<pre name="code" class="html">grok:
解析任意文本并构造它:
Grok 是当前最好的方式在logstash 解析蹩脚的非结构化日志数据 到一些结构化的可查询的。
这个工具是完美的对于syslog logs, apache和其他webserver logs,mysqllogs,在一般情况下,任何日志格式
通常对于人是友好的而不是对于电脑
Logstash 有120种模式默认,你可以找到它们在:https://github.com/logstash-plugins/logstash-patterns-
core/tree/master/patterns.
Grok Basics:
Grok 通过结合文本模式来匹配你的日志
语法对于一个grok 是 %{SYNTAX:SEMANTIC}
语法是 模式的名字会匹配你的文本,比如,3.44 会通过NUMBER 模式匹配和55.3.244.1 通过IP模式匹配。
语法是你如何匹配:
SEMANTIC (语义)是标识 你给到一块文本被匹配。
比如,3.44 可能是一个一个事件的持续事件,因此你可以简单的调用它。
此外, 一个字符串 55.3.244.1 可能识别客户端发出的请求。
在上述例子中,你的grok filter 可以看起来像这样:
%{NUMBER:duration} %{IP:client}
你可以添加一个数据类型转换成你的grok 模式。默认的 所有的语义都保存作为字符串.
如果你希望 转换一个语义的数据类型,比如改变一个字符串为一个整型 然后将其后缀为目标数据类型。
比如 %{NUMBER:num:int} 会转换num语义从一个字符串到一个整型,当前只支持转换是int和float
例子: 这个质疑的语法和语义,我们可以把有用的字段从一个简单的日志像这个虚构的http 请求日志:
55.3.244.1 GET /index.html 15824 0.043
匹配模式:
%{IP:client} %{WORD:method} %{URIPATHPARAM:request} %{NUMBER:bytes} %{NUMBER:duration}
{
"client": [
"55.3.244.1"
],
"method": [
"GET"
],
"request": [
"/index.html"
],
"bytes": [
"15824"
],
"duration": [
"0.043"
]
}
正则表达式:
Grok 坐在正则表达式之上,因此很多的正则表达式也是正确的在grok里。
正则表达式库是Oniguruma,你可以看到完整的支持的正则表达式的语言在Oniguruma 网站
自定义 模式:
有时候logstash没有你需要的模式,你有几个选项:
第一,你可以使用Oniguruma 语法用于命名捕获 让你匹配一个文件的片段,保存作为字段
(?<field_name>the pattern here)
/********
55.3.244.1 GET /index.html 15824 0.043
(?<field_name>S+)
输出:
{
"field_name": [
"55.3.244.1"
]
}
(?<field_name>S+s+)
输出:多了个空格
{
"field_name": [
"55.3.244.1 "
]
}
(?<field_name>S+s+S+)
输出:
{
"field_name": [
"55.3.244.1 GET"
]
}
例如, 后缀日志有一个队列id 是10或者11 个16进制字符,你可以捕获像这样:
(?<queue_id>[0-9A-F]{10,11})
d4111111112
表达式:
(?<queue_id>[0-9A-F]{10,11})
输出:
{
"queue_id": [
"4111111112"
]
}
或者,你也可以创建一个自定义模式的文件:
创建一个目录叫做patterns 里面有个文件叫做extra(文件名不重要,但是名字得对你有意义)
在这个文件中,写pattern 你需要的作为pattern名字,一个空格,然后正则用于哪个模式
例如: 后缀队列id例子:
# contents of ./patterns/postfix:
POSTFIX_QUEUEID [0-9A-F]{10,11}
Jan 1 06:25:43 mailserver14 postfix/cleanup[21403]: BEF25A72965: message-
id=<20130101142543.5828399CCAF@mailserver14.example.com>
filter {
grok {
patterns_dir => ["./patterns"]
match => { "message" => "%{SYSLOGBASE} %{POSTFIX_QUEUEID:queue_id}: %{GREEDYDATA:syslog_message}" }
}
}
上面的会被匹配,结果是下面的字段:
timestamp: Jan 1 06:25:43
logsource: mailserver14
program: postfix/cleanup
pid: 21403
queue_id: BEF25A72965
syslog_message: message-id=<20130101142543.5828399CCAF@mailserver14.example.com>
timestamp, logsource, program, 和pid 来自SYSLOGBASE 模式本身定义了一些模式
/*******************
zjtest7-frontend:/usr/local/logstash-2.3.4/config# pwd
/usr/local/logstash-2.3.4/config
zjtest7-frontend:/usr/local/logstash-2.3.4/config# ls -lr patterns/
total 4
-rw-r--r-- 1 root root 32 Aug 30 13:33 postfix
zjtest7-frontend:/usr/local/logstash-2.3.4/config/patterns# cat postfix
POSTFIX_QUEUEID [0-9A-F]{10,11}
zjtest7-frontend:/usr/local/logstash-2.3.4/config# cat stdin.conf
input {
stdin {
}
}
filter {
grok {
patterns_dir => ["./patterns"]
match => { "message" => "%{SYSLOGBASE} %{POSTFIX_QUEUEID:queue_id}: %{GREEDYDATA:syslog_message}" }
}
}
output {
stdout {
codec=>rubydebug{}
}
}
zjtest7-frontend:/usr/local/logstash-2.3.4/config# ../bin/logstash -f stdin.conf
Settings: Default pipeline workers: 1
Pipeline main started
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>",
"@version" => "1",
"@timestamp" => "2016-08-30T05:34:11.849Z",
"host" => "0.0.0.0",
"timestamp" => "Jan 1 06:25:43",
"logsource" => "mailserver14",
"program" => "postfix/cleanup",
"pid" => "21403",
"queue_id" => "BEF25A72965",
"syslog_message" => "message-id=<20130101142543.5828399CCAF@mailserver14.example.com>"
}
简介:
插件支持下面的配置选项:
需要的配置选项:
grok {
}
细节:
add_field
1.值类型是hash
2. 默认值是{}
如果 filter 是成功的,增加任何属性字段到这个事件,Field名字可以动态的和包含event部分使用%{field}.
