I need to send application logs directly to logstash using: Logstash Logback Encoder from multiple microservices. Problem is that when I am sending logs logstash recive logs like this:
{
"_index": "logstash-2021.01.21-000001",
"_type": "_doc",
"_id": "id",
"_version": 1,
"_score": 1.6928859,
"_source": {
"#timestamp": "2021-01-21T14:13:05.480Z",
"#version": "1",
"message": "message",
"host": "gateway",
"port": 43892
},
"fields": {
"#timestamp": [
"2021-01-21T14:13:05.480Z"
]
},
"highlight": {
"message": [msg]
},
"sort": [ sort ]
}
I need to add a custom field in "fields" section or in general section. Do you have any idea how I can do this?
You can use mutate filter in your logstash configuration file.
For example, into logstash configuration your file, this looks like this :
filter {
mutate { add_field => { "field_name" => "field_value" } }
}
Related
I need to create an index in elasticsearch by assigning a default value for a field. Ex,
In python3,
request_body = {
"settings":{
"number_of_shards":1,
"number_of_replicas":1
},
"mappings":{
"properties":{
"name":{
"type":"keyword"
},
"school":{
"type":"keyword"
},
"pass":{
"type":"keyword"
}
}
}
}
from elasticsearch import Elasticsearch
es = Elasticsearch(['https://....'])
es.indices.create(index="test-index", ignore=400, body= request_body)
in above scenario, the index will be created with those fields. But i need to put a default value to "pass" as True. Can i do that here?
Elastic search is schema-less. It allows any number of fields and any content in fields without any logical constraints.
In a distributed system integrity checking can be expensive so checks like RDBMS are not available in elastic search.
Best way is to do validations at client side.
Another approach is to use ingest
Ingest pipelines let you perform common transformations on your data before indexing. For example, you can use pipelines to remove fields, extract values from text, and enrich your data.
**For testing**
POST _ingest/pipeline/_simulate
{
"pipeline": {
"processors": [
{
"script": {
"lang": "painless",
"source": "if (ctx.pass ===null) { ctx.pass='true' }"
}
}
]
},
"docs": [
{
"_index": "index",
"_type": "type",
"_id": "2",
"_source": {
"name": "a",
"school":"aa"
}
}
]
}
PUT _ingest/pipeline/default-value_pipeline
{
"description": "Set default value",
"processors": [
{
"script": {
"lang": "painless",
"source": "if (ctx.pass ===null) { ctx.pass='true' }"
}
}
]
}
**Indexing document**
POST my-index-000001/_doc?pipeline=default-value_pipeline
{
"name":"sss",
"school":"sss"
}
**Result**
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "hlQDGXoB5tcHqHDtaEQb",
"_score" : 1.0,
"_source" : {
"school" : "sss",
"pass" : "true",
"name" : "sss"
}
},
I'm using the official Elasticsearch NodeJS client library, to query the following index structure:
{
"_index": "articles",
"_type": "context",
"_id": "1",
"_version": 1,
"found": true,
"_source": {
"article": "this is a paragraph",
"topic": "topic A"
}
}
{
"_index": "articles",
"_type": "context",
"_id": "2",
"_version": 1,
"found": true,
"_source": {
"article": "this is a paragraph this is a paragraph this is a paragraph",
"topic": "topic B"
}
}
I would like to query my index using the term "this is a paragraph" and boost the result with the most similar text length, IE: document _id:1
Can I do this without re-indexing and adding a field to my index (as described here)?
The below query uses Groovy to look at the length of the actual text indexed into ES (using _source.article.length()) and at the length of the text to be searched. As a very simple basic query, I used match_phrase and then rescored the documents based on how long the text to search is compared to how long the original text is.
GET /articles/context/_search
{
"query": {
"function_score": {
"query": {
"match_phrase": {
"article": "this is a paragraph"
}
},
"functions": [
{
"script_score": {
"script": {
"inline": "text_to_search_length=text_to_search.length(); compared_length=_source.article.length();return (compared_length-text_to_search_length).abs()",
"params": {
"text_to_search": "this is a paragraph"
}
}
}
}
]
}
},
"sort": [
{
"_score": {
"order": "asc"
}
}
]
}
I would like to add logstash.log log into my ELK stack but I always have grokparsefailure.
