Logstash 日志收集切割及注意事项
一、Logstash收集日志
1.Logstash的配置文件
[root@web01 ~]# vim /etc/logstash/logstash.yml
path.config: /etc/logstash/conf.d
2.logstash收集日志文件到文件
[root@web01 ~]# vim /etc/logstash/conf.d/file_file.conf
input {
file {
path => "/var/log/messages"
start_position => "beginning"
}
}
output {
file {
path => "/tmp/messages_%{+YYYY-MM-dd}.log"
}
}
3.logstash收集日志文件到ES
[root@web01 ~]# vim /etc/logstash/conf.d/file_es.conf
input {
file {
path => "/var/log/messages"
start_position => "beginning"
}
}
output {
elasticsearch {
hosts => ["172.16.1.51:9200"]
index => "messages_%{+YYYY-MM-dd}.log"
}
}
4.Logstash收集多日志到文件
[root@web01 ~]# vim /etc/logstash/conf.d/file_file.conf
input {
file {
type => "messages_log"
path => "/var/log/messages"
start_position => "beginning"
}
file {
type => "secure_log"
path => "/var/log/secure"
start_position => "beginning"
}
}
output {
if [type] == "messages_log" {
file {
path => "/tmp/messages_%{+YYYY-MM-dd}"
}
}
if [type] == "secure_log" {
file {
path => "/tmp/secure_%{+YYYY-MM-dd}"
}
}
}
5.Logstash收集多日志到ES
1)方法一:
[root@web01 ~]# vim /etc/logstash/conf.d/more_es.conf
input {
file {
type => "messages_log"
path => "/var/log/messages"
start_position => "beginning"
}
file {
type => "secure_log"
path => "/var/log/secure"
start_position => "beginning"
}
}
output {
if [type] == "messages_log" {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "messages_%{+YYYY-MM-dd}"
}
}
if [type] == "secure_log" {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "secure_%{+YYYY-MM-dd}"
}
}
}
[root@web01 ~]# /usr/share/logstash/bin/logstash -f /etc/logstash/conf.d/more_es.conf &
#启动后查看页面
2)方法二:
[root@web01 ~]# vim /etc/logstash/conf.d/more_es_2.conf
input {
file {
type => "messages_log"
path => "/var/log/messages"
start_position => "beginning"
}
file {
type => "secure_log"
path => "/var/log/secure"
start_position => "beginning"
}
}
output {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "%{type}_%{+YYYY-MM-dd}"
}
}
[root@web01 ~]# /usr/share/logstash/bin/logstash -f /etc/logstash/conf.d/more_es_2.conf --path.data=/data/logstash/more_es_2 &
3)启动多实例
#创建不同的数据目录
[root@web01 ~]# mkdir /data/logstash/more_es_2
[root@web01 ~]# mkdir /data/logstash/more_es
#启动时使用--path.data指定数据目录
[root@web01 ~]# /usr/share/logstash/bin/logstash -f /etc/logstash/conf.d/more_es.conf --path.data=/data/logstash/more_es &
[root@web01 ~]# /usr/share/logstash/bin/logstash -f /etc/logstash/conf.d/more_es_2.conf --path.data=/data/logstash/more_es_2 &
#如果资源充足,可以使用多实例收集多日志,如果服务器资源不足,启动不了多实例,配置一个文件收集多日志启动
二、Logstash收集Tomcat日志
1.安装Tomcat
1.安装java环境
[root@web01 ~]# rpm -ivh jdk-8u181-linux-x64.rpm
2.上传包
[root@web01 ~]# rz apache-tomcat-10.0.0-M7.tar.gz
3.解压
[root@web01 ~]# tar xf apache-tomcat-10.0.0-M7.tar.gz -C /usr/local/
4.做软连接
[root@web01 ~]# ln -s /usr/local/apache-tomcat-10.0.0-M7 /usr/local/tomcat
5.启动Tomcat
[root@web01 ~]# /usr/local/tomcat/bin/startup.sh
