"
    topics => "my-topic-partition"
 }
}
filter {
  #Only matched data are send to output
}
output  {
  elasticsearch{
    hosts => ["192.168.139.160:9200","192.168.139.161:9200","192.168.139.162:9200"] # es地址
    index => "kafka-log-%{+YYYY.MM.dd}"
    user => "elastic"
    password => "cGKuMaWGZLBaSSDW7qKX"
  }
  stdout{
    codec => rubydebug
  }
}

logstash.yml文件注释说明

# Settings file in YAML
#
# Settings can be specified either in hierarchical form, e.g.:
#
#   pipeline:
#     batch:
#       size: 125
#       delay: 5
#
# Or as flat keys:
#
#   pipeline.batch.size: 125
#   pipeline.batch.delay: 5
#
# ------------  Node identity ------------
#
# Use a descriptive name for the node:
#默认机器主机名称
# node.name: test
#
# If omitted the node name will default to the machine's host name
#
# ------------ Data path ------------------
#
# Which directory should be used by logstash and its plugins
# for any persistent needs. Defaults to LOGSTASH_HOME/data
#logstash及其插件目录
# path.data:
#
# ------------ Pipeline Settings --------------
#
# The ID of the pipeline.
#
# pipeline.id: main
#
# Set the number of workers that will, in parallel, execute the filters+outputs
# stage of the pipeline.
#
# This defaults to the number of the host's CPU cores.
#将并行执行管道的过滤器和输出阶段的工作线程数，默认是cpu核数
# pipeline.workers: 2
#
# How many events to retrieve from inputs before sending to filters+workers
#单个工作线程将从输入中收集的最大事件数
pipeline.batch.size: 125
#
# How long to wait in milliseconds while polling for the next event
# before dispatching an undersized batch to filters+outputs
#轮询下一个事件时等待的时间（毫秒）
pipeline.batch.delay: 50
#
# Force Logstash to exit during shutdown even if there are still inflight
# events in memory. By default, logstash will refuse to quit until all
# received events have been pushed to the outputs.
#
# WARNING: enabling this can lead to data loss during shutdown
#设置为 时true，强制 Logstash 在关闭期间退出，即使内存中仍有进行中的事件。
#默认情况下，Logstash 将拒绝退出，直到所有接收到的事件都已推送到输出
# pipeline.unsafe_shutdown: false
#
# Set the pipeline event ordering. Options are "auto" (the default), "true" or "false".
# "auto" will  automatically enable ordering if the 'pipeline.workers' setting
# is also set to '1'.
# "true" will enforce ordering on the pipeline and prevent logstash from starting
# if there are multiple workers.
# "false" will disable any extra processing necessary for preserving ordering.
#排序
# pipeline.ordered: auto
#
# ------------ Pipeline Configuration Settings --------------
#
# Where to fetch the pipeline configuration for the main pipeline
#
# path.config:
#
# Pipeline configuration string for the main pipeline
#
# config.string:
#
# At startup, test if the configuration is valid and exit (dry run)
#检查配置是否正确，默认不检查
# config.test_and_exit: false
#
# Periodically check if the configuration has changed and reload the pipeline
# This can also be triggered manually through the SIGHUP signal
#会定期检查配置是否已更改，并在更改时重新加载配置。默认不检查
# config.reload.automatic: false
#
# How often to check if the pipeline configuration has changed (in seconds)
# Note that the unit value (s) is required. Values without a qualifier (e.g. 60) 
# are treated as nanoseconds.
# Setting the interval this way is not recommended and might change in later versions.
#Logstash 检查配置文件的更改频率（以秒为单位）
# config.reload.interval: 3s
#
# Show fully compiled configuration as debug log message
# NOTE: --log.level must be 'debug'
#
# config.debug: false
#
# When enabled, process escaped characters such as \n and \" in strings in the
# pipeline configuration files.
#带引号的字符串是否转义
