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    第3章 Logstash数据分析

    Logstash使用管道方式进行日志的搜集处理和输出。有点类似*NIX系统的管道命令 xxx | ccc | ddd，xxx执行完了会执行ccc，然后执行ddd。
    在logstash中，包括了三个阶段:
    输入input –> 处理filter（不是必须的） –> 输出output

    ElasticSearch学习笔记之三：Logstash数据分析插图

    每个阶段都由很多的插件配合工作，比如file、elasticsearch、redis等等。
    每个阶段也可以指定多种方式，比如输出既可以输出到elasticsearch中，也可以指定到stdout在控制台打印。

    logstash支持多输入和多输出

    ELFK架构示意图：

    ElasticSearch学习笔记之三：Logstash数据分析插图(1)

    1.Logstash基础部署

    1. 安装软件
    [root@host3 ~]# yum install logstash --enablerepo=es -y 			# 偶尔需要使用的仓库可以将它关闭，用到的时候临时打开

[root@host3 ~]# ln -sv /usr/share/logstash/bin/logstash /usr/local/bin/	# 做软连接，命令就可以直接使用了
"/usr/local/bin/logstash" -> "/usr/share/logstash/bin/logstash"
    1. 创建第一个配置文件
    [root@host3 ~]# vim 01-stdin-stdout.conf