6.访问页面 10.0.0.7:8080
2.配置Logstash收集Tomcat日志到文件
[root@web01 ~]# vim /etc/logstash/conf.d/tomcat_file.conf
input {
file {
path => "/usr/local/tomcat/logs/localhost_access_log.*.txt"
start_position => "beginning"
}
}
output {
file {
path => "/tmp/tomcat_%{+YYYY-MM-dd}.log"
}
}
3.配置Logstash收集Tomcat日志到ES
[root@web01 ~]# vim /etc/logstash/conf.d/tomcat_es.conf
input {
file {
path => "/usr/local/tomcat/logs/localhost_access_log.*.txt"
start_position => "beginning"
}
}
output {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "tomcat_%{+YYYY-MM-dd}.log"
}
}
三、收集Tomcat日志修改格式
#收集tomcat日志,当遇到报错时,一条报错会被分割成很多条数据,不方便查看
解决方法:
1.修改tomcat日志格式为json
1)开发修改输出日志为json
2)修改tomcat配置,日志格式为json
2.使用logstash的input插件下的mutiline模块
1.方法一:修改tomcat日志格式
1)配置tomcat日志为json格式
[root@web01 ~]# vim /usr/local/tomcat/conf/server.xml
#把原来的日志格式注释,添加我们的格式
<Valve className="org.apache.catalina.valves.AccessLogValve" directory="logs"
prefix="tomcat_access_json" suffix=".log"
pattern="{"clientip":"%h","ClientUser":"%l","authenticated":"%u","AccessTime":"%t","method":"%r","status":"%s","SendBytes":"%b","Query?string":"%q","partner":"%{Referer}i","AgentVersion":"%{User-Agent}i"}"/>
2)重启tomcat
[root@web01 ~]# /usr/local/tomcat/bin/shutdown.sh
[root@web01 ~]# /usr/local/tomcat/bin/startup.sh
3)配置收集新的tomcat日志
[root@web01 ~]# vim /etc/logstash/conf.d/tomcat_json_es.conf
input {
file {
path => "/usr/local/tomcat/logs/tomcat_access_json.*.log"
start_position => "beginning"
}
}
output {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "tomcat_json_%{+YYYY-MM-dd}.log"
}
}
2.方法二:使用mutiline模块收集日志
1)配置收集日志测试
[root@web01 ~]# vim /etc/logstash/conf.d/test_mutiline.conf
input {
stdin {
codec => multiline {
#以[开头
pattern => "^\["
#匹配到
negate => true
#向上合并,向下合并是next
what => "previous"
}
}
}
output {
stdout {
codec => json
}
}
#测试,输入内容不会直接输出,当遇到以 [ 开头才会收集以上的日志
2)配置收集tomcat错误日志
[root@web01 ~]# vim /etc/logstash/conf.d/tomcat_mutiline.conf
input {
file {
path => "/usr/local/tomcat/logs/tomcat_access_json.*.log"
start_position => "beginning"
codec => multiline {
pattern => "^\["
negate => true
what => "previous"
}
}
}
output {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "tomcat_json_%{+YYYY-MM-dd}"
codec => "json"
}
}
3)将错误日志写入
[root@web01 ~]# cat 1.txt >> /usr/local/tomcat/logs/tomcat_access_json.2020-08-14.log
4)页面查看数据
在message切割后的key和value处有黄色感叹号.无法制表.
需要进入如下页面处刷新fields即可.
四、收集Nginx日志
1.安装Nginx
[root@web01 ~]# yum install -y nginx
2.配置Nginx日志格式
[root@web01 ~]# vim /etc/nginx/nginx.conf
... ...
http {
log_format json '{"@timestamp":"time_iso8601",'
'"host":"server_addr",'
'"clientip":"remote_addr",'
'"size":body_bytes_sent,'
'"responsetime":request_time,'
'"upstreamtime":"upstream_response_time",'
'"upstreamhost":"upstream_addr",'
'"http_host":"host",'
'"url":"uri",'
'"referer":"http_referer",'
'"agent":"http_user_agent",'
'"status":"status"}';
access_log /var/log/nginx/access.log json;
... ...
