I am currently working with Kibana and am running into a problem which i cant solve.
in my source file there is a rule which includes "", however when i run the script i made for kibana in dev tools it does not include that rule bur gives a error. how can i exclude those characters or how can it be included?
i have tried to exclude those characters using a g sub field but that doesn't work either.
"%{DATA:Datetime},%{DATA:Elapsed},%{DATA:label},%{DATA:ResponseCode},%{DATA:ResponseMessage},%{DATA:ThreadName},%{DATA:DataType},%{DATA:Success},%{DATA:FailureMessage},%{DATA:Bytes},%{DATA:SentBytes},%{DATA:GRPThreads},%{DATA:AllThreads},%{DATA:URL},%{DATA:Latency},%{DATA:IdleTime},%{GREEDYDATA:Connect}"
that is the grok pattern i'm using.
27-19-2018 12:19:43,8331,OK - Refresh Samenvatting,200,"Number of samples in transaction : 67, number of failing samples : 0",Thread Group 1-1,,true,,550720,137198,1,1,null,8318,5094,270
and this is the line i want to run trough it, it goes wrong at the "".
R. Kiers
Best to use custom patterns. Tested on Kibana 6.x and works for the sample data provided above. Can easily tweak to work with any sample data
custom patterns used:
UNTILNEXTCOMMA ([^,]*)
Grok pattern:
%{DATA:Datetime},%{NUMBER:Elapsed},%{UNTILNEXTCOMMA:label},%{NUMBER:Responsecode},"%{GREEDYDATA:ResponseMessage}",%{UNTILNEXTCOMMA:ThreadName},%{UNTILNEXTCOMMA:DataType},%{UNTILNEXTCOMMA:Success},%{UNTILNEXTCOMMA:FailureMessage},%{NUMBER:Bytes},%{NUMBER:SentBytes},%{NUMBER:GRPThreads},%{NUMBER:AllThreads},%{UNTILNEXTCOMMA:URL},%{NUMBER:Latency},%{NUMBER:IdleTime},%{NUMBER:Connect}
EDIT1:
Pipeline for Kibana 5.x
PUT _ingest/pipeline/test
{
"description": "Test pipeline",
"processors": [
{
"grok": {
"field": "message",
"patterns": [
"%{DATA:Datetime},%{DATA:Elapsed},%{DATA:label},%{DATA:ResponseCode},\"%{GREEDYDATA:ResponseMessage}\",%{DATA:ThreadName},%{DATA:DataType},%{DATA:Success},%{DATA:FailureMessage},%{DATA:Bytes},%{DATA:SentBytes},%{DATA:GRPThreads},%{DATA:AllThreads},%{DATA:URL},%{DATA:Latency},%{DATA:IdleTime},%{GREEDYDATA:Connect}"
],
"ignore_failure": false
}
}
]
}
Tested using simulate and it works
POST _ingest/pipeline/test/_simulate
{
"docs" : [
{ "_source": { "message" : "27-19-2018 12:19:43,8331,OK - Refresh Samenvatting,200,\"Number of samples in transaction : 67, number of failing samples : 0\",Thread Group 1-1,,true,,550720,137198,1,1,null,8318,5094,270"
} }
]
}
Related
I only want to run my pipeline on files where the log path contains a certain keyword, how do I do this within the pipeline?
Pipeline (removed my pattern and patterns as it is not relevant):
{
"description" : "...",
"processors": [
{
"grok": {
"if": "ctx['log']['file']['path'].value.contains('keyword')",
"field": "message",
}
}
]
}
In Kibana I see I have log.file.path available as metadata, and I just want to run the pipeline if it contains a keyword, but I get a runtime error because of my if statement.
Thanks for your help!
EDIT: I think the problem lies with how I am trying to access the log.file.path field as I don't know how to reference it correctly from here.
You can probably use the Drop processor
https://www.elastic.co/guide/en/elasticsearch/reference/current/drop-processor.html
"drop": {
"if": "ctx.log.file.path.contains('keyword');"
}
You can find more complexe exemples here:
https://www.elastic.co/guide/en/elasticsearch/reference/master/ingest-conditional-complex.html
I am having a query related to grok processor.
For example this is my message filed
{
"message":"agentId:agent003"
}
I want to Grok this and my output should me something like this
{
"message":"agentId:agent003",
"agentId":"agent003"
}
Could some one help me on this how to achieve this? If i am able to do it for one field i can manage for rest of my fields. Thanks in advance.
