FMT="1358 15:41:07W19/03/21 (A) Interlocking Link 116 Restored" STY="A" AMSEQ="LINKFAIL" AMSST="RTN" ALTID="1358" TS="20210319154107" CP="LOC A" CP="LOC X" MP="104.95" MP="104.95" EQ="MDIPRIMARYOFF" POS="TC-NORTH"
The log format is as above. I would like to capture the following fields using grok
Time - 15:41:07
Date - 19/03/21
Message - Interlocking Link 116 Restored
Location - Loc X
Anyone help with creating grok pattern that I can use on my logstash filter to parse my logs?
I would not use grok to start with. This is key/value data, so a kv filter will get you started, then you can grok the parts of the FMT field out.
kv { include_keys => [ "FMT", "CP" ] target => "[#metadata]" }
mutate { add_field => { "Location" => "%{[#metadata][CP][1]}" } }
grok { match => { "[#metadata][FMT]" => "%{NUMBER} %{TIME:Time}W%{DATE_EU:Date} \(%{WORD}\) %{GREEDYDATA:Message}" } }
will result in
"Message" => "Interlocking Link 116 Restored",
"Date" => "19/03/21",
"Time" => "15:41:07",
"Location" => "LOC X",
Although having multiple CP fields feels fragile.
The include_keys option on the kv filter tells the filter to ignore other keys. Using target to put the fields under [#metadata] means they are available to other filters but are not sent to the output. The remove_field option on the kv filter is only processed if the filter is able to parse the message, so if your kv data is invalid you will have a [message] field on the event that you can look at.
Related
I am trying to index a document in ElasticSearch through logstash. An example from the file I am trying to index is as follows
GET firstname=john&lastname=smith 400
My objective is to create an index that looks something like the following
HTTPMethod: GET
firstname : john
lastname: smith
query_time : 400
I did the following so far
filter {
grok{
match => {"message" => "%{WORD:HttpMethod} %{GREEDYDATA:KVText} %{NUMBER:time:int}"}
}
kv {
source => "KVText"
value_split => "&"
remove_field => [ "KVText" ]
}
}
However, when I execute the logstash conf file I see the following
"query_time": 400,
"message": "GET firstname=john&lastname=smith 400\r",
"HttpMethod": "GET",
"firstname=john": "lastname=smith"
I am not getting the index as a key1=value1 format as discrete values. e.g. firstname=john lastname=smith
Also, whenever I make a change to my log file the logstash process doesn't pick the change for indexing in real time. I have to rename the file and restart logstash. I do understand it has something to do with the since_db path in my logstash.conf.
Any pointers are truly appreciated.
Thanks
Nick
You are configuring the kv filter the wrong way.
The value_split param tells the filter what char to use for splitting one key/value pair (you should put "=") while the field_split config tells what char to use to split pairs from the string. Try using:
kv {
source => "KVText"
value_split => "="
field_split => "&"
remove_field => [ "KVText" ]
}
I am trying to stash a log file to elasticsearch using Logstash. I am facing a problem while doing this.
If the log file has same kind of log lines like the below,
[12/Sep/2016:18:23:07] VendorID=5037 Code=C AcctID=5317605039838520
[12/Sep/2016:18:23:22] VendorID=9108 Code=A AcctID=2194850084423218
[12/Sep/2016:18:23:49] VendorID=1285 Code=F AcctID=8560077531775179
[12/Sep/2016:18:23:59] VendorID=1153 Code=D AcctID=4433276107716482
where the date, vendorId, code and acctID's order of occurrence of fields does not change or a new element is not added in to it, then the filter(given below) in the config files work well.
\[%{MONTHDAY}/%{MONTH}/%{YEAR}:%{TIME}\] VendorID=%{INT:VendorID} Code=%{WORD:Code} AcctID=%{INT:AcctID}
Suppose the order changes like the example given below or if a new element is added to one of the log lines, then the grokparsefailure occurs.
[12/Sep/2016:18:23:07] VendorID=5037 Code=C AcctID=5317605039838520
[12/Sep/2016:18:23:22] VendorID=9108 Code=A AcctID=2194850084423218
[12/Sep/2016:18:23:49] VendorID=1285 Code=F AcctID=8560077531775179
[12/Sep/2016:18:23:59] VendorID=1153 Code=D AcctID=4433276107716482
[12/Sep/2016:18:24:50] AcctID=3168124750473449 VendorID=1065 Code=L
[12/Sep/2016:18:24:50] AcctID=3168124750473449 VendorID=1065 Code=L
[12/Sep/2016:18:24:50] AcctID=3168124750473449 VendorID=1065 Code=L
Here in the example, the last three log lines are different from the first four log lines in order of occurrence of the fields. And because of this, the filter message with the grok pattern could not parse the below three lines as it is written for the first four lines.