input {
  stdin {}
}

output {
  stdout {}
}
    1. 测试配置文件
    [root@host3 ~]# logstash -tf 01-stdin-stdout.conf
    1. 自定义启动，这种方式通常用于实验环境，业务环境下，通常将配置修改后，使用systemctl来管理服务
    [root@host3 ~]# logstash -f 01-stdin-stdout.conf 
Using bundled JDK: /usr/share/logstash/jdk
OpenJDK 64-Bit Server VM warning: Option UseConcMarkSweepGC was deprecated in version 9.0 and will likely be removed in a future release.
WARNING: Could not find logstash.yml which is typically located in $LS_HOME/config or /etc/logstash. You can specify the path using --path.settings. Continuing using the defaults
Could not find log4j2 configuration at path /usr/share/logstash/config/log4j2.properties. Using default config which logs errors to the console
[INFO ] 2022-09-15 21:49:37.109 [main] runner - Starting Logstash {"logstash.version"=>"7.17.6", "jruby.version"=>"jruby 9.2.20.1 (2.5.8) 2021-11-30 2a2962fbd1 OpenJDK 64-Bit Server VM 11.0.16+8 on 11.0.16+8 +indy +jit [linux-x86_64]"}
[INFO ] 2022-09-15 21:49:37.115 [main] runner - JVM bootstrap flags: [-Xms1g, -Xmx1g, -XX:+UseConcMarkSweepGC, -XX:CMSInitiatingOccupancyFraction=75, -XX:+UseCMSInitiatingOccupancyOnly, -Djava.awt.headless=true, -Dfile.encoding=UTF-8, -Djdk.io.File.enableADS=true, -Djruby.compile.invokedynamic=true, -Djruby.jit.threshold=0, -Djruby.regexp.interruptible=true, -XX:+HeapDumpOnOutOfMemoryError, -Djava.security.egd=file:/dev/urandom, -Dlog4j2.isThreadContextMapInheritable=true]
[INFO ] 2022-09-15 21:49:37.160 [main] settings - Creating directory {:setting=>"path.queue", :path=>"/usr/share/logstash/data/queue"}
[INFO ] 2022-09-15 21:49:37.174 [main] settings - Creating directory {:setting=>"path.dead_letter_queue", :path=>"/usr/share/logstash/data/dead_letter_queue"}
[WARN ] 2022-09-15 21:49:37.687 [LogStash::Runner] multilocal - Ignoring the 'pipelines.yml' file because modules or command line options are specified
[INFO ] 2022-09-15 21:49:38.843 [LogStash::Runner] Reflections - Reflections took 114 ms to scan 1 urls, producing 119 keys and 419 values 
[WARN ] 2022-09-15 21:49:39.658 [LogStash::Runner] line - Relying on default value of `pipeline.ecs_compatibility`, which may change in a future major release of Logstash. To avoid unexpected changes when upgrading Logstash, please explicitly declare your desired ECS Compatibility mode.
[WARN ] 2022-09-15 21:49:39.703 [LogStash::Runner] stdin - Relying on default value of `pipeline.ecs_compatibility`, which may change in a future major release of Logstash. To avoid unexpected changes when upgrading Logstash, please explicitly declare your desired ECS Compatibility mode.
Configuration OK
[INFO ] 2022-09-15 21:49:39.917 [LogStash::Runner] runner - Using config.test_and_exit mode. Config Validation Result: OK. Exiting Logstash
[root@host3 ~]# logstash -f 01-stdin-stdout.conf 
Using bundled JDK: /usr/share/logstash/jdk
OpenJDK 64-Bit Server VM warning: Option UseConcMarkSweepGC was deprecated in version 9.0 and will likely be removed in a future release.
WARNING: Could not find logstash.yml which is typically located in $LS_HOME/config or /etc/logstash. You can specify the path using --path.settings. Continuing using the defaults
Could not find log4j2 configuration at path /usr/share/logstash/config/log4j2.properties. Using default config which logs errors to the console
[INFO ] 2022-09-15 21:50:25.095 [main] runner - Starting Logstash {"logstash.version"=>"7.17.6", "jruby.version"=>"jruby 9.2.20.1 (2.5.8) 2021-11-30 2a2962fbd1 OpenJDK 64-Bit Server VM 11.0.16+8 on 11.0.16+8 +indy +jit [linux-x86_64]"}
[INFO ] 2022-09-15 21:50:25.103 [main] runner - JVM bootstrap flags: [-Xms1g, -Xmx1g, -XX:+UseConcMarkSweepGC, -XX:CMSInitiatingOccupancyFraction=75, -XX:+UseCMSInitiatingOccupancyOnly, -Djava.awt.headless=true, -Dfile.encoding=UTF-8, -Djdk.io.File.enableADS=true, -Djruby.compile.invokedynamic=true, -Djruby.jit.threshold=0, -Djruby.regexp.interruptible=true, -XX:+HeapDumpOnOutOfMemoryError, -Djava.security.egd=file:/dev/urandom, -Dlog4j2.isThreadContextMapInheritable=true]
[WARN ] 2022-09-15 21:50:25.523 [LogStash::Runner] multilocal - Ignoring the 'pipelines.yml' file because modules or command line options are specified
[INFO ] 2022-09-15 21:50:25.555 [LogStash::Runner] agent - No persistent UUID file found. Generating new UUID {:uuid=>"3fc04af1-7665-466e-839f-1eb42348aeb0", :path=>"/usr/share/logstash/data/uuid"}
[INFO ] 2022-09-15 21:50:27.119 [Api Webserver] agent - Successfully started Logstash API endpoint {:port=>9600, :ssl_enabled=>false}
[INFO ] 2022-09-15 21:50:28.262 [Converge PipelineAction::Create<main>] Reflections - Reflections took 110 ms to scan 1 urls, producing 119 keys and 419 values 
[WARN ] 2022-09-15 21:50:29.084 [Converge PipelineAction::Create<main>] line - Relying on default value of `pipeline.ecs_compatibility`, which may change in a future major release of Logstash. To avoid unexpected changes when upgrading Logstash, please explicitly declare your desired ECS Compatibility mode.
[WARN ] 2022-09-15 21:50:29.119 [Converge PipelineAction::Create<main>] stdin - Relying on default value of `pipeline.ecs_compatibility`, which may change in a future major release of Logstash. To avoid unexpected changes when upgrading Logstash, please explicitly declare your desired ECS Compatibility mode.
[INFO ] 2022-09-15 21:50:29.571 [[main]-pipeline-manager] javapipeline - Starting pipeline {:pipeline_id=>"main", "pipeline.workers"=>2, "pipeline.batch.size"=>125, "pipeline.batch.delay"=>50, "pipeline.max_inflight"=>250, "pipeline.sources"=>["/root/01-stdin-stdout.conf"], :thread=>"#"}
[INFO ] 2022-09-15 21:50:30.906 [[main]-pipeline-manager] javapipeline - Pipeline Java execution initialization time {"seconds"=>1.33}
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by com.jrubystdinchannel.StdinChannelLibrary$Reader (file:/usr/share/logstash/vendor/bundle/jruby/2.5.0/gems/jruby-stdin-channel-0.2.0-java/lib/jruby_stdin_channel/jruby_stdin_channel.jar) to field java.io.FilterInputStream.in
WARNING: Please consider reporting this to the maintainers of com.jrubystdinchannel.StdinChannelLibrary$Reader
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
[INFO ] 2022-09-15 21:50:31.128 [[main]-pipeline-manager] javapipeline - Pipeline started {"pipeline.id"=>"main"}
The stdin plugin is now waiting for input:
[INFO ] 2022-09-15 21:50:31.270 [Agent thread] agent - Pipelines running {:count=>1, :running_pipelines=>[:main], :non_running_pipelines=>[]}
abc
{
"message" => " abc",
"@version" => "1",
"host" => "host3.test.com",
"@timestamp" => 2022-09-15T13:52:02.984Z
}
bbb
{
"message" => "bbb",
"@version" => "1",
"host" => "host3.test.com",
"@timestamp" => 2022-09-15T13:52:06.177Z
}

