I am trying to fetch data using elastic search with java using method
.addAggregation(terms(term))
The JSON response that I am expecting is
{
"key" : "TEST"
}
but I am getting the response as
{
"key" : "test"
}
which is in lower case, I want the response to be as it is stored. Please help here
The reason is that key is being analyzed e.g. lower-cased.
What you could do is have a "searchable" field that is being tokenized, but aggregate on a display field that preserves the casing. Or if you only want to aggregate (or if your search is case-sensitive and it seems for a field like key tokenization is also not desired) use the keyword type (https://www.elastic.co/guide/en/elasticsearch/reference/current/keyword.html)
Related
recently I made a change to the way ids were being generated in my ES index. Previously, we were generating the ids in the code, using a format like: uuid_WEEKDAY_COUNTRY_TIMESTAMP
I removed this and instead let the value of this field be auto-generated by ES (as i guess it should be)
How can i write a query that checks none of the old-format ids are still being generated? I tried something like
GET /_search
{
"query": {
"query_string": {
"query": "*WEDNESDAY*",
"default_field": "_id"
}
}
}
But got errors saying i can't query _id field, only text or keyword
how can i do this otherwise?
thanks
The _id field is special field handled in elastic search as the ID of the document. It is not indexed field like other text fields, though we can set the value , for documents where we do not specify this field it is actually "generated" based on the UID of the document (see: https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-id-field.html 2.8k).
The drop side of this is that , this field only supports a limited subset of the query functionality. One way to get over this is to add a field called id_field (as a text / keyword) into the document itself and then term queries on this field
I'm confused on what index type I should apply for my field for prefix search, many show search_as_you_type but I think auto complete is not what I'm going for.
I have a UUID field:
id: 34y72ca1-3739-41ff-bbec-f6d17479384c
The following terms should return the doc above:
3
34
34y72ca1
34y72ca1-3739
34y72ca1-3739-41ff-bbec-f6d17479384c
Using 3739 should not return it as it doesn't start with 3739. Initially this is what I was going for but then the wildcard field is not supported by Amazon AWS, so I compromise for prefix search instead of partial search.
I tried search_as_you_type field but it doesn't return the result when I use the whole ID. Actually, my use case is when user click enter, the results will be shown, instead of real-live when they type, so if speed is compromised its OK, just that I hope for something that will be good for many rows of data.
Thanks
If you have not explicitly defined any index mapping, then you need to use id.keyword field instead of the id field for the prefix query to show the appropriate results. This uses the keyword analyzer instead of the standard analyzer
{
"query": {
"prefix": {
"id.keyword": {
"value": "34y72ca1"
}
}
}
}
Otherwise, you can modify your index mapping, by adding multi fields for id field
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 am new to elastic search. I have got following document where one of the field "eventId" has "-" in value.
When i try to search with complete value of eventId, i don't get any results.
Sample Document app/event
{
"tags": {}
"eventId": "cc98d57b-c6bc-424c-b54c-df1e3df0d942",
}
I haven't created any explicit settings for my index.
Thanks.
you should check if the tokenizer splits your value into multiple fields. Maybe your value is stored as 5 fields: "cc98d57b", "c6bc", "424c", "b54c" and "df1e3df0d942"
You can analyze that with the 'Kopf' Plugin (https://github.com/lmenezes/elasticsearch-kopf).
If that is your problem you should change your field mapping, so that the value is not analyzed ("index" : "not_analyzed").
For an example how to set that mapping see here: Elasticsearch mapping settings 'not_analyzed' and grouping by field in Java
After that, you should be able to search for your specific value.
I am trying to do sorting by "timestamp" field (which is not a "_timestamp" default).
"timestamp" field stores micro-unixtime in
"_source": {
...
"timestamp": "1381256450000"
...
}
On screenshot you can see this value in 'sort' (right side). Last record should be definitely on the top of the result. But it isn't.
Screenshot:
From elasticsearch website :
By default, the search request will fail if there is no mapping associated with a field. The ignore_unmapped option allows to ignore fields that have no mapping and not sort by them.
You have to map the field if you want to use it to sort the results.