How should I handle this scenario, when i come across this case? Please help me solve this problem. Also provide any link to any document for detailed explanation with examples.
Thank you very much in advance.
As correctly pointed out by baudsp, this can be achieved by multiple grok filters. The KV filter seems like a nicer option, but as for grok, this is one solution:
input {
stdin {}
}
filter {
grok {
match => {
"message" => ".*test1=%{INT:test1}.*"
}
}
grok {
match => {
"message" => ".*test2=%{INT:test2}.*"
}
}
}
output {
stdout { codec => rubydebug }
}
By having 2 different grok filter applied, we can disregard the order of the logs coming in. The patterns specified basically do not care about what comes before or after the String test and rather just standalone match their respective patterns.
So, for these 2 strings:
test1=12 test2=23
test2=23 test1=12
You will get the correct output. Test:
artur#pandaadb:~/dev/logstash$ ./logstash-2.3.2/bin/logstash -f conf_grok_ordering/
Settings: Default pipeline workers: 8
Pipeline main started
test1=12 test2=23
{
"message" => "test1=12 test2=23",
"#version" => "1",
"#timestamp" => "2016-12-21T16:48:24.175Z",
"host" => "pandaadb",
"test1" => "12",
"test2" => "23"
}
test2=23 test1=12
{
"message" => "test2=23 test1=12",
"#version" => "1",
"#timestamp" => "2016-12-21T16:48:29.567Z",
"host" => "pandaadb",
"test1" => "12",
"test2" => "23"
}
Hope that helps
After parsing logs I am find there are some new lines at the end of the message
Sample message
ts:2016-04-26 05-02-16-018
CDT|ll:TRACE|tid:10000.140|scf:xxxxxxxxxxxxxxxxxxxxxxxxxxx.pc|mn:null|fn:xxxxxxxxxxxxxxxxxxxxxxxxxxx|ln:749|auid:xxxxxxxxxxxxxxxxxxxxxxxxxxx|eid:xxx.xxx.xxx.xxx-58261618-1-1461664935955-139|cid:900009865|ml:null|mid:-99|uip:xxx.xxx.xxx.xxx|hip:xxx.xxx.xxx.xxx|pli:null|msg:
xxxxxxxxxxxxxxxxxxxxxxxxxxx|pl: xxxxxxxxxxxxxxxxxxxxxxxxxxx
TAKE 1 xxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxx
I am using the regex pattern below as suggested below as answers
ts:(?(([0-9]+)-)+ ([0-9]+-)+ [A-Z]+)\|ll:%{WORD:ll}\|tid:%{NUMBER:tid}\|scf:%{DATA:scf}\|mn:%{WORD:mn}\|fn:%{WORD:fn}\|ln:%{WORD:ln}\|auid:%{WORD:auid}\|eid:%{DATA:eid}\|cid:%{WORD:cid}\|ml:%{WORD:ml}\|mid:%{NUMBER:mid}\|uip:%{DATA:uip}\|hip:%{DATA:hip}\|pli:%{WORD:pli}\|\smsg:%{GREEDYDATA:msg}(\|pl:(?(.|\r|\n)))
But unfortunately it is not working properly when the last part of the log is not present
ts:2016-04-26 05-02-16-018
CDT|ll:TRACE|tid:10000.140|scf:xxxxxxxxxxxxxxxxxxxxxxxxxxx.pc|mn:null|fn:xxxxxxxxxxxxxxxxxxxxxxxxxxx|ln:749|auid:xxxxxxxxxxxxxxxxxxxxxxxxxxx|eid:xxx.xxx.xxx.xxx-58261618-1-1461664935955-139|cid:900009865|ml:null|mid:-99|uip:xxx.xxx.xxx.xxx|hip:xxx.xxx.xxx.xxx
What should be the correct pattern?
-------------------Previous Question --------------------------------------
I am trying to parse log line such as this one.