    2.输入类型

    在上例中，输入类型是stdin，也就是手动输入，而在生产环境中，日志不可能通过手工输入的发生产生，因此stdin通常都是用于测试环境是否搭建成功，下面会介绍几种常见的输入类型。

    2.1 file

    input {
file {
path => ["/tmp/test/*.txt"]
# 从最开始读日志文件（默认是末尾），仅在读取记录没有任何记录的情况下生效，也就是说，在服务停止的时候有新文件产生，服务器启动后可以读取到（旧文件不行）
start_position => "beginning"  
}
}

    文件的读取记录放在/usr/share/logstash/data/plugins/inputs/file/.sincedb_3cd99a80ca58225ec14dc0ac340abb80中

    [root@host3 ~]# cat /usr/share/logstash/data/plugins/inputs/file/.sincedb_3cd99a80ca58225ec14dc0ac340abb80
5874000 0 64768 4 1663254379.147252 /tmp/test/1.txt

    2.2 tcp

    和filebeat一样，Logstash同样支持监听TCP的某一个端口，用来接收日志。可以同时监听多个端口

    这种方式通常用于无法安装客户端的服务器

    也可以使用HTTP协议，配置方法和TCP类似

    [root@host3 ~]#vim 03-tcp-stdout.conf 
input {
tcp {
port => 9999
}
}
output {
stdout {}
}

    [root@host2 ~]# telnet 192.168.19.103 9999
Trying 192.168.19.103...
Connected to 192.168.19.103.
Escape character is '^]'.
123456
test
hello

    {
"message" => "123456\r",
"@version" => "1",
"@timestamp" => 2022-09-15T15:30:23.123Z,
"host" => "host2",
"port" => 51958
}
{
"message" => "test\r",
"@version" => "1",
"@timestamp" => 2022-09-15T15:30:24.494Z,
"host" => "host2",
"port" => 51958
}
{
"message" => "hello\r",
"@version" => "1",
"@timestamp" => 2022-09-15T15:30:26.336Z,
"host" => "host2",
"port" => 51958
}

    2.3 redis

    Logstash支持直接从redis数据库中拿数据。支持三种redis数据类型：

    1. list，表示的redis命令为blpop，代表从redis list的左边获取第一个元素，如无元素则阻塞；
    2. channel，表示的redis命令为subscribe，代表从redis频道获取最新的数据；
    3. pattern_channel，表示的redis命令为psubscribe，代表通过pattern正则表达式匹配频道，获取最新的数据。

    数据类型之间的区别：

    1. channel与pattern_channel的区别在于，pattern_channel可以通过正则表达式匹配多个频道，而channel是单一频道；
    2. list与另外两个channel的区别在于，1个channel的数据会被多个订阅的logstash重复获取，1个list的数据被多个logstash获取时不会重复，会被分摊在各个Logstash中。

