Can we use a Unix Timestamp as _timestamp field in elasticsearch - elasticsearch

When we create time-based indices, elasticsearch/kibana need a field named "_timestamp".
I found that this field should be a string.
But in my log, Unix Timestamp is a necessary segment.

Yes you can store unix timestamp in Date type fields. But make sure you use proper format like epoch_millis for timestamp in millis and epoch_second for timestamp in seconds.
Example mapping for timestamp field which stores unix timestamp in seconds.
PUT my-index
{
"mappings": {
"my-type": {
"properties": {
"timestamp": {
"type": "date",
"format": "epoch_second"
}
}
}
}
}
You can find more information here

Related

keeping [Europe/Berlin] (or other timezones in this fomat) while indexing Elasticsearch

I'm trying to familiarize myself with the Elasticsearch, specifically defining the mapping within a json file and creating a new index with it (with the help of the new Java API Client and Spring boot).
This is what my json file looks like:
{
"mappings": {
"properties": {
"Id": {
"type": "text"
},
"timestamp": {
"type": "date",
"format": "date_optional_time"
},
"metadata":{
"type": "nested"
},
"attributes": {
"type": "nested"
}
}
}
}
this can index my documents just fine, but I realized that if I use ZonedDateTime.now() for the data in my timestamp field, it fails to index due to the [Europe/Berlin] at the end. It works if I change it to
ZonedDateTime now = ZonedDateTime.now();
String date = now.format(DateTimeFormatter.ISO_OFFSET_DATE_TIME);
which gives me the time but without [Europe/Berlin]! As far as I understand from my various googling and "stackoverflow-ing", ES does not take [Timezone] in its date types, only the +2:00 format. But is it possible to keep it? (Maybe through an ingest pipeline?)
There are various documents that I would like to reindex that has [Timezone] hanging at the end of it, but these older documents saved it as text.... I would like to be able to do date math with the timestamp field in the future, which is why I decided to try and create a new/better mapping with proper fields. Any pointers appreciated!

any elasticsearch datatype matching decimal timestamp?

I have a timestamp from log file like {"ts" : "1486418325.948487"}
My infrastructure are "filebeat" 5.2.0 --> "elasticsearch" 5.2
I tried mapping the "ts" to "date" -- "epoch_second" but es writing failed in filebeat.
PUT /auth_auditlog
{
"mappings": {
"auth-auditlogs": {
"properties": {
"ts": {
"type": "date",
"format": "epoch_second"
}
}
}
}
}
The filebeat error msg like
WARN Can not index event (status=400): {"type":"mapper_parsing_exception","reason":"failed to parse [ts]","caused_by":{"type":"illegal_argument_exception","reason":"Invalid format: \"1486418325.948487\""}}
I tried use "1486418325" is ok so I guess es doesn't accept decimal format timestamp. However, python default output timestamp is this format.
My purpose is to type correctly in elasticsearch. I want to use ts as a original timestamp in elasticsearch.
Any solution is welcome except to change the original log data!
Filebeat doesn't have a processor for this type of stuff. You can't replace the #timestamp with the one your log has in Filebeat. What you can do, is send that stuff to logstash and let the date filter parse epoch.
date {
match => ["timestamp","UNIX","UNIX_MS"]
}
The other option would be to use a ingest node. Although I haven't used this myself, it seems it is also able to do the job. Check out the docs here.

ElasticSearch Mapping: is it possible to auto-truncate a date to fit it's format?

On our project we're using NEST to insert data into ElasticSearch (1.7). We'd like to be able to force ES to truncate all dates towards the mapped format.
Mapping example:
"dateFrom" : {
"type": "date",
"format": "dateHourMinute" // Or yyyy-MM-dd'T'HH:mm
}
Data example:
{
"dateFrom" : 2015-12-21T15:55:00.000Z
}
Inserting this data throws an IllegalArgumentException:
Invalid format: "2015-12-21T15:55:00.000Z" is malformed at ":00.000Z"
Obviously we don't need the last part of the date. Can't we configure ES to just truncate it instead of erroring out?
Keep in mind we're using 1.7 right now, since date formatting seems to have changed in recent versions...
In order to get the data to index correctly I could change the data type to date_optional_time (supported in 1.7)
PUT my_index
{
"mappings": {
"my_type": {
"properties": {
"date": {
"type": "date",
"format": "date_optional_time"
}
}
}
}
}
This will allow you to contribute date with time being optional.
such as:
PUT /my_index/my_type/1
{
"date": "2015-12-21"
}
or as you have it
PUT /my_index/my_type/2
{
"date": "2015-12-21T15:55:00.000Z"
}
Both are now valid submissions. I don't know of any transformation approaches within ES to support a truncation or transformation of field data at time of index. I would think if you want to parse the data and remove the time pre-submission you will need to do that outside of ES when you create the JSON object.
It appears ES is currently not capable of editing dates through a custom mapping. We ended up using JsonConverters (like this) to drop seconds and millis before inserting them into ES.