filter {
grok {
add_field => { "foo_%{somefield}" => "Hello world, from %{host}" }
patterns_dir => ["./patterns"]
match => { "message" => "%{SYSLOGBASE} %{POSTFIX_QUEUEID:queue_id}: %{GREEDYDATA:syslog_message}" }
}
}
输出;
zjtest7-frontend:/usr/local/logstash-2.3.4/config# ../bin/logstash -f stdin.conf
Settings: Default pipeline workers: 1
Pipeline main started
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>",
"@version" => "1",
"@timestamp" => "2016-08-30T05:44:35.071Z",
"host" => "0.0.0.0",
"timestamp" => "Jan 1 06:25:43",
"logsource" => "mailserver14",
"program" => "postfix/cleanup",
"pid" => "21403",
"queue_id" => "BEF25A72965",
"syslog_message" => "message-id=<20130101142543.5828399CCAF@mailserver14.example.com>",
"foo_%{somefield}" => "Hello world, from 0.0.0.0"
}
##你可以一次增加多个字段:
filter {
grok {
add_field => { "foo_%{somefield}" => "Hello world, from %{host}"
"new_field" => "new_static_value"
}
patterns_dir => ["./patterns"]
match => { "message" => "%{SYSLOGBASE} %{POSTFIX_QUEUEID:queue_id}: %{GREEDYDATA:syslog_message}" }
}
}
输出;
zjtest7-frontend:/usr/local/logstash-2.3.4/config# ../bin/logstash -f stdin.conf
Settings: Default pipeline workers: 1
Pipeline main started
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>",
"@version" => "1",
"@timestamp" => "2016-08-30T05:46:37.029Z",
"host" => "0.0.0.0",
"timestamp" => "Jan 1 06:25:43",
"logsource" => "mailserver14",
"program" => "postfix/cleanup",
"pid" => "21403",
"queue_id" => "BEF25A72965",
"syslog_message" => "message-id=<20130101142543.5828399CCAF@mailserver14.example.com>",
"foo_%{somefield}" => "Hello world, from 0.0.0.0",
"new_field" => "new_static_value"
add_tag
1.值类型是array
2.默认是[]
如果filter 成功,增加任意的tags 到这个事件。Tags 可以动态的包含事件的部分使用%{field} syntax.
filter {
grok {
add_tag => [ "foo_%{somefield}" ]
}
}
# You can also add multiple tags at once:
filter {
grok {
add_tag => [ "foo_%{somefield}", "taggedy_tag"]
}
}
zjtest7-frontend:/usr/local/logstash-2.3.4/config# ../bin/logstash -f stdin.conf
Settings: Default pipeline workers: 1
Pipeline main started
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>",
"@version" => "1",
"@timestamp" => "2016-08-30T05:50:18.451Z",
"host" => "0.0.0.0",
"timestamp" => "Jan 1 06:25:43",
"logsource" => "mailserver14",
"program" => "postfix/cleanup",
"pid" => "21403",
"queue_id" => "BEF25A72965",
"syslog_message" => "message-id=<20130101142543.5828399CCAF@mailserver14.example.com>",
"foo_%{somefield}" => "Hello world, from 0.0.0.0",
"new_field" => "new_static_value",
"tags" => [
[0] "foo_%{somefield}"
]
}
break_on_match
1.值类型是波尔型
2.默认值是true
Break 在第一个匹配,第一次成功匹配通过grok 会导致filter 被完成。如果你需要grok 尝试所有的patterns(
可能解析不同的东西),设置这个为false
match:
1.值类型是hash
2.默认是{}
filter {
grok { match => { "message" => "Duration: %{NUMBER:duration}" } }
}