    输入配置如下

    input { 
redis {
data_type => "list"         # 指定数据类型
db => 5                     # 指定数据库，默认是0
host => "192.168.19.101"    # 指定redis服务器IP，默认是localhost
port => 6379
password => "bruce"
key => "test-list"
}
}

    redis中追加数据

    [root@host1 ~]# redis-cli -h host1 -a bruce
host1:6379> select 5
OK
host1:6379[5]> lpush test-list bruce
(integer) 1
host1:6379[5]> lrange test-list 0 -1
(empty list or set)
host1:6379[5]> lpush test-list hello
(integer) 1
host1:6379[5]> lrange test-list 0 -1		# 可以看到，Logstash获取数据后，会将列表清空
(empty list or set)
host1:6379[5]> lpush test-list '{"requestTime":"[12/Sep/2022:23:30:56 +0800]","clientIP":"192.168.19.1","threadID":"http-bio-8080-exec-7","protocol":"HTTP/1.1","requestMethod":"GET / HTTP/1.1","requestStatus":"404","sendBytes":"-","queryString":"","responseTime":"0ms","partner":"-","agentVersion":"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36"}'

    Logstash获取数据

    {
"message" => "bruce",
"@timestamp" => 2022-09-16T08:17:38.213Z,
"@version" => "1",
"tags" => [
[0] "_jsonparsefailure"
]
}
# 非json格式数据会报错，但是能接收
[ERROR] 2022-09-16 16:18:21.688 [[main]<redis] json - JSON parse error, original data now in message field {:message=>"Unrecognized token 'hello': was expecting ('true', 'false' or 'null')
at [Source: (String)\"hello\"; line: 1, column: 11]", :exception=>LogStash::Json::ParserError, :data=>"hello"}
{
"message" => "hello",
"@timestamp" => 2022-09-16T08:18:21.689Z,
"@version" => "1",
"tags" => [
[0] "_jsonparsefailure"
]
}
# json格式的数据过来，Logstash可以自动解析
{
"clientIP" => "192.168.19.1",
"requestTime" => "[12/Sep/2022:23:30:56 +0800]",
"queryString" => "",
"@version" => "1",
"agentVersion" => "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36",
"partner" => "-",
"@timestamp" => 2022-09-16T08:23:10.320Z,
"protocol" => "HTTP/1.1",
"requestStatus" => "404",
"threadID" => "http-bio-8080-exec-7",
"requestMethod" => "GET / HTTP/1.1",
"sendBytes" => "-",
"responseTime" => "0ms"
}

    2.4 beats

    在FileBeat中已经配置好了将日志输出到Logstash，在Logstash中，只需要接收数据即可。

    filebeat配置

    filebeat.inputs:
- type: log
paths: /tmp/1.txt
output.logstash:
hosts: ["192.168.19.103:5044"]

    Logstash配置

    input { 
beats {
port => 5044
}
}

    host2上在/tmp/1.txt中追加111，Logstash的输出

    {
"message" => "111",
"tags" => [
[0] "beats_input_codec_plain_applied"
],
"agent" => {
"id" => "76b7876b-051a-4df8-8b13-bd013ac5ec59",
"version" => "7.17.4",
"hostname" => "host2.test.com",
"type" => "filebeat",
"name" => "host2.test.com",
"ephemeral_id" => "437ac89f-7dc3-4898-a457-b2452ac4223b"
},
"input" => {
"type" => "log"
},
"host" => {
"name" => "host2.test.com"
},
"log" => {
"offset" => 0,
"file" => {
"path" => "/tmp/1.txt"
}
},
"@version" => "1",
"ecs" => {
"version" => "1.12.0"
},
"@timestamp" => 2022-09-16T08:53:20.975Z
}

    3. 输出类型

    3.1 redis

    redis也可以作为输出类型，配置方式和输入类似

    output { 
redis {
data_type => "list" 
db => 6 
host => "192.168.19.101" 
port => 6379
password => "bruce"
key => "test-list"
}
}