# config.support_escapes: false
#
# ------------ HTTP API Settings -------------
# Define settings related to the HTTP API here.
#
# The HTTP API is enabled by default. It can be disabled, but features that rely
# on it will not work as intended.
# http.enabled: true
#
# By default, the HTTP API is bound to only the host's local loopback interface,
# ensuring that it is not accessible to the rest of the network. Because the API
# includes neither authentication nor authorization and has not been hardened or
# tested for use as a publicly-reachable API, binding to publicly accessible IPs
# should be avoided where possible.
#
# http.host: 127.0.0.1
#
# The HTTP API web server will listen on an available port from the given range.
# Values can be specified as a single port (e.g., `9600`), or an inclusive range
# of ports (e.g., `9600-9700`).
#默认9600
# http.port: 9600-9700
#
# ------------ Module Settings ---------------
# Define modules here.  Modules definitions must be defined as an array.
# The simple way to see this is to prepend each `name` with a `-`, and keep
# all associated variables under the `name` they are associated with, and
# above the next, like this:
#
# modules:
#   - name: MODULE_NAME
#     var.PLUGINTYPE1.PLUGINNAME1.KEY1: VALUE
#     var.PLUGINTYPE1.PLUGINNAME1.KEY2: VALUE
#     var.PLUGINTYPE2.PLUGINNAME1.KEY1: VALUE
#     var.PLUGINTYPE3.PLUGINNAME3.KEY1: VALUE
#
# Module variable names must be in the format of
#
# var.PLUGIN_TYPE.PLUGIN_NAME.KEY
#
# modules:
#
# ------------ Cloud Settings ---------------
# Define Elastic Cloud settings here.
# Format of cloud.id is a base64 value e.g. dXMtZWFzdC0xLmF3cy5mb3VuZC5pbyRub3RhcmVhbCRpZGVudGlmaWVy
# and it may have an label prefix e.g. staging:dXMtZ...
# This will overwrite 'var.elasticsearch.hosts' and 'var.kibana.host'
# cloud.id: <identifier>
#
# Format of cloud.auth is: <user>:<pass>
# This is optional
# If supplied this will overwrite 'var.elasticsearch.username' and 'var.elasticsearch.password'
# If supplied this will overwrite 'var.kibana.username' and 'var.kibana.password'
# cloud.auth: elastic:<password>
#
# ------------ Queuing Settings --------------
#
# Internal queuing model, "memory" for legacy in-memory based queuing and
# "persisted" for disk-based acked queueing. Defaults is memory
# persisted基于磁盘的 ACKed 队列，会将未消费的消息持久化到磁盘
#memory基于内存，宕机之后，有可能丢失数据，默认是memory
# queue.type: memory
#
# If using queue.type: persisted, the directory path where the data files will be stored.
# Default is path.data/queue
#启用持久队列时将存储数据文件的目录路径
# path.queue:
#
# If using queue.type: persisted, the page data files size. The queue data consists of
# append-only data files separated into pages. Default is 64mb
#启用持久队列时使用的页面数据文件的大小,默认64M
# queue.page_capacity: 64mb
#
# If using queue.type: persisted, the maximum number of unread events in the queue.
# Default is 0 (unlimited)
#启用持久队列时队列中未读事件的最大数量，0表示没有限制
# queue.max_events: 0
#
# If using queue.type: persisted, the total capacity of the queue in number of bytes.
# If you would like more unacked events to be buffered in Logstash, you can increase the
# capacity using this setting. Please make sure your disk drive has capacity greater than
# the size specified here. If both max_bytes and max_events are specified, Logstash will pick
# whichever criteria is reached first
# Default is 1024mb or 1gb
#队列的总容量
# queue.max_bytes: 1024mb
#
# If using queue.type: persisted, the maximum number of acked events before forcing a checkpoint
# Default is 1024, 0 for unlimited
#启用持久队列时强制检查点之前 ACKed 事件的最大数量
# queue.checkpoint.acks: 1024
#
# If using queue.type: persisted, the maximum number of written events before forcing a checkpoint
# Default is 1024, 0 for unlimited
#启用持久队列时强制检查点之前的最大写入事件数
# queue.checkpoint.writes: 1024
#
# If using queue.type: persisted, the interval in milliseconds when a checkpoint is forced on the head page
# Default is 1000, 0 for no periodic checkpoint.
#
# queue.checkpoint.interval: 1000
#
# ------------ Dead-Letter Queue Settings --------------
# Flag to turn on dead-letter queue.
#死信队列
# dead_letter_queue.enable: false