3.配置收集Nginx日志
[root@web01 ~]# vim /etc/logstash/conf.d/nginx_json.conf
input {
file {
path => "/var/log/nginx/access.log"
start_position => "beginning"
}
}
output {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "nginx_json_%{+YYYY-MM-dd}.log"
}
}
五、获取的日志参数分离
1.方法一:
1)修改tomcat日志收集配置
[root@web01 ~]# vim /etc/logstash/conf.d/tomcat_json_es.conf
input {
file {
path => "/usr/local/tomcat/logs/tomcat_access_json.*.log"
start_position => "beginning"
}
}
#把收集到的数据进行处理
filter {
json {
source => "message"
}
}
output {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "tomcat_json_%{+YYYY-MM-dd}.log"
}
}
2)去掉多余数据
#message数据已经拆分,数据还在,去掉message数据
filter {
json {
source => "message"
remove_field => ["message"]
}
}
2.方法二:
1)修改收集Nginx日志的配置
#nginx不需要配置修改获取日志,只需要收集同时修改格式即可
[root@web01 ~]# vim /etc/logstash/conf.d/nginx_json.conf
input {
file {
path => "/var/log/nginx/access.log"
start_position => "beginning"
codec => "json"
}
}
output {
elasticsearch {
hosts => ["10.0.0.51:9200"]
index => "nginx_json_%{+YYYY-MM-dd}.log"
}
}
六、Logstash收集日志写入redis
1.安装redis
2.配置将数据写入redis
[root@web01 ~]# vim /etc/logstash/conf.d/nginx_to_redis.conf
input {
file {
path => "/var/log/nginx/access.log"
start_position => "beginning"
codec => "json"
}
}
output {
redis {
host => "172.16.1.51"
port => "6379"
data_type => "list"
db => "0"
key => "nginx_log"
}
}
七、收集切割公司自定义的日志
很多公司的日志并不是和服务默认的日志格式一致,因此,就需要我们来进行切割了。
1、需切割的日志示例
2018-02-24 11:19:23,532 [143] DEBUG performanceTrace 1145 http://api.114995.com:8082/api/Carpool/QueryMatchRoutes 183.205.134.240 null 972533 310000 TITTL00 HUAWEI 860485038452951 3.1.146 HUAWEI 5.1 113.552344 33.332737 发送响应完成 Exception:(null)
2、切割的配置
在logstash 上,使用fifter 的grok 插件进行切割
input {
beats {
port => "5044"
}
}
filter {
grok {
match => {
"message" => "%{TIMESTAMP_ISO8601:timestamp} \[%{NUMBER:thread:int}\] %{DATA:level} (?<logger>[a-zA-Z]+) %{NUMBER:executeTime:int} %{URI:url} %{IP:clientip} %{USERNAME:UserName} %{NUMBER:userid:int} %{NUMBER:AreaCode:int} (?<Board>[0-9a-zA-Z]+[-]?[0-9a-zA-Z]+) (?<Brand>[0-9a-zA-Z]+[-]?[0-9a-zA-Z]+) %{NUMBER:DeviceId:int} (?<TerminalSourceVersion>[0-9a-z\.]+) %{NUMBER:Sdk:float} %{NUMBER:Lng:float} %{NUMBER:Lat:float} (?<Exception>.*)"
}
remove_field => "message"
}
date {
match => ["timestamp","dd/MMM/YYYY:H:m:s Z"]
remove_field => "timestamp"
}
geoip {
source => "clientip"
target => "geoip"
database => "/etc/logstash/maxmind/GeoLite2-City.mmdb"
}
}
output {
elasticsearch {
hosts => ["http://192.168.10.101:9200/"]
index => "logstash-%{+YYYY.MM.dd}"
document_type => "apache_logs"
}
}
3、切割解析后效果
