I'm trying to create a scripted field in Kibana, which checks whether the field "Direction" is "I" or not.
if (doc['Direction'].value != "I") {return 1;} else {return 0;}
But for some reason, it won't work. With all other fields, that aren't explicitly mentioned in the index mapping it works that way, but I had to mention Direction in the mapping because I also have an alias pointing to it. For Direction I put the following in the mapping file:
"Direction": {
"type": "keyword"
}
And there is also an alias pointing to Direction:
"ISDN_Direction": {
"path": "Direction",
"type": "alias"
}
but both fields can't be used in the painless script. I don't get an error, but the result preview, for the first 10 results, is just empty.
Can someone help me with this issue?
I found the problem!
I changed the data type mapping, but I still had indices in my ES DB that had an old mapping on "text". Kibana didn't show me a mapping conflict, since both, text and keywords, are strings.
I deleted the old indices which mapped the field to "text" and now the painless calculation works without any problem :slight_smile:
Related
I am a beginner in Elasticsearch. I recently added a new field jc_job_meta_field which is of keyword type (see image 1 below as I output the mapping of all my fields) and my index is en-gb. I expect it to be an array to hold a bunch of values. And I now have a document with ["Virtual", "Hybrid"] in that field. I wanted to have the ability to search all entries with Virtual in the field jc_job_meta_field. But now when I do a term query search like this
{
"query": {
"terms": {
"jc_job_meta_field": ["Virtual"]
}
}
}
Nothing returned (see image 2 below). Shouldn't it at least return that exact document with [Virtual, Hybrid]? I checked a similar post here and it seems like I am doing exactly what's supposed to work. What went wrong here? Thanks in advance!
My Mapping and field values:
My query:
I am trying to use the metricbeat http module to monitor F5 pools.
I make a request to the f5 api and bring back json, which is saved to kibana. But the json contains an array of pool members and I want to count the number which are up.
The advice seems to be that this can be done with a scripted field. However, I can't get the script to retrieve the array. eg
doc['http.f5pools.items.monitor'].value.length()
returns in the preview results with the same 'Additional Field' added for comparison:
[
{
"_id": "rT7wdGsBXQSGm_pQoH6Y",
"http": {
"f5pools": {
"items": [
{
"monitor": "default"
},
{
"monitor": "default"
}
]
}
},
"pool.MemberCount": [
7
]
},
If I try
doc['http.f5pools.items']
Or similar I just get an error:
"reason": "No field found for [http.f5pools.items] in mapping with types []"
Googling suggests that the doc construct does not contain arrays?
Is it possible to make a scripted field which can access the set of values? ie is my code or the way I'm indexing the data wrong.
If not is there an alternative approach within metricbeats? I don't want to have to make a whole new api to do the calculation and add a separate field
-- update.
Weirdly it seems that the number values in the array do return the expected results. ie.
doc['http.f5pools.items.ratio']
returns
{
"_id": "BT6WdWsBXQSGm_pQBbCa",
"pool.MemberCount": [
1,
1
]
},
-- update 2
Ok, so if the strings in the field have different values then you get all the values. if they are the same you just get one. wtf?
I'm adding another answer instead of deleting my previous one which is not the actual question but still may be helpful for someone else in future.
I found a hint in the same documentation:
Doc values are a columnar field value store
Upon googling this further I found this Doc Value Intro which says that the doc values are essentially "uninverted index" useful for operations like sorting; my hypotheses is while sorting you essentially dont want same values repeated and hence the data structure they use removes those duplicates. That still did not answer as to why it works different for string than number. Numbers are preserved but strings are filters into unique.
This “uninverted” structure is often called a “column-store” in other
systems. Essentially, it stores all the values for a single field
together in a single column of data, which makes it very efficient for
operations like sorting.
In Elasticsearch, this column-store is known as doc values, and is
enabled by default. Doc values are created at index-time: when a field
is indexed, Elasticsearch adds the tokens to the inverted index for
search. But it also extracts the terms and adds them to the columnar
doc values.
Some more deep-dive into doc values revealed it a compression technique which actually de-deuplicates the values for efficient and memory-friendly operations.