how do you transform a date that's storred as a type long (epoch time) into a dateOptionalTime in Elasticsearch?

I have a field in my database that's stored as Epoch time, which is a long. I'm trying to get Elasticsearch to recognize this field as what it actually is: a date. Once indexed by Elasticsearch, I want it to be of type dateOptionalTime.
My thinking is that I need to apply a transform to convert the Epoch long into a string date.
On my index, I have a mapping that specifies the type for my field as date with a format of dateOptionalTime. Finally, this timestamp is in all of my docs, so I've added my (attempted) mapping to _default_.
The code:
'_default_', {
'_all': {'enabled': 'true'},
'dynamic_templates': [
{ "date_fixer" : {
"match": "my_timestamp",
"mapping": {
"transform": {
"script": "ctx._source['my_timestamp'] = new Date(ctx._source['my_timestamp']).toString()"
},
'type': "date",
}
}
}]
}
I'm brand new to Elastic, so I'll walk through what I think is happening.
I'm setting this to type _default_ which will apply this to all new types Elastic encounters.
I set _all to enabled. I want Elastic to use the default mapping for all types with the exception of my timestamp field.
finally, I add my dynamic template that (a) converts the long into a date, and (b) applies a mapping to the timestamp field explicitly saying that it is a date
The Problem:
When I try to add my data to the index, I get the following exception.
TransportError(400, u'MapperParsingException[failed to parse [my_timestamp]]; nested: ElasticsearchIllegalArgumentException[unknown property [$date]]; ')
My data looks like:
{
"timestamp": 8374747594,
"owner": "text",
"some_more": {
"key": "val",
"key": "val"
}
}

Elasticsearch change field date format

When i created my index and type a while ago I specified the date format of a field in the mapping as:
{"type": "date","format" : "dd/MM/yyyy HH:mm:ss"}
Is there a way to change the format of the field knowing that now i have more than 6000 docs indexed in my index ? I want the format to be:
{"type": "date","format" : "dd-MM-yyyy HH:mm:ss"}
You can update format mapping on an existing date field with the PUT mapping API:
PUT twitter/_mapping/user
{
"properties": {
"myDate": {
"format": "dd-MM-yyyy HH:mm:ss"
}
}
}
format is one of the few mappings that can be updated on existing fields without losing data
https://www.elastic.co/guide/en/elasticsearch/reference/2.0/mapping-date-format.html
You cannot change field mappings after you have indexed documents into Elasticsearch. You can add new fields but you cannot change existing fields.
You could create a new index with the new mappings and then re-index all the data into it. You could then delete the old index and create a new index alias with the old name point to the new index.
There are a few strategies documented for minimizing downtime when changing mappings in the Elasticsearch blog: https://www.elastic.co/blog/changing-mapping-with-zero-downtime
Overall I'd highly suggest using index aliases - they provide a high level of abstraction and flexibility over using index names directly within your application. Perfect for situations like this where you want to make a change to the underlying index: http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/indices-aliases.html
For elastic version <7.0 where mapping type is not deprecated
you can use something like this
PUT inf/_mapping/_doc
{
"properties": {
"ChargeDate": {
"type":"date",
"format": "dd-MM-yyyy HH:mm:ss"
}
}
}
where inf is your index and _doc is mapping type(which is deprecated in v >7.0)
or
PUT inf
{
"mappings": {
"_doc": {
"properties": {
"ChargeDate": {
"type":"date",
"format": "dd-MM-yyyy HH:mm:ss"
}
}
}
}
}

Resources