4、最终kibana 展示效果
① top10 clientip
② top5 url
③ 根据ip 显示地理位置
⑤ top10 executeTime
⑥ 其他字段都可进行设置,多种图案,也可将多个图形放在一起展示
八、grok 用法详解
1、简介
Grok是迄今为止使蹩脚的、无结构的日志结构化和可查询的最好方式。Grok在解析 syslog logs、apache and other webserver logs、mysql logs等任意格式的文件上表现完美。
Grok内置了120多种的正则表达式库,地址:https://github.com/logstash-plugins/logstash-patterns-core/tree/master/patterns。
2、入门例子
① 示例
55.3.244.1 GET /index.html 15824 0.043
② 分析
这条日志可切分为5个部分,IP(55.3.244.1)、方法(GET)、请求文件路径(/index.html)、字节数(15824)、访问时长(0.043),对这条日志的解析模式(正则表达式匹配)如下:
%{IP:client} %{WORD:method} %{URIPATHPARAM:request} %{NUMBER:bytes} %{NUMBER:duration}
③ 写到filter中
filter { grok { match => { "message" => "%{IP:client} %{WORD:method} %{URIPATHPARAM:request} %{NUMBER:bytes} %{NUMBER:duration}"} } }
④ 解析后效果
client: 55.3.244.1
method: GET
request: /index.html
bytes: 15824
duration: 0.043
3、解析任意格式日志
(1)解析任意格式日志的步骤:
① 先确定日志的切分原则,也就是一条日志切分成几个部分。
② 对每一块进行分析,如果Grok中正则满足需求,直接拿来用。如果Grok中没用现成的,采用自定义模式。
③ 学会在Grok Debugger中调试。
(2)grok 的分类
- 满足自带的grok 正则 grok_pattern
① 可以查询
# less /usr/share/logstash/vendor/bundle/jruby/1.9/gems/logstash-patterns-core-4.1.1/patterns/grok-patterns
② 使用格式
grok_pattern 由零个或多个 %{SYNTAX:SEMANTIC}组成
例: %{IP:clientip}
其中SYNTAX 是表达式的名字,是由grok提供的:例如数字表达式的名字是NUMBER,IP地址表达式的名字是IP
SEMANTIC 表示解析出来的这个字符的名字,由自己定义,例如IP字段的名字可以是 client
- 自定义SYNTAX
使用格式:(?
例:(?
(3)正则解析容易出错,强烈建议使用Grok Debugger调试,姿势如下(我打开这个网页不能用)
九、使用mysql 模块,收集mysql 日志
1、官方文档使用介绍
https://www.elastic.co/guide/en/beats/filebeat/current/filebeat-module-mysql.html
2、配置filebeat ,使用mysql 模块收集mysql 的慢查询
# vim filebeat.yml
#=========================== Filebeat prospectors =============================
filebeat.modules:
- module: mysql
error:
enabled: true
var.paths: ["/var/log/mariadb/mariadb.log"]
slowlog:
enabled: true
var.paths: ["/var/log/mariadb/mysql-slow.log"]
#----------------------------- Redis output --------------------------------
output.redis:
hosts: ["192.168.10.102"]
password: "ilinux.io"
key: "httpdlogs"
datatype: "list"
db: 0
timeout: 5
3、elk—logstash 切割mysql 的慢查询日志
① 切割配置
# vim mysqllogs.conf
input {
redis {
host => "192.168.10.102"
port => "6379"
password => "ilinux.io"
data_type => "list"
key => "httpdlogs"
threads => 2
}
}
filter {
grok {
match => { "message" => "(?m)^#\s+User@Host:\s+%{USER:user}\[[^\]]+\]\s+@\s+(?:(?<clienthost>\S*) )?\[(?:%{IPV4:clientip})?\]\s+Id:\s+%{NUMBER:row_id:int}\n#\s+Query_time:\s+%{NUMBER:query_time:float}\s+Lock_time:\s+%{NUMBER:lock_time:float}\s+Rows_sent:\s+%{NUMBER:rows_sent:int}\s+Rows_examined:\s+%{NUMBER:rows_examined:int}\n\s*(?:use %{DATA:database};\s*\n)?SET\s+timestamp=%{NUMBER:timestamp};\n\s*(?<sql>(?<action>\w+)\b.*;)\s*(?:\n#\s+Time)?.*$" }