    查看redis数据库

    [root@host1 ~]# redis-cli -h host1 -a bruce
host1:6379> select 6
OK
host1:6379[6]> lrange test-list 0 -1
1) "{\"message\":\"1111\",\"@version\":\"1\",\"@timestamp\":\"2022-09-16T09:12:29.890Z\",\"host\":\"host3.test.com\"}"

    3.2 file

    file类型是输出到本地磁盘保存。

    output { 
file {
path => "/tmp/test-file.log"
}
}

    3.3 elasticsearch

    output { 
elasticsearch {
hosts => ["192.168.19.101:9200","192.168.19.102:9200","192.168.19.103:9200"]
index => "centos-logstash-elasticsearh-%{+YYYY.MM.dd}"
}
}

    4. filter

    filter是一个可选插件，在接收到日志信息后，可以对日志进行格式化，然后再输出。

    4.1 grok

    grok可以用来解析任意文本并进行结构化。该工具适合syslog日志、Apache和其他网络服务器日志。

    ①简单示例

    input {
file {
path => ["/var/log/nginx/access.log*"]
start_position => "beginning"
}
}
filter {
grok {
match => {
"message" => "%{COMBINEDAPACHELOG}"
# "message" => "%{HTTPD_COMMONLOG}"		# 新版本Logstash可能会用这个变量
}
}
}
output {
stdout {}
elasticsearch {
hosts => ["192.168.19.101:9200","192.168.19.102:9200","192.168.19.103:9200"]
index => "nginx-logs-es-%{+YYYY.MM.dd}"
}
}

    解析出来的结果：

    {
"request" => "/",
"bytes" => "4833",
"@version" => "1",
"auth" => "-",
"agent" => "\"curl/7.29.0\"",
"path" => "/var/log/nginx/access.log-20220913",
"ident" => "-",
"verb" => "GET",
"message" => "192.168.19.102 - - [12/Sep/2022:21:48:29 +0800] \"GET / HTTP/1.1\" 200 4833 \"-\" \"curl/7.29.0\" \"-\"",
"httpversion" => "1.1",
"host" => "host3.test.com",
"@timestamp" => 2022-09-16T14:27:43.208Z,
"response" => "200",
"timestamp" => "12/Sep/2022:21:48:29 +0800",
"referrer" => "\"-\"",
"clientip" => "192.168.19.102"
}

    ElasticSearch学习笔记之三：Logstash数据分析插图(2)

    ②预定义字段

    grok是基于正则表达式来进行匹配，它的语法格式是%{SYNTAX:SEMANTIC}

    • SYNTAX是将匹配您的文本的模式的名称，这是内置好的语法，官方支持120种字段。
    • SEMANTIC是您为要匹配的文本提供的标识符，也就是你要给它去的名字。

    示例：

    1. 日志源文件
    55.3.244.1 GET /index.html 15824 0.043
    1. 匹配的字段应该是
        %{IP:client} %{WORD:method} %{URIPATHPARAM:request} %{NUMBER:bytes} %{NUMBER:duration}
    1. 配置文件
    input {
stdin {}
}
filter {
grok {
match => { "message" => "%{IP:client} %{WORD:method} %{URIPATHPARAM:request} %{NUMBER:bytes} %{NUMBER:duration}" }
}
}
output {
stdout {}
}
    1. 匹配出来的结果
    55.3.244.1 GET /index.html 15824 0.043
{
"message" => "55.3.244.1 GET /index.html 15824 0.043",
"@version" => "1",
"@timestamp" => 2022-09-16T14:46:46.426Z,
"method" => "GET",
"request" => "/index.html",
"bytes" => "15824",
"duration" => "0.043",
"host" => "host3.test.com",
"client" => "55.3.244.1"
}

    针对不同服务的日志，可以查看官方文档的定义：
    http://github.com/logstash-plugins/logstash-patterns-core/tree/master/patterns