ts:2016-04-26 05-02-16-018 CDT|ll:TRACE|tid:10000.140|scf:xxxxxxxxxxxxxxxxxxxxxxxxxxx.pc|mn:null|fn:xxxxxxxxxxxxxxxxxxxxxxxxxxx|ln:749|auid:xxxxxxxxxxxxxxxxxxxxxxxxxxx|eid:xxx.xxx.xxx.xxx-58261618-1-1461664935955-139|cid:900009865|ml:null|mid:-99|uip:xxx.xxx.xxx.xxx|hip:xxx.xxx.xxx.xxx|pli:null|msg: xxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxx
Below is my logstash filter
filter {
grok {
match => ["mesage", "ts:(?<date>(([0-9]+)-*)+ ([0-9]+-*)+ [A-Z]+)\|ll:%{WORD:ll}\|tid:%{WORD:tid}\|scf:%{WORD:scf}\|mn:%{WORD:mn}\|fn:%{WORD:fn}\|ln:%{WORD:ln}\|auid:%{WORD:auid}\|eid:%{WORD:eid}\|cid:%{WORD:cid}\|ml:%{WORD:ml}\|mid:%{WORD:mid}\|uip:%{WORD:uip}\|hip:%{WORD:hip}\|pli:%{WORD:pli}\|msg:%{WORD:msg}"]
}
date {
match => ["ts","yyyy-MM-dd HH-mm-ss-SSS ZZZ"]
target => "#timestamp"
}
}
I am getting "_grokparsefailure"
I have tested the configuration from #HAL, there was a few things to change:
In the grok filter mesage => message
In the date filter ts => date so the date parsing is on the right field
The CDT is a time zone name, it is captured by z in the date syntax.
So the right configuration would look like this :
filter{
grok {
match => ["message", "ts:(?<date>(([0-9]+)-*)+ ([0-9]+-*)+ [A-Z]+)\|ll:%{WORD:ll}\|tid:%{NUMBER:tid}\|scf:%{DATA:scf}\|mn:%{WORD:mn}\|fn:%{WORD:fn}\|ln:%{WORD:ln}\|auid:%{WORD:auid}\|eid:%{DATA:eid}\|cid:%{WORD:cid}\|ml:%{WORD:ml}\|mid:%{NUMBER:mid}\|uip:%{DATA:uip}\|hip:%{DATA:hip}\|pli:%{WORD:pli}\|\s*msg:%{GREEDYDATA:msg}"]
}
date {
match => ["date","yyyy-MM-dd HH-mm-ss-SSS z"]
target => "#timestamp"
}
}
Tried to parse your input via grokdebug with your expression but it failed to read out any fields. Managed to get it to work by changing the expression to:
ts:(?<date>(([0-9]+)-*)+ ([0-9]+-*)+ [A-Z]+)\|ll:%{WORD:ll}\|tid:%{NUMBER:tid}\|scf:%{DATA:scf}\|mn:%{WORD:mn}\|fn:%{WORD:fn}\|ln:%{WORD:ln}\|auid:%{WORD:auid}\|eid:%{DATA:eid}\|cid:%{WORD:cid}\|ml:%{WORD:ml}\|mid:%{NUMBER:mid}\|uip:%{DATA:uip}\|hip:%{DATA:hip}\|pli:%{WORD:pli}\|\s*msg:%{GREEDYDATA:msg}
I also think that you need to change the name of the column that logstash shall parse from mesage to message.
Also, the date parsing pattern should match the format of the date in the input. There is no timezone identity (ZZZ) in your input data (at least not in the example).
Something like this should work better (not tested though):
filter {
grok {
match => ["mesage", "ts:(?<date>(([0-9]+)-*)+ ([0-9]+-*)+ [A-Z]+)\|ll:%{WORD:ll}\|tid:%{NUMBER:tid}\|scf:%{DATA:scf}\|mn:%{WORD:mn}\|fn:%{WORD:fn}\|ln:%{WORD:ln}\|auid:%{WORD:auid}\|eid:%{DATA:eid}\|cid:%{WORD:cid}\|ml:%{WORD:ml}\|mid:%{NUMBER:mid}\|uip:%{DATA:uip}\|hip:%{DATA:hip}\|pli:%{WORD:pli}\|\s*msg:%{GREEDYDATA:msg}"]
}
date {
match => ["ts","yyyy-MM-dd HH-mm-ss-SSS"]
target => "#timestamp"
}
}
I am finding that logstash is not a fan of my filter. Would be nice to have a second set of eyes on it.
First - my log file - has the following entries with new lines for every volume.
/vol/vol0/ 298844160 6916836 291927324 2% /vol/vol0/
My config file looks as follows:
INPUT
file {
type => "testing"
path => "/opt/log_repo/ssh/netapp/*"
tags => "netapp"
start_position => "beginning"
sincedb_path => "/dev/null"
}
FILTER
if [type] == "testing" {
grok{
match => [ "#message", "{UNIXPATH:volume}%{SPACE}%{INT:total}%{SPACE}%{INT:used}%{SPACE}%{INT:avail}%{SPACE}%{PROG:cap}%{SPACE}%{UNIXPATH:vols}"]
}
}
OUTPUT
if [type] == "testing" {
elasticsearch {
action => "index"
hosts => ["http://localhost:9200"]
index => ["testing4-%{+YYYY.MM.dd}"]
}
}
When I run this it tells me it has a bad config file. If I change the filter to:
match => [ "#message", "{UNIXPATH:volume}" ]
It creates a new field called volume with the volume name. I am using the space component because the log is simply not consistent. Some volumes will have 4 spaces between the usable space and some will have more or less depending on the volume name and the size.