}
date {
match => ["timestamp","dd/MMM/YYYY:H:m:s Z"]
remove_field => "timestamp"
}
}
output {
elasticsearch {
hosts => ["http://192.168.10.101:9200/"]
index => "logstash-%{+YYYY.MM.dd}"
document_type => "mysql_logs"
}
}
② 切割后显示结果
4、kibana 最终显示效果
① 哪几个的数据库最多,例:top2 库
表无法显示,因为有些语句不涉及表,切割不出来
② 哪几个sql语句出现的最多,例:top5 sql语句
③ 哪几个sql语句出现的最多,例:top5 sql语句
④ 哪几台服务器慢查询日志生成的最多,例:top5 服务器
⑤ 哪几个用户慢查询日志生成的最多,例:top2 用户
可以合并显示
5、使用mysql 模块收集mysql 的慢查询
(1)filebeat 配置和上边一样
(2)elk—logstash 切割mysql 的错误日志
# vim mysqllogs.conf
filter {
grok {
match => { "message" => "(?<timestamp>\d{4}-\d{2}-\d{2}\s+\d{2}:\d{2}:\d{2}) %{NUMBER:pid:int} \[%{DATA:level}\] (?<content>.*)" }
}
date {
match => ["timestamp","dd/MMM/YYYY:H:m:s Z"]
remove_field => "timestamp"
}
}
(3)就不在展示结果了
十、ELK 收集多实例日志
很多情况下,公司资金不足,不会一对一收集日志;因此,一台logstash 使用多实例收集处理多台agent 的日志很有必要。
1、filebeat 的配置
主要是output 的配置,只需不同agent 指向不同的端口即可
① agent 1 配置指向5044 端口
#----------------------------- Logstash output --------------------------------
output.logstash:
# The Logstash hosts
hosts: ["192.168.10.107:5044"]
② agent 2 配置指向5045 端口
#----------------------------- Logstash output --------------------------------
output.logstash:
# The Logstash hosts
hosts: ["192.168.10.107:5045"]
2、logstash 的配置
针对不同的agent ,input 指定对应的端口
① agent 1
input {
beats {
port => "5044"
}
}
output { #可以在output 加以区分
elasticsearch {
hosts => ["http://192.168.10.107:9200/"]
index => "logstash-apache1-%{+YYYY.MM.dd}"
document_type => "apache1_logs"
}
}
② agent 1
input {
beats {
port => "5045"
}
}
output { #可以在output 加以区分
elasticsearch {
hosts => ["http://192.168.10.107:9200/"]
index => "logstash-apache2-%{+YYYY.MM.dd}"
document_type => "apache2_logs"
}
}
开启对应的服务就ok 了。
十一、elk 注意点总结
1、编码转换问题(主要就是中文乱码)
(1)input 中的codec => plain 转码
codec => plain {
charset => "GB2312"
}
将GB2312 的文本编码,转为UTF-8 的编码
(2)也可以在filebeat中实现编码的转换(推荐)
filebeat.prospectors:
- input_type: log
paths:
- c:\Users\Administrator\Desktop\performanceTrace.txt
encoding: GB2312
2、删除多余日志中的多余行
(1)logstash filter 中drop 删除
if ([message] =~ "^20.*-\ task\ request,.*,start\ time.*") { #用正则需删除的多余行
drop {}
}
(2)日志示例
2018-03-20 10:44:01,523 [33]DEBUG Debug - task request,task Id:1cbb72f1-a5ea-4e73-957c-6d20e9e12a7a,start time:2018-03-20 10:43:59 #需删除的行
-- Request String : {"UserName":"15046699923","Pwd":"ZYjyh727","DeviceType":2,"DeviceId":"PC-20170525SADY","EquipmentNo":null,"SSID":"pc","RegisterPhones":null,"AppKey":"ab09d78e3b2c40b789ddfc81674bc24deac","Version":"2.0.5.3"} -- End