This is the pipeline i have created in elasticsearch
PUT _ingest/pipeline/dissectpipeline
{
"description" : "split message content",
"processors": [
{
"dissect": {
"field": "message",
"pattern" : "%{apm_application_message.agentId}:%{apm_application_message.agentId}"
}
}
]
}
Central management added filebeat module other config
- pipeline:
if: ctx.first_char == '{'
name: '{< IngestPipeline "dissectpipeline" >}'
There is no error with my filebeat it's working fine but i am unable to find any field like apm_application_message.agentId in index.
How to make sure my pipeline working or not. Also if i am doing something wrong please let me know.
Instead of grok I'd suggest using the dissect filter instead with, which is more intuitive and easier to use.
dissect {
mapping => {
"message" => "%{?agentId}:%{&agentId}"
}
}
If you're using Filebeat, there is also the possibility to use the dissect processor:
processors:
- dissect:
tokenizer: "%{?agentId}:%{&agentId}"
field: "message"
target_prefix: ""
I'm using Elasticsearch's Update by Query API to update some documents with a Painless script like this (the actual query is more complicated):
POST ts-scenarios/_update_by_query?routing=test
{
"query": {
"term": { "routing": { "value": "test" } }
},
"script": {
"source": """ctx._source.tagIDs = ["5T8QLHIBB_kDC9Ugho68"]"""
}
}
This works, except that upon reindexing, other fields get reordered, including some classes which are automatically (de)serialized using JSON.NET's type handling. That means a document with the following source before the update:
{
"routing" : "testsuite",
"activities" : [
{
"$type" : "Test.Models.SomeActivity, Test"
},
{
"$type" : "Test.Models.AnotherActivity, Test",
"CustomParameter" : 1,
"CustomSetting" : false
}
]
}
ends up as
{
"routing" : "testsuite",
"activities" : [
{
"$type" : "Test.Models.SomeActivity, Test"
},
{
"CustomParameter" : 1,
"CustomSetting" : false,
"$type" : "Test.Models.AnotherActivity, Test"
}
],
"tagIDs" : [
"5T8QLHIBB_kDC9Ugho68"
]
}
which JSON.NET can't deserialize. Is there a way I can tell the script (or the Update by Query API) not to change the order of those other fields?
In case it matters, I'm using Elasticsearch OSS version 7.6.1 on macOS. I haven't checked whether an Ingest pipeline would work here, as I'm not familiar with them.
(It turns out I can make the deserialization more flexible by setting the MetadataPropertyHandling property to ReadAhead, as mentioned here. That works, but as mentioned it may hurt performance and there might be other situations where field order matters. Technically, it shouldn't; JSON isn't XML, but there are always edge cases where it does matter.)
I have an OKD cluster setup with EFK stack for logging, as described here. I have never worked with one of the components before.
One deployment logs requests that contain a specific value that I'm interested in. I would like to extract just this value and visualize it with an area map in Kibana that shows the amount of requests and where they come from.
The content of the message field basically looks like this:
[fooServiceClient#doStuff] {"somekey":"somevalue", "multivalue-key": {"plz":"12345", "foo": "bar"}, "someotherkey":"someothervalue"}
This plz is a German zip code, which I would like to visualize as described.
My problem here is that I have no idea how to extract this value.
A nice first success would be if I could find it with a regexp, but Kibana doesn't seem to work the way I think it does. Following its docs, I expect this /\"plz\":\"[0-9]{5}\"/ to deliver me the result, but I get 0 hits (time interval is set correctly). Even if this regexp matches, I would only find the log entry where this is contained and not just the specifc value. How do I go on here?
I guess I also need an external geocoding service, but at which point would I include it? Or does Kibana itself know how to map zip codes to geometries?
A beginner-friendly step-by-step guide would be perfect, but I could settle for some hints that guide me there.
It would be possible to parse the message field as the document gets indexed into ES, using an ingest pipeline with grok processor.