# If using dead_letter_queue.enable: true, the maximum size of each dead letter queue. Entries
# will be dropped if they would increase the size of the dead letter queue beyond this setting.
# Default is 1024mb
# dead_letter_queue.max_bytes: 1024mb

# If using dead_letter_queue.enable: true, the interval in milliseconds where if no further events eligible for the DLQ
# have been created, a dead letter queue file will be written. A low value here will mean that more, smaller, queue files
# may be written, while a larger value will introduce more latency between items being "written" to the dead letter queue, and
# being available to be read by the dead_letter_queue input when items are are written infrequently.
# Default is 5000.
#
# dead_letter_queue.flush_interval: 5000

# If using dead_letter_queue.enable: true, the directory path where the data files will be stored.
# Default is path.data/dead_letter_queue
#
# path.dead_letter_queue:
#
# ------------ Metrics Settings --------------
#
# Bind address for the metrics REST endpoint
#
# http.host: "127.0.0.1"
#
# Bind port for the metrics REST endpoint, this option also accept a range
# (9600-9700) and logstash will pick up the first available ports.
#
# http.port: 9600-9700
#
# ------------ Debugging Settings --------------
#
# Options for log.level:
#   * fatal
#   * error
#   * warn
#   * info (default)
#   * debug
#   * trace
#
# log.level: info
# path.logs:
#
# ------------ Other Settings --------------
#
# Where to find custom plugins
# path.plugins: []
#
# Flag to output log lines of each pipeline in its separate log file. Each log filename contains the pipeline.name
# Default is false
#用于启用不同日志文件中每个管道的日志分离
# pipeline.separate_logs: false
#
# ------------ X-Pack Settings (not applicable for OSS build)--------------
#
# X-Pack Monitoring
# https://www.elastic.co/guide/en/logstash/current/monitoring-logstash.html
#xpack.monitoring.enabled: false
#xpack.monitoring.elasticsearch.username: logstash_system
#xpack.monitoring.elasticsearch.password: password
#xpack.monitoring.elasticsearch.proxy: ["http://proxy:port"]
#xpack.monitoring.elasticsearch.hosts: ["https://es1:9200", "https://es2:9200"]
# an alternative to hosts + username/password settings is to use cloud_id/cloud_auth
#xpack.monitoring.elasticsearch.cloud_id: monitoring_cluster_id:xxxxxxxxxx
#xpack.monitoring.elasticsearch.cloud_auth: logstash_system:password
# another authentication alternative is to use an Elasticsearch API key
#xpack.monitoring.elasticsearch.api_key: "id:api_key"
#xpack.monitoring.elasticsearch.ssl.certificate_authority: [ "/path/to/ca.crt" ]
#xpack.monitoring.elasticsearch.ssl.truststore.path: path/to/file
#xpack.monitoring.elasticsearch.ssl.truststore.password: password
#xpack.monitoring.elasticsearch.ssl.keystore.path: /path/to/file
#xpack.monitoring.elasticsearch.ssl.keystore.password: password
#xpack.monitoring.elasticsearch.ssl.verification_mode: certificate
#xpack.monitoring.elasticsearch.sniffing: false
#xpack.monitoring.collection.interval: 10s
#xpack.monitoring.collection.pipeline.details.enabled: true
#
# X-Pack Management
# https://www.elastic.co/guide/en/logstash/current/logstash-centralized-pipeline-management.html
#xpack.management.enabled: false
#xpack.management.pipeline.id: ["main", "apache_logs"]
#xpack.management.elasticsearch.username: logstash_admin_user
#xpack.management.elasticsearch.password: password
#xpack.management.elasticsearch.proxy: ["http://proxy:port"]
#xpack.management.elasticsearch.hosts: ["https://es1:9200", "https://es2:9200"]
# an alternative to hosts + username/password settings is to use cloud_id/cloud_auth
#xpack.management.elasticsearch.cloud_id: management_cluster_id:xxxxxxxxxx
#xpack.management.elasticsearch.cloud_auth: logstash_admin_user:password
# another authentication alternative is to use an Elasticsearch API key
#xpack.management.elasticsearch.api_key: "id:api_key"
#xpack.management.elasticsearch.ssl.certificate_authority: [ "/path/to/ca.crt" ]
#xpack.management.elasticsearch.ssl.truststore.path: /path/to/file
#xpack.management.elasticsearch.ssl.truststore.password: password
#xpack.management.elasticsearch.ssl.keystore.path: /path/to/file
#xpack.management.elasticsearch.ssl.keystore.password: password
#xpack.management.elasticsearch.ssl.verification_mode: certificate
#xpack.management.elasticsearch.sniffing: false
#xpack.management.logstash.poll_interval: 5s

# X-Pack GeoIP plugin
# https://www.elastic.co/guide/en/logstash/current/plugins-filters-geoip.html#plugins-filters-geoip-manage_update
#xpack.geoip.download.endpoint: "https://geoip.elastic.co/v1/database"

4、启动

[root@localhost logstash]# ./bin/logstash
#后台启动
[root@localhost logstash]# nohup ./bin/logstash &

Docker方式

1、拉取镜像

docker pull docker.elastic.co/logstash/logstash:7.15.2

2、创建挂载

mkdir -p /data/logstash/{pipeline,config}

logstash.yml

#开启
http.host: 0.0.0.0

pipelines.yml

# List of pipelines to be loaded by Logstash
#
# This document must be a list of dictionaries/hashes, where the keys/values are pipeline settings.
# Default values for omitted settings are read from the `logstash.yml` file.
# When declaring multiple pipelines, each MUST have its own `pipeline.id`.
#
# Example of two pipelines:
  - pipeline.id: kafka
    pipeline.workers: 2 #线程数默认与cpu核数一致
    pipeline.batch.size: 1 #批量处理的条数默认125
    path.config: "/usr/share/logstash/pipeline"

降配置文件放到pipeline目录（logstash-kafka.conf）

3、创建容器

docker run -it --name logstash --net=host \
-v /data/logstash/pipeline/:/usr/share/logstash/pipeline/ \
-v /data/logstash/config/logstash.yml:/usr/share/logstash/config/logstash.yml \
-v /data/logstash/config/pipelines.yml:/usr/share/logstash/config/pipelines.yml \
docker.elastic.co/logstash/logstash:7.15.2

注意若是es与logstash不在同一台服务器上启动参数一定要加上--net=host，不然其他es节点连接不上！

标签：pipeline,xpack,logstash,queue,elasticsearch,path,Docker,安装,LogStash
来源： https://blog.csdn.net/weixin_39555954/article/details/121666779