    ③自定义字段

    当预定义的字段不符合要求时，grok也支持自定义正则表达式来匹配日志信息

    1. 首先需要创建自定义表达式保存的目录，并将表达式写进去
    [root@host3 ~]# mkdir patterns
[root@host3 ~]# echo "POSTFIX_QUEUEID [0-9A-F]{10,11}" >> ./patterns/1
    1. 修改配置文件
    input {
stdin {}
}
filter {
grok {
patterns_dir => ["/root/patterns"]											# 指定表达式位置
match => { "message" => "%{SYSLOGBASE} %{POSTFIX_QUEUEID:queue_id}: %{GREEDYDATA:syslog_message}" }	# 这里有系统预定义的，也有自定义的表达式，大括号外的字符就是常规的字符，需要逐个匹配，如冒号: 
}
}
output {
stdout {}
}
    1. 运行并测试
    ...
The stdin plugin is now waiting for input:
[INFO ] 2022-09-16 23:22:04.511 [Agent thread] agent - Pipelines running {:count=>1, :running_pipelines=>[:main], :non_running_pipelines=>[]}
Jan  1 06:25:43 mailserver14 postfix/cleanup[21403]: BEF25A72965: message-id=<20130101142543.5828399CCAF@mailserver14.example.com>
{
"message" => "Jan  1 06:25:43 mailserver14 postfix/cleanup[21403]: BEF25A72965: message-id=<20130101142543.5828399CCAF@mailserver14.example.com>",
"host" => "host3.test.com",
"timestamp" => "Jan  1 06:25:43",
"queue_id" => "BEF25A72965",			# 自定义表达式匹配的字段
"logsource" => "mailserver14",
"@timestamp" => 2022-09-16T15:22:19.516Z,
"program" => "postfix/cleanup",
"pid" => "21403",
"@version" => "1",
"syslog_message" => "message-id=<20130101142543.5828399CCAF@mailserver14.example.com>"
}

    4.2 通用字段

    顾名思义，这些字段可以用在所有属于filter的插件中。

    • remove_field
    filter {
grok {
remove_field => ["@version","tag","agent"]
}
}
    • add_field
    filter {
grok {
add_field => ["new_tag" => "hello world %{YYYY.mm.dd}"]
}
}

    4.3 date

    在数据中，会有两个时间戳timestamp和@timestamp，日志产生的时间和数据采集的时间，这两个时间可能会不一致。
    date插件可以用来转换日志记录中的时间字符串，参考@timestamp字段里的时间。date插件支持五种时间格式：

    • ISO8601
    • UNIX
    • UNIX_MS
    • TAI64N
    input {
file {
path => "/var/log/nginx/access.log*"
start_position => "beginning"
}
}
filter {
grok {
match => { "message" => "%{HTTPD_COMMONLOG}" }
remove_field => ["message","ident","auth","@version","path"]
}
date {
match => [ "timestamp","dd/MMM/yyyy:HH:mm:ss Z" ]		
# timestamp必须是现有的字段，这里只是对这个字段的时间进行校正，且需要和timestamp字段的原数据格式一致，否则会报解析错误
# timestamp原来的数据格式为"17/Sep/2022:18:42:26 +0800"，因此时区改成ZZZ就会一直报错，因为ZZZ代表Asia/Shanghai这种格式，Z代表+0800
timezone => "Asia/Shanghai"
}
}
output {
stdout {}
}

    输出的格式：

    {
"timestamp" => "17/Sep/2022:18:42:26 +0800", #和@timestamp有8小时的时间差，可到Elasticsearch中查看，如果也有时间差，可以在date中修改timezone
"response" => "200",
"httpversion" => "1.1",
"clientip" => "192.168.19.102",
"verb" => "GET",
"host" => "host3.test.com",
"request" => "/",
"@timestamp" => 2022-09-17T10:42:26.000Z,
"bytes" => "4833"
}

    使用target将匹配到的时间字段解析后存储到目标字段，若不指定，默认是@timestamp字段。这个字段在Kibana中创建索引时可以用到

      date {
match => [ "timestamp","dd/MMM/yyyy:HH:mm:ss Z" ]
timezone => "Asia/Shanghai"
target => "logtime"
}
# 结果
{
"timestamp" => "17/Sep/2022:21:15:30 +0800",
"response" => "200",
"logtime" => 2022-09-17T13:15:30.000Z,		# 日志产生的时间
"httpversion" => "1.1",
"clientip" => "192.168.19.102",
"verb" => "GET",
"host" => "host3.test.com",
"request" => "/",
"@timestamp" => 2022-09-17T13:15:31.357Z,		# 日志记录的时间，可以看到和日志产生的时间有一定的延迟
"bytes" => "4833"
}