My pattern is OK on http://grokconstructor.appspot.com/do/match#result
My logstash conf file (filter part) is
filter {
if [application] == "logstash" {
grok {
match => { "message" => "\{:timestamp=>\"%{TIMESTAMP_ISO8601:timestamp}\", :message=>%{GREEDYDATA:errormessage}\}" }
}
date {
match => [ "timestamp" , "yyyy-MM-dd'T'HH:mm:ss.SSSSSSZ" ]
}
}
}
But still In only get
{
"_index": "logstash-2016.05.03",
"_type": "logs",
"_id": "AVR3WUtpT8BPcJ-gVynN",
"_score": null,
"_source": {
"#version": "1",
"#timestamp": "2016-05-03T16:00:20.708Z",
"path": "/var/log/logstash/logstash.log",
"host": "xxx.arte.tv",
"application": "logstash",
"tags": [
"_grokparsefailure"
]
I guess I have issue with either { ou " but with or without backslashing theim, still grokparsefailure.
Shame on me, there is no error in my previous post, problem was no message because of a remove_field message in another conf file.
Sorry guys for the waste of time
I want to make exact matches ids in a doc field. I have mapped the fields to index them not_analyzed but it seems like in the query each term is tokenizde or at least lowercased. How do I make the query also not_analyzed? Using ES 1.4.4, 1.5.1, and 2.0.0
Here is a doc:
{
"_index": "index_1446662629384",
"_type": "docs",
"_id": "Cat-129700",
"_score": 1,
"_source": {
"similarids": [
"Cat-129695",
"Cat-129699",
"Cat-129696"
],
"id": "Cat-129700"
}
}
Here is a query:
{
"size": 10,
"query": {
"bool": {
"should": [{
"terms": {
"similarids": ["Cat-129695","Cat-129699","Cat-129696"]
}
}]
}
}
}
The query above does not work. If I remove caps and dashes from the doc ids it works. I can't do that for many reasons. Is there a way to make the similarids not_analyzed like the doc fields?
If I'm understanding you correctly, all you need to do is set "index":"not_analyzed" on the "similarids" in your mapping. If you have that setting correct already, then there is something else going on that isn't apparent from what you posted (the "terms" query doesn't do any analysis on your search terms). You may want to check your mapping to make sure it is set up the way you think.
To test it, I set up a simple index like this:
PUT /test_index
{
"settings": {
"number_of_shards": 1
},
"mappings": {
"doc": {
"properties": {
"id": {
"type": "string",
"index": "not_analyzed"
},
"similarids": {
"type": "string",
"index": "not_analyzed"
}
}
}
}
}
Then added your document:
PUT /test_index/doc/1
{
"similarids": [
"Cat-129695",
"Cat-129699",
"Cat-129696"
],
"id": "Cat-129700"
}
And your query works just fine.
POST /test_index/_search
{
"size": 10,
"query": {
"bool": {
"should": [
{
"terms": {
"similarids": [
"Cat-129695",
"Cat-129699",
"Cat-129696"
]
}
}
]
}
}
}
...
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 0.53148466,
"hits": [
{
"_index": "test_index",
"_type": "doc",
"_id": "1",
"_score": 0.53148466,
"_source": {
"similarids": [
"Cat-129695",
"Cat-129699",
"Cat-129696"
],
"id": "Cat-129700"
}
}
]
}
}
I used ES 2.0 here, but it shouldn't matter which version you use. Here is the code I used to test:
http://sense.qbox.io/gist/562ccda28dfaed2717b43739696b88ea861ad690
I am using Bunyan and bunyas-lumberjack to send my logs to log stash and index them in elastic search. The problem I am facing is when I am filtering the logs: I am using a basic filter for Logstash :
filter {
if [type == "json"]{
json {
source => "message"
}
}
}
that puts the JSON from bunyan into the source.message field and indexes it in elastic search. How can I index every field from bunyan into a particular elastic search field so I can search over it or use it in Kibana ?
I am attaching what I have obtained now and what I want to obtain as example.
Currently:
{
"_index": "logstash-2015.10.26",
"_type": "json",
"_id": "AVCjvDHWHiX5VLMgQZIC",
"_score": null,
"_source": {
"message": "{\"name\":\"myLog\",\"hostname\":\"atnm-4.local\",\"pid\":6210,\"level\":\"error\",\"message\":\"This should work!\",\"#timestamp\":\"2015-10-26T10:40:29.503Z\",\"tags\":[\"bunyan\"],\"source\":\"atnm-4.local/node\"}",
"#version": "1",
"#timestamp": "2015-10-26T10:40:31.184Z",
"type": "json",
"host": "atnm-4.local",
"bunyanLevel": "50"
},
Wanted:
{
"_index": "logstash-2015.10.26",
"_type": "json",
"_id": "AVCjvDHWHiX5VLMgQZIC",
"_score": null,
"_source": {
"message": {
"name": example,
"hostname": example,
"etc": example
Each input in logstash can have different codec and type. In your case, if you want to index bunyan and syslog, you'll have two inputs with two different types. The syslog will have codec "plain", the bunyan will have "json". You do not need any filter for the bunyan messages. The json will be parsed and the fields will appear automagically. You will have to have a filter to parse the syslog input.