To get to this configuration i leveraged the following sites:
https://grokdebug.herokuapp.com/discover?#
http://grokconstructor.appspot.com/do/constructionstep
Still struggling on what I am missing.... Any help would be greatly appreciated.
UPDATE: After adding the recommendation below it still doesn't create a new field.
_index string
message string
type string
tags string
path string
#timestamp date
#version string
host string
_source _source
_id string
_type string
_score
Your pattern doesn't matrch the sample log for a very simple and silly reason - you are missing % at the start of your pattern. If you will add it then it works like a charm:
So the full filter is:
if [type] == "testing" {
grok{
match => [ "#message", "%{UNIXPATH:volume}%{SPACE}%{INT:total}%{SPACE}%{INT:used}%{SPACE}%{INT:avail}%{SPACE}%{PROG:cap}%{SPACE}%{UNIXPATH:vols}"]
}
}
I've got log lines in the following format and want to extract fields:
[field1: content1] [field2: content2] [field3: content3] ...
I neither know the field names, nor the number of fields.
I tried it with backreferences and the sprintf format but got no results:
match => [ "message", "(?:\[(\w+): %{DATA:\k<-1>}\])+" ] # not working
match => [ "message", "(?:\[%{WORD:fieldname}: %{DATA:%{fieldname}}\])+" ] # not working
This seems to work for only one field but not more:
match => [ "message", "(?:\[%{WORD:field}: %{DATA:content}\] ?)+" ]
add_field => { "%{field}" => "%{content}" }
The kv filter is also not appropriate because the content of the fields may contain whitespaces.
Is there any plugin / strategy to fix this problem?
Logstash Ruby Plugin can help you. :)
Here is the configuration:
input {
stdin {}
}
filter {
ruby {
code => "
fieldArray = event['message'].split('] [')
for field in fieldArray
field = field.delete '['
field = field.delete ']'
result = field.split(': ')
event[result[0]] = result[1]
end
"
}
}
output {
stdout {
codec => rubydebug
}
}
With your logs:
[field1: content1] [field2: content2] [field3: content3]
This is the output:
{
"message" => "[field1: content1] [field2: content2] [field3: content3]",
"#version" => "1",
"#timestamp" => "2014-07-07T08:49:28.543Z",
"host" => "abc",
"field1" => "content1",
"field2" => "content2",
"field3" => "content3"
}
I have try with 4 fields, it also works.
Please note that the event in the ruby code is logstash event. You can use it to get all your event field such as message, #timestamp etc.
Enjoy it!!!
I found another way using regex:
ruby {
code => "
fields = event['message'].scan(/(?<=\[)\w+: .*?(?=\](?: |$))/)
for field in fields
field = field.split(': ')
event[field[0]] = field[1]
end
"
}
I know that this is an old post, but I just came across it today, so I thought I'd offer an alternate method. Please note that, as a rule, I would almost always use a ruby filter, as suggested in either of the two previous answers. However, I thought I would offer this as an alternative.
If there is a fixed number of fields or a maximum number of fields (i.e., there may be fewer than three fields, but there will never be more than three fields), this can be done with a combination of grok and mutate filters, as well.
# Test message is: `[fieldname: value]`
# Store values in [#metadata] so we don't have to explicitly delete them.
grok {
match => {
"[message]" => [
"\[%{DATA:[#metadata][_field_name_01]}:\s+%{DATA:[#metadata][_field_value_01]}\]( \[%{DATA:[#metadata][_field_name_02]}:\s+%{DATA:[#metadata][_field_value_02]}\])?( \[%{DATA:[#metadata][_field_name_03]}:\s+%{DATA:[#metadata][_field_value_03]}\])?"
]
}
}
# Rename the fieldname, value combinations. I.e., if the following data is in the message:
#
# [foo: bar]
#
# It will be saved in the elasticsearch output as:
#
# {"foo":"bar"}
#
mutate {
rename => {
"[#metadata][_field_value_01]" => "[%{[#metadata][_field_name_01]}]"
"[#metadata][_field_value_02]" => "[%{[#metadata][_field_name_02]}]"
"[#metadata][_field_value_03]" => "[%{[#metadata][_field_name_03]}]"
}
tag_on_failure => []
}
For those who may not be as familiar with regex, the captures in ()? are optional regex matches, meaning that if there is no match, the expression won't fail. The tag_on_failure => [] option in the mutate filter ensures that no error will be appended to tags if one of the renames fails because there was no data to capture and, as a result, there is no field to rename.