-- Response String : {"ErrorCode":0,"Success":true,"ErrorMsg":null,"Result":null,"WaitInterval":30} -- End
3、grok 处理多种日志不同的行
(1)日志示例:
2018-03-20 10:44:01,523 [33]DEBUG Debug - task request,task Id:1cbb72f1-a5ea-4e73-957c-6d20e9e12a7a,start time:2018-03-20 10:43:59
-- Request String : {"UserName":"15046699923","Pwd":"ZYjyh727","DeviceType":2,"DeviceId":"PC-20170525SADY","EquipmentNo":null,"SSID":"pc","RegisterPhones":null,"AppKey":"ab09d78e3b2c40b789ddfc81674bc24deac","Version":"2.0.5.3"} -- End
-- Response String : {"ErrorCode":0,"Success":true,"ErrorMsg":null,"Result":null,"WaitInterval":30} -- End
(2)在logstash filter中grok 分别处理3行
match => {
"message" => "^20.*-\ task\ request,.*,start\ time\:%{TIMESTAMP_ISO8601:RequestTime}"
match => {
"message" => "^--\ Request\ String\ :\ \{\"UserName\":\"%{NUMBER:UserName:int}\",\"Pwd\":\"(?<Pwd>.*)\",\"DeviceType\":%{NUMBER:DeviceType:int},\"DeviceId\":\"(?<DeviceId>.*)\",\"EquipmentNo\":(?<EquipmentNo>.*),\"SSID\":(?<SSID>.*),\"RegisterPhones\":(?<RegisterPhones>.*),\"AppKey\":\"(?<AppKey>.*)\",\"Version\":\"(?<Version>.*)\"\}\ --\ \End.*"
}
match => {
"message" => "^--\ Response\ String\ :\ \{\"ErrorCode\":%{NUMBER:ErrorCode:int},\"Success\":(?<Success>[a-z]*),\"ErrorMsg\":(?<ErrorMsg>.*),\"Result\":(?<Result>.*),\"WaitInterval\":%{NUMBER:WaitInterval:int}\}\ --\ \End.*"
}
... 等多行
4、日志多行合并处理—multiline插件(重点)
(1)示例:
① 日志
2018-03-20 10:44:01,523 [33]DEBUG Debug - task request,task Id:1cbb72f1-a5ea-4e73-957c-6d20e9e12a7a,start time:2018-03-20 10:43:59
-- Request String : {"UserName":"15046699923","Pwd":"ZYjyh727","DeviceType":2,"DeviceId":"PC-20170525SADY","EquipmentNo":null,"SSID":"pc","RegisterPhones":null,"AppKey":"ab09d78e3b2c40b789ddfc81674bc24deac","Version":"2.0.5.3"} -- End
-- Response String : {"ErrorCode":0,"Success":true,"ErrorMsg":null,"Result":null,"WaitInterval":30} -- End
② logstash grok 对合并后多行的处理(合并多行后续都一样,如下)
filter {
grok {
match => {
"message" => "^%{TIMESTAMP_ISO8601:InsertTime}\ .*-\ task\ request,.*,start\ time:%{TIMESTAMP_ISO8601:RequestTime}\n--\ Request\ String\ :\ \{\"UserName\":\"%{NUMBER:UserName:int}\",\"Pwd\":\"(?<Pwd>.*)\",\"DeviceType\":%{NUMBER:DeviceType:int},\"DeviceId\":\"(?<DeviceId>.*)\",\"EquipmentNo\":(?<EquipmentNo>.*),\"SSID\":(?<SSID>.*),\"RegisterPhones\":(?<RegisterPhones>.*),\"AppKey\":\"(?<AppKey>.*)\",\"Version\":\"(?<Version>.*)\"\}\ --\ \End\n--\ Response\ String\ :\ \{\"ErrorCode\":%{NUMBER:ErrorCode:int},\"Success\":(?<Success>[a-z]*),\"ErrorMsg\":(?<ErrorMsg>.*),\"Result\":(?<Result>.*),\"WaitInterval\":%{NUMBER:WaitInterval:int}\}\ --\ \End"
}
}
}