Here's a NOTE given on the link above which answers the question:
You may be thinking "Well that’s great for numbers, but what about
strings?" Strings are encoded similarly, with the help of an ordinal
table. The strings are de-duplicated and sorted into a table, assigned
an ID, and then those ID’s are used as numeric doc values. Which means
strings enjoy many of the same compression benefits that numerics do.
The ordinal table itself has some compression tricks, such as using
fixed, variable or prefix-encoded strings.
Also, if you dont want this behavior then you can disable doc-values
OK, solved it.
https://discuss.elastic.co/t/problem-looping-through-array-in-each-doc-with-painless/90648
So as I discovered arrays are prefiltered to only return distinct values (except in the case of ints apparently?)
The solution is to use params._source instead of doc[]
The answer for why doc doesnt work
Quoting below:
Doc values are a columnar field value store, enabled by default on all
fields except for analyzed text fields.
Doc-values can only return "simple" field values like numbers, dates,
geo- points, terms, etc, or arrays of these values if the field is
multi-valued. It cannot return JSON objects
Also, important to add a null check as mentioned below:
Missing fields
The doc['field'] will throw an error if field is
missing from the mappings. In painless, a check can first be done with
doc.containsKey('field')* to guard accessing the doc map.
Unfortunately, there is no way to check for the existence of the field
in mappings in an expression script.
Also, here is why _source works
Quoting below:
The document _source, which is really just a special stored field, can
be accessed using the _source.field_name syntax. The _source is loaded
as a map-of-maps, so properties within object fields can be accessed
as, for example, _source.name.first.
.
Responding to your comment with an example:
The kyeword here is: It cannot return JSON objects. The field doc['http.f5pools.items'] is a JSON object
Try running below and see the mapping it creates:
PUT t5/doc/2
{
"items": [
{
"monitor": "default"
},
{
"monitor": "default"
}
]
}
GET t5/_mapping
{
"t5" : {
"mappings" : {
"doc" : {
"properties" : {
"items" : {
"properties" : {
"monitor" : { <-- monitor is a property of items property(Object)
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
}
}
}
}
}
I'm facing a problem in ElasticSearch 6.1 that I cannot solve and I don't know why. I have read the docs several times and maybe I'm missing something.
I have a scripted query that needs to do some calculation before decides if a record is available or not.
Here is the following script:
https://gist.github.com/dunice/a3a8a431140ec004fdc6969f77356fdf
What I'm doing is trying to loop though an array field with the following source:
"unavailability": [
{
"starts_at": "2018-11-27T18:00:00+00:00",
"local_ends_at": "2018-11-27T15:04:00",
"local_starts_at": "2018-11-27T13:00:00",
"ends_at": "2018-11-27T20:04:00+00:00"
},
{
"starts_at": "2018-12-04T18:00:00+00:00",
"local_ends_at": "2018-12-04T15:04:00",
"local_starts_at": "2018-12-04T13:00:00",
"ends_at": "2018-12-04T20:04:00+00:00"
},
]
When the script is executed it throws the error: No field found for [unavailability] in mapping with types [aircraft]
Is there any clue to make it work?
Thanks
UPDATE
Query:
https://gist.github.com/dunice/3ccd7d83ca6ddaa63c11013b84e659aa
UPDATE 2
Mapping:
https://gist.github.com/dunice/f8caee114bbd917115a21b8b9175a439
Data example:
https://gist.github.com/dunice/8ad0602bc282b4ca19bce8ae849117ad
You cannot access an array present in the source document via doc_values (i.e. doc). You need to directly access the source document via the _source variable instead, like this:
for(int i = 0; i < params._source['unavailability'].length; i++) {
Note that depending on your ES version, you might want to try ctx._source or just _source instead of params._source
I solve my use-case in a different approach.
Instead having a field as array of object like unavailability was I decided to create two fields as array of datetime:
unavailable_from
unavailable_to
My script walks through the first field then checks the second with the same position.