    4.4 geoip

    用来解析访问IP的位置信息。这个插件是依赖GeoLite2城市数据库，信息不一定准确，也可以自己下载MaxMind格式的数据库然后应用，官方网站有自定义数据库的指导手册。

    input {
file {
path => "/var/log/nginx/access.log*"
start_position => "beginning"
}
}
filter {
grok {
match => { "message" => "%{HTTPD_COMMONLOG}" }
remove_field => ["message","ident","auth","@version","path"]
}
geoip {
source => "clientip" 			# IP地址的源参考clientip字段
# fields => ["country_name" ,"timezone", "city_name"]		# 可以选择显示的字段
}
}
output {
stdout {}
}

    得到的结果，可以看到，私有地址无法正常解析

    {
"timestamp" => "17/Sep/2022:21:15:30 +0800",
"response" => "200",
"geoip" => {},
"httpversion" => "1.1",
"clientip" => "192.168.19.102",
"verb" => "GET",
"host" => "host3.test.com",
"tags" => [
[0] "_geoip_lookup_failure"				# 私网地址
],
"request" => "/",
"@timestamp" => 2022-09-17T13:30:05.178Z,
"bytes" => "4833"
}
{
"timestamp" => "17/Sep/2022:21:15:30 +0800",
"response" => "200",
"geoip" => {					# 解析的结果放在geoip中
"country_code2" => "CM",
"country_code3" => "CM",
"country_name" => "Cameroon",
"ip" => "154.72.162.134",
"timezone" => "Africa/Douala",
"location" => {
"lon" => 12.5,
"lat" => 6.0
},
"continent_code" => "AF",
"latitude" => 6.0,
"longitude" => 12.5
},
"httpversion" => "1.1",
"clientip" => "154.72.162.134",
"verb" => "GET",
"host" => "host3.test.com",
"request" => "/",
"@timestamp" => 2022-09-17T13:30:05.178Z,
"bytes" => "4833"
}

    4.5 useragent

    用来解析浏览器的信息。前提是输出的信息有浏览器信息字段。

    input {
file {
path => "/var/log/nginx/access.log*"
start_position => "beginning"
}
}
filter {
grok {
match => { "message" => "%{HTTPD_COMBINEDLOG}" }		# HTTPD_COMBINEDLOG可以解析浏览器
remove_field => ["message","ident","auth","@version","path"]
}
useragent {
source => "agent"							# 指定浏览器信息在哪个字段中，这个字段必须要存在
target => "agent_test"						# 为了方便查看，将所有解析后的信息放到这个字段里面去
}
}
output {
stdout {}
}

    得到的结果：

    {
"timestamp" => "17/Sep/2022:23:42:31 +0800",
"response" => "404",
"geoip" => {},
"httpversion" => "1.1",
"clientip" => "192.168.19.103",
"verb" => "GET",
"agent" => "\"Mozilla/5.0 (X11; Linux x86_64; rv:60.0) Gecko/20100101 Firefox/60.0\"",
"host" => "host3.test.com",
"request" => "/favicon.ico",
"referrer" => "\"-\"",
"@timestamp" => 2022-09-17T15:42:31.927Z,
"bytes" => "3650",
"agent_test" => {
"major" => "60",
"name" => "Firefox",
"os" => "Linux",
"os_full" => "Linux",
"os_name" => "Linux",
"version" => "60.0",
"minor" => "0",
"device" => "Other"
}
}
{
{
...
"agent_test" => {
"major" => "60",
"name" => "Firefox",
"os" => "Linux",
"os_full" => "Linux",
"os_name" => "Linux",
"version" => "60.0",
"minor" => "0",
"device" => "Other"
}
}
{
...
"agent_test" => {
"os_minor" => "0",
"os_full" => "iOS 16.0",
"version" => "16.0",
"os_major" => "16",
"device" => "iPhone",
"major" => "16",
"name" => "Mobile Safari",
"os" => "iOS",
"os_version" => "16.0",
"os_name" => "iOS",
"minor" => "0"
}
}
{
...
"agent_test" => {
"patch" => "3987",
"os_full" => "Android 10",
"version" => "80.0.3987.162",
"os_major" => "10",
"device" => "Samsung SM-G981B",
"major" => "80",
"name" => "Chrome Mobile",
"os" => "Android",
"os_version" => "10",
"os_name" => "Android",
"minor" => "0"
}
}