(2)在filebeat中使用multiline 插件(推荐)
① 介绍multiline
pattern:正则匹配从哪行合并
negate:true/false,匹配到pattern 部分开始合并,还是不配到的合并
match:after/before(需自己理解)
after:匹配到pattern 部分后合并,注意:这种情况最后一行日志不会被匹配处理
before:匹配到pattern 部分前合并(推荐)
② 5.5版本之后(before为例)
filebeat.prospectors:
- input_type: log
paths:
- /root/performanceTrace*
fields:
type: zidonghualog
multiline.pattern: '.*\"WaitInterval\":.*--\ End'
multiline.negate: true
multiline.match: before
③ 5.5版本之前(after为例)
filebeat.prospectors:
- input_type: log
paths:
- /root/performanceTrace*
input_type: log
multiline:
pattern: '^20.*'
negate: true
match: after
(3)在logstash input中使用multiline 插件(没有filebeat 时推荐)
① 介绍multiline
pattern:正则匹配从哪行合并
negate:true/false,匹配到pattern 部分开始合并,还是不配到的合并
what:previous/next(需自己理解)
previous:相当于filebeat 的after
next:相当于filebeat 的before
② 用法
input {
file {
path => ["/root/logs/log2"]
start_position => "beginning"
codec => multiline {
pattern => "^20.*"
negate => true
what => "previous"
}
}
}
(4)在logstash filter中使用multiline 插件(不推荐)
(a)不推荐的原因:
① filter设置multiline后,pipline worker会自动将为1
② 5.5 版本官方把multiline 去除了,要使用的话需下载,下载命令如下:
/usr/share/logstash/bin/logstash-plugin install logstash-filter-multiline
(b)示例:
filter {
multiline {
pattern => "^20.*"
negate => true
what => "previous"
}
}
5、logstash filter 中的date使用
(1) 日志示例
2018-03-20 10:44:01 [33]DEBUG Debug - task request,task Id:1cbb72f1-a5ea-4e73-957c-6d20e9e12a7a,start time:2018-03-20 10:43:59
(2) date 使用
date {
match => ["InsertTime","YYYY-MM-dd HH:mm:ss "]
remove_field => "InsertTime"
}
注:
match => ["timestamp" ,"dd/MMM/YYYY H:m:s Z"]
匹配这个字段,字段的格式为:日日/月月月/年年年年 时/分/秒 时区
也可以写为:match => ["timestamp","ISO8601"](推荐)
(3)date 介绍
就是将匹配日志中时间的key 替换为@timestamp 的时间,因为@timestamp 的时间是日志送到logstash 的时间,并不是日志中真正的时间。
6、对多类日志分类处理(重点)
① 在filebeat 的配置中添加type 分类
filebeat:
prospectors:
-
paths:
#- /mnt/data/WebApiDebugLog.txt*
- /mnt/data_total/WebApiDebugLog.txt*
fields:
type: WebApiDebugLog_total
-
paths:
- /mnt/data_request/WebApiDebugLog.txt*
#- /mnt/data/WebApiDebugLog.txt*
fields:
type: WebApiDebugLog_request
-
paths:
- /mnt/data_report/WebApiDebugLog.txt*
#- /mnt/data/WebApiDebugLog.txt*
fields:
type: WebApiDebugLog_report
② 在logstash filter中使用if,可进行对不同类进行不同处理
filter {
if [fields][type] == "WebApiDebugLog_request" { #对request 类日志
if ([message] =~ "^20.*-\ task\ report,.*,start\ time.*") { #删除report 行
drop {}
}
grok {
match => {"... ..."}
}
}
③ 在logstash output中使用if
if [fields][type] == "WebApiDebugLog_total" {
elasticsearch {
hosts => ["6.6.6.6:9200"]
index => "logstashl-WebApiDebugLog_total-%{+YYYY.MM.dd}"
document_type => "WebApiDebugLog_total_logs"
}