What is the most appropriate name for the timestamp when utilizing Logstash to parse logs into Elasticsearch, then visualizing with Kibana?
I am defining the timestamp using date in a filter:
date {
match => [ "logtime", "yy-MM-dd HH:mm:ss" ]
}
Logstash automatically puts this into the #timestamp field. Kibana can be configured to use any correctly formatted field as the timestamp, but it seems to be correct to use _timestamp in Elasticsearch. To do that, you have to mutate and rename the datestamp field.
mutate {
rename => { "#timestamp" => "_timestamp" }
}
Which is slightly annoying.
This question could be entirely semantic - but is it most correct to use _timestamp, or is it just fine to use #timestamp? Are there any other considerations which should influence the naming of the timestamp field?
Elasticsearch allows you to define fields starting with an underscore, however, Kibana (since v4) will only show the ones declared outside of the _source document.
You should definitely keep with #timestamp which is the standard way to name the timestamp field in Logstash. Kibana will not allow you to use _timestamp.
Please note that _timestamp is reserved and deprecated special field name. Actually any field names starting with underscore are reserved for elasticsearch future internal usage. AFAIK logstash documentation examples use #timestamp as field name
without any renaming.
Related
This is the naming convention of my log files which looks like this:
adminPortal-2021-10-10.0.log
adminPortal-2021-10-27.0.log
I need to publish them to different indices that match the log file date, but Elasticsearch publishes logs from all log files into one index.
output {
elasticsearch {
hosts => ["localhost:9200"]
index => "admin-%{+YYYY-MM-dd}"
}
}
A sprintf reference to a date, like %{+YYYY-MM-dd} always uses the value of the #timestamp field. If you want it to use the value from the log entry you will need to parse the timestamp out of the [message] field, possibly using grok, and then parse that using a date filter to overwrite the default value of the #timestamp field (which is Time.now).
I have a log file which has a date time in 'yyyyMMdd_HHmmss_SSS' format. I am successful in parsing this with _ as delimiter and getting as 3 different text field in ES. But I need this to be converted as ISO_8601 so I can query and visualize the data by date or by hour or by minute.
If you don't specifically need ISO-8601, but care more about the events getting a queryable timestamp, the date filter sounds like a better fit for you.
filter {
date {
match => [ "logdate", "yyyyMMdd_HHmmss_SSS" ]
}
}
This will set the #timestamp field to be a date-searchable field.
However, if you really do need Grok to do the work, you'll probably be best suited through using custom regexes.
(?<logyear>\d{4,})(?<logmonth>\d\d)(?<logday>\d\d)_(and so on)
This leverages single-digit captures to build your string.
I have a hostname field that's coming in via filebeat to my logstash instance is getting passed to ElasticSearch where it's being treated as an analyzed field. That's causing issues, because the field itself needs to be reported on in it's totality.
Example: Knowing how many requests come to "prd-awshst-x-01" rather than splitting those out into prd, awshst, x, 01.
Does anyone have a lightweight way of doing this that can be used with visualizations?
Thanks,
We have to update mapping from analyzed to not_analyzed for specific field.
PUT/ mapping url/
{
property:{
field:{
text:"not_analyzed"
}
}
}
After updating the property please check is it reflected in mapping using GET method on mapping url.
Based on the title of your post, you already know that you need to change the mapping of the field to not_analyzed.
You should setup a template so that future indexes contain this mapping.
If you want to keep the existing data, you'll have to reindex it into a new index with the new mapping.
If you're using the default logstash template, it might be creating you a not_analyzed ".raw" field that you can use in visualizations in kibana.
The index template that is provided with Filebeat configures the hostname field as not_analyzed.
You should manually install the index template provided with Filebeat and then configure Logstash to write data to the Filebeat index as described in the docs.
This is what the elasticsearch output would look like. If you are processing other data through Logstash, then you might want to add a conditional around this output so that only beat events are sent via this output.
output {
elasticsearch {
hosts => "localhost:9200"
manage_template => false
index => "%{[#metadata][beat]}-%{+YYYY.MM.dd}"
document_type => "%{[#metadata][type]}"
}
}
Our data model doesn't have version field separately. One of the ways we versioned the data model is by the id and the last updated timestamp, the version will be incremented when a new record with same id but latest last updated timestamp is received.
However in elastic search, there is no way to derive the value of _id field. Multi fields cannot applied to _id field.
Our system is reactive and message driven, so can't rely on the order in which we receive the message.
is there anyways we can solve versioning in a performant way?
The _version field in elasticsearch is not for versioning. It's to ensure you are working on the expected document (e.g. you read a doc and decide to delete it, than it would be wise to add the version-number of the read doc to the delete command).
You can set the _id field to "[your_id]_[timestamp]" and add two additional fields "my_id" and "timestamp".
How to set the _id to "[your_id]_[timestamp]"? If you use logstash than you can use the mutate filter:
mutate { add_field => ["id", "%{your_id}", "_", "%{timestamp}"] }
should work. If you don't use logstash, you have to create the id-field similar.
I have an issue similar to this Difference between #timestamp and timestamp field in elasticsearch. But I will need solution for it.
We use Kibana which by default use #timestamp as time filter. Yes, I can change it to whatever field manually EVERYTIME people create the time filter, but it is impossible for EVERYBODY in our big team to know it. So we need #timestamp.
#timestamp won't show up even I use the mapping here,
"_timestamp" : {
"enabled" : true,
"store" : true
}
So I workaround by adding a field name called #timestamp. I can use curl to add documents to it and The time filer start working.
However, when I move to use NEST api which cannot create #timestamp field. Even I define the field name as #timestamp, NEST api automatically change it to timestamp.
So Kibana time filter broken again.
Any suggestion?
Just figured it out. Nest API does have a way to explicitly set the field name.
[ElasticProperty(Name = "#timestamp", Type = FieldType.Date, DateFormat = "yyyy-MM-dd'T'HH:mm:ss", Store = true)]
So this is resolved.