    4.6 mutate

    1. 切割自定的字段
    input {
stdin {}
}
filter {
mutate {
split => {
message =>  " "		# 将message消息以空格作为分隔符进行分割
}
remove_field => ["@version","host"]
add_field => {
"tag" => "This a test field from Bruce"
}
}
}
output {
stdout {}
}

    111 222 333
{
"tag" => "This a test field from Bruce",
"message" => [
[0] "111",
[1] "222",
[2] "333"
],
"@timestamp" => 2022-09-18T08:07:36.373Z
}
    1. 将切割后的数据取出来
    input {
stdin {}
}
filter {
mutate {
split => {
message =>  " "		# 将message消息以空格作为分隔符进行分割
}
remove_field => ["@version","host"]
add_field => {
"tag" => "This a test field from Bruce"
}
}
mutate {
add_field => {
"name" => "%{[message][0]}"
"age" => "%{[message][1]}"
"sex" => "%{[message][2]}"
}
}
}
output {
stdout {}
}

    bruce 37 male
{
"message" => [
[0] "bruce",
[1] "37",
[2] "male"
],
"age" => "37",
"@timestamp" => 2022-09-18T08:14:31.230Z,
"sex" => "male",
"tag" => "This a test field from Bruce",
"name" => "bruce"
}
    1. convert：将字段的值转换成不同的类型，例如将字符串转换成证书，如字段值是一个数组，所有成员都会被转换。如果该字段是散列，则不会采取任何动作
    filter {
mutate {
convert => {
"age" => "integer"			# 将age转换成数字类型
}
}
}

    bruce 20 male
{
"message" => [
[0] "bruce",
[1] "20",
[2] "male"
],
"sex" => "male",
"name" => "bruce",
"age" => 20,					# 没有引号，代表已经修改成数字类型了
"@timestamp" => 2022-09-18T08:51:07.633Z,
"tag" => "This a test field from Bruce"
}
    1. strip：剔除字段中的前导和尾随的空格
    filter {
mutate {
strip => { "name","sex" }
}
}
    1. rename：修改字段名
    filter {
mutate {
rename => { "sex" => "agenda" }
}
}
    1. replace：替换字段内容
    filter {
mutate {
replace => { "tag" => "This is test message" }		# 修改了tag字段的内容
}
}

    1. update：用法和replace一样，区别在于如果字段存在则修改内容，如果过不存在则忽略此操作

    2. uppercase/lowercase：转换成大写/小写；capitalize：首字母大写。转换的是字段内容

    filter {
mutate {
uppercase => "tag" 
capitalize => "name" 
}
}

    5 高级特性

    5.1 判断语法

    在input中打上标记后，可以在output和filter中通过判断语句来做区别化的处理

    input {
beats {
port => 8888
type => "nginx-beats"
}
tcp {
port => 9999
type => "tomcat-tcp"
}
}
output { 
if [type] == "nginx-beats" {
elasticsearch {
hosts => ["192.168.19.101:9200","192.168.19.102:9200","192.168.19.103:9200"]
index => "nginx-beats-elasticsearh-%{+YYYY.MM.dd}"
}
} else {
elasticsearch {
hosts => ["192.168.19.101:9200","192.168.19.102:9200","192.168.19.103:9200"]
index => "tomcat-tcp-elasticsearh-%{+YYYY.MM.dd}"
}
}

    5.2 多实例运行

    Logstash支持多实例运行，但是如果直接启动，第二个实例会报错，需要指定path.data的路径才能正常启动。

    [root@host3 ~]# logstash -f 01-stdin-stdout.conf --path.data /tmp/logstash
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