First, create the ingest pipeline like this:
PUT _ingest/pipeline/parse-plz
{
"processors": [
{
"grok": {
"field": "message",
"patterns": [
"%{POSINT:plz}"
]
}
}
]
}
Then, when you index your data, you simply reference that pipeline:
PUT plz/_doc/1?pipeline=parse-plz
{
"message": """[fooServiceClient#doStuff] {"somekey":"somevalue", "multivalue-key": {"plz":"12345", "foo": "bar"}, "someotherkey":"someothervalue"}"""
}
And you will end up with a document like the one below, which now has a field called plz with the 12345 value in it:
{
"message": """[fooServiceClient#doStuff] {"somekey":"somevalue", "multivalue-key": {"plz":"12345", "foo": "bar"}, "someotherkey":"someothervalue"}""",
"plz": "12345"
}
When indexing your document from Fluentd, you can specify a pipeline to be used in the configuration. If you can't or don't want to modify your Fluentd configuration, you can also define a default pipeline for your index that will kick in every time a new document is indexed. Simply run this on your index and you won't need to specify ?pipeline=parse-plz when indexing documents:
PUT index/_settings
{
"index.default_pipeline": "parse-plz"
}
If you have several indexes, a better approach might be to define an index template instead, so that whenever a new index called project.foo-something is created, the settings are going to be applied:
PUT _template/project-indexes
{
"index_patterns": ["project.foo*"],
"settings": {
"index.default_pipeline": "parse-plz"
}
}
Now, in order to map that PLZ on a map, you'll first need to find a data set that provides you with geolocations for each PLZ.
You can then add a second processor in your pipeline in order to do the PLZ/ZIP to lat,lon mapping:
PUT _ingest/pipeline/parse-plz
{
"processors": [
{
"grok": {
"field": "message",
"patterns": [
"%{POSINT:plz}"
]
}
},
{
"script": {
"lang": "painless",
"source": "ctx.location = params[ctx.plz];",
"params": {
"12345": {"lat": 42.36, "lon": 7.33}
}
}
}
]
}
Ultimately, your document will look like this and you'll be able to leverage the location field in a Kibana visualization:
{
"message": """[fooServiceClient#doStuff] {"somekey":"somevalue", "multivalue-key": {"plz":"12345", "foo": "bar"}, "someotherkey":"someothervalue"}""",
"plz": "12345",
"location": {
"lat": 42.36,
"lon": 7.33
}
}
So to sum it all up, it all boils down to only two things:
Create an ingest pipeline to parse documents as they get indexed
Create an index template for all project* indexes whose settings include the pipeline created in step 1
I am using elastic 5.1.1 in my environment. I have chosen completion suggester on a field name post_hashtags with an array of strings to have suggestion on it. I am getting response as below for prefix "inv"
Req:
POST hashtag/_search?pretty&&filter_path=suggest.hash-suggest.options.text,suggest.hash-suggest.options._source
{"_source":["post_hashtags" ],
"suggest": {
"hash-suggest" : {
"prefix" : "inv",
"completion" : {
"field" : "post_hashtags"
}
}
}
Response :
{
"suggest": {
"hash-suggest": [
{
"options": [
{
"text": "invalid",
"_source": {
"post_hashtags": [
"invalid"
]
}
},
{
"text": "invalid",
"_source": {
"post_hashtags": [
"invalid",
"coment_me",
"daya"
]
}
}
]
}
]
}
Here "invalid" is returned twice because it is also a input string for same field "post_hashtags" in other document.
Problems is if same "invalid" input string present in 1000 documents in same index then i would get 1000 duplicated suggestions which is huge and not needed.
Can I apply an aggregation on a field of type completion ?
Is there any way I can get unique suggestion instead of duplicated text field, even though if i have same input string given to a particular field in multiple documents of same index ?
ElasticSearch 6.1 has introduced the skip_duplicates operator. Example usage:
{
"suggest": {
"autocomplete": {
"prefix": "MySearchTerm",
"completion": {
"field": "name",
"skip_duplicates": true
}
}
}
}
Edit: This answer only applies to Elasticsearch 5
No, you cannot de-duplicate suggestion results. The autocomplete suggester is document-oriented in Elasticsearch 5 and will thus return suggestions for all documents that match.
In Elasticsearch 1 and 2, the autocomplete suggester automatically de-duplicated suggestions. There is an open Github ticket to bring back this functionality, and it looks like it is possible to do so in a future version.
For now, you have two options:
Use Elasticsearch version 1 or 2.
Use a different suggestion implementation not based on the autocomplete suggester. The only semi-official suggestion I have seen so far involve putting your suggestion strings in a separate index.