UPDATE
The direct access to _source is disabled by default:
https://github.com/elastic/elasticsearch/issues/17558
I'm parsing log files which for simplicity's sake let's say will have the following format :
{"message": "hello world", "size": 100, "forward-to": 127.0.0.1}
I'm indexing these lines into an Elasticsearch index, where I've defined a custom mapping such that message, size, and forward-to are of type text, integer, and ip respectively. However, some log lines will look like this :
{"message": "hello world", "size": "-", "forward-to": ""}
This leads to parsing errors when Elasticsearch tries to index these documents. For technical reasons, it's very much untrivial for me to pre-process these documents and change "-" and "" to null. Is there anyway to define which values my mapping should treat as null ? Is there perhaps an analyzer I can write which works on any field type whatsoever that I can add to all entries in my mapping ?
Basically I'm looking for somewhat of the opposite of the null_value option. Instead of telling Elasticsearch what to turn a null_value into, I'd like to tell it what it should turn into a null_value. Also acceptable would be a way to tell Elasticsearch to simply ignore fields that look a certain way but still parse the other fields in the document.
So this one's easy apparently. Add the following to your mapping settings :
{
"settings": {
"index": {
"mapping": {
"ignore_malformed": "true"
}
}
}
}
This will still index the field (contrary to what I've understood from the documentation...) but it will be ignored during aggregations (so if you have 3 entries in an integer field that are "1", 3, and "hello world", an averaging aggregation will yield 2).
Keep in mind that because of the way the option was implemented (and I would say this is a bug) this still fails for and object that is entered as a concrete value and vice versa. If you'd like to get around that you can set the field's enabled value to false like this :
{
"mappings": {
"my_mapping_name": {
"properties": {
"my_unpredictable_field": {
"enabled": false
}
}
}
}
}
This comes at a price though, since this means the field won't be indexed, but the values entered will be still be stored so you can still accessing them by searching for that document through another field. This usually shouldn't be an issue as you likely won't be filtering documents based on the value of such an unpredictable field, but that depends on your specific case use. See here for the official discussion of this issue.
I'm pretty new to Kibana and just set up an instance to look at some ElasticSearch data.
I have one index in Elastic Search, which has a few fields including _timestamp. When I go to the 'Discover' tab and look at my documents, each have the _timestamp field but with a yellow warning next to the field saying "No cached mapping for this field". As a result, I can't seem to sort/filter by time.
When I try and create a new index pattern and click on "Index contains time-based events", the 'Time-field name' dropdown doesn't contain anything.
Is there something else I need to do to get Kibana to recognise the _timestamp field?
I'm using Kibana 4.0.
You'll need to take these quick steps first :
Go to Settings → Advanced.
Edit the metaFields and add "_timestamp". Hit save.
Now go back to Settings → Indices and _timestamp will be available in the drop-down list for "Time-field name".
In newer versions you are required to specify the date field before you send your data.
Your date field must be in a standard format such as miliseconds after Epoch (long number) or - just as suggested by MrE - in ISO8601.
See more info here: https://www.elastic.co/guide/en/elasticsearch/reference/current/date.html
Again, before you send your data to the index, you must specify the mapping for this field. In python:
import requests
mapping = '{"mappings": {"your_index": {"properties": {"your_timestamp_field": { "type": "date" }}}}}'
requests.put('http://yourserver/your_index', data=mapping)
...
send_data()
My es version is 2.2.0
You have to the right schema.
I follow the guide
Eg:
{
"memory": INT,
"geo.coordinates": "geo_point"
"#timestamp": "date"
}
If you have the #timestamp, you will see the
ps: if your schema doesn't have "date" field, do not check "Index
contains time-based events
The accepted answer is obsolete as of Kibana 2.0
you should use a simple date field in your data and set it explicitly using either a timestamp, or a date string in ISO 8601 format.
https://en.wikipedia.org/wiki/ISO_8601
you also need to set a mapping to date BEFORE you start sending data apparently.
curl -XPUT 'http://localhost:9200/myindex' -d '{
"mappings": {
"my_type": {
"properties": {
"date": {
"type": "date"
}
}
}
}
}'
Go to Settings->Indices, select your index, and click the yellow "refresh" icon. That will get rid of the warning, and perhaps make the field available in your visualization.