I wonder if there is a way of using a substring when using add_field in mutate filter, maybe with %{field} syntax.
For example:
filter {
mutate {
add_field => { "shorter_field" => "%{field[0:4]}" }
}
}
I saw solutions using ruby filters, but I prefer only using mutate because I have a sequence of operation I'm doing using the filter and I prefer keeping it simple
Try this:
(assuming that you need first 4 characters of the field.)
CODE:
filter {
mutate {
gsub => ["shorter_field", "(?<=^....)(.*)", ""]
}
}
In here all characters except first 4 characters will be removed from shorter_field.
example:
INPUT:
shorter_field = example_value
OUTPUT:
shorter_field = exam
Related
I was wondering what will be the best way to implement the following task in logstash :
I have the following field that contains multiple paths divided by ':' :
my_field : "/var/log/my_custom_file.txt:/var/log/otherfile.log/:/root/aaa.jar
I want to add a new field called "first_file" that will contain only the file_name(without suffix) of the first path :
first_file : my_custom_file
I implemented it with the following ruby code ;
code => 'event.set("first_file",event.get("[my_field]").split(":")[0].split("/")[-1].split(".")[0])'
How can I use logstash filters (add_field,split,grok) to do the same task ? I feel like using ruby code should be my last option.
You could do it using just grok, but I think it would be clearer to use mutate to pull out the first value
mutate { split => { "my_field" => ":" } }
mutate { replace => "{ "my_field" => "[my_field][0]" } }
grok { match => { "my_field" => "/(?<my_field>[^/]+)\.%{WORD}$" } overwrite => [ "my_field" ] }
rather than
grok { match => { "my_field" => "/(?<my_field>[^/]+)\.%{WORD}:" } overwrite => [ "my_field" ] }
The (?<my_field>[^/]+) is a custom pattern (documented here) which creates a field called [my_field] from a sequence of one or more (+) characters which are not /
Yes with a basic grok you could match every field in the value.
This kind of filter must work (put it in your logstash configuration file), this one extract the "basename" of the file (filename without extension and path) :
filter{
grok {
match => { "my_field" => "%{GREEDYDATA}/%{WORD:filename}.%{WORD}:%{GREEDYDATA}/%{WORD:filename2}.%{WORD}:%{GREEDYDATA}/%{WORD:filename3}.%{WORD}" }
}
}
You could be more strict in grok with use of PATH in place of GREYDATA, I let you determine your best approach that works in your context.
You could debug the grok pattern with the online tool grokdebug.
I am trying to adjust path name so that it no longer has the time stamp attached to the end. I am input many different logs so it would be impractical to write a conditional filter for every possible log. If possible I would just like to trim the last nine characters of the value.
For example "random.log-20140827" would become "random.log".
mutate {
gsub => [
"path", "-\d{8}$", ""
]
}
So if you know it's always going to be random.log-something --
if [path] =~ /random.log/ {
mutate {
replace => ["path", "random.log"]
}
}
If you want to "fix" anything that has a date in it:
if [path] =~ /-\d\d\d\d\d\d\d\d/ {
grok {
match => [ "path", "^(?<pathPrefix>[^-]+)-" ]
}
mutate {
replace => ["path", "%{pathPrefix}"]
remove_field => "pathPrefix"
}
}
Of the two, the first is going to be less compute intensive.
I haven't tested either of these, but they should work.
I am using Logstash and one of my applications is sending me fields like:
[message][UrlVisited]
[message][TotalDuration]
[message][AccountsProcessed]
I'd like to be able to collapse these fields, removing the top level message altogether. So the above fields will become:
[UrlVisited]
[TotalDuration]
[AccountsProcessed]
Is there a way to do this in Logstash?
Assuming the names of all such subfields are known in advance you can use the mutate filter:
filter {
mutate {
rename => ["[message][UrlVisited]", "UrlVisited"]
}
mutate {
rename => ["[message][TotalDuration]", "TotalDuration"]
}
mutate {
rename => ["[message][AccountsProcessed]", "AccountsProcessed"]
}
mutate {
remove_field => ["message"]
}
}
Alternatively, use a ruby filter (which works even if you don't know the field names):
filter {
ruby {
code => "
event.get('message').each {|k, v|
event.set(k, v)
}
event.remove('message')
"
}
}
This example works on Logstash 2.4 and later. For earlier versions use event['message'].each ... and event[k] = v instead.
After changing my mapping in ElasticSearch to more definitively type the data I am inputting into the system, I have unwittingly made my new variables a nested object. Upon thinking about it more, I actually like the idea of those fields being nested objects because that way I can explicitly know if that src_port statistic is from netflow or from the ASA logs, as an example.
I'd like to use a mutate (gsub, perhaps?) to cause all of my fieldnames for a given type to be renamed to newtype.fieldname. I see that there is gsub which uses a regexp, and rename which takes the literal field name, but I would like to prevent having 30 distinct gsub/rename statements when I will be replacing all of the fields in that type with the "newtype" prefix.
Is there a way to do this?
Here is an example for your reference.
input {
stdin{
type => 'netflow'
}
}
filter {
mutate {
add_field => {"%{type}.message" => "%{message}"}
remove_field => ["message"]
}
}
output {
stdout{
codec => rubydebug
}
}
In this example I have change the message field name to type.message, then delete the origin message field. I think you can use this sample to do what you want.
Hope this can help you.
I have updated my answer!
Use the ruby plugin to do what you want!
Please notice that elasticsearch uses #timestamp field to do index, so I recommend do not change the field name.
input {
stdin{
type => 'netflow'
}
}
filter {
ruby {
code => "
data = event.clone.to_hash;
type = event['type']
data.each do |k,v|
if k != '#timestamp'
newFieldName = type +'.'+ k
event[newFieldName] = v
event.remove(k)
end
end
"
}
}
output {
stdout{
codec => rubydebug
}
}
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.