Elasticsearch field name aliasing - elasticsearch

Is it possible to setup alias for field names in elasticsearch? (Just like how index names can be aliased)
For example: i have a document {'firstname': 'John', 'lastname': 'smith'}
I would like to alias 'firstname' to 'fn'...

Just a quick update, Elasticsearch 6.4 came up with feature called Alias Datatype. Check the below mapping and query as sample.
Note that the type of the field is alias in the below mapping for fieldname fn
Sample Mapping:
PUT myindex
{
"mappings": {
"_doc": {
"properties": {
"firstname": {
"type": "text"
},
"fn": {
"type": "alias",
"path": "firstname"
}
}
}
}
}
Sample Query:
GET myindex/_search
{
"query": {
"match" : {
"fn" : "Steve"
}
}
}
The idea is to use the alias for actual field on which inverted index is created. Note that fields with alias datatype aren't meant for write operations and its only meant for querying purpose.
Although you can refer to the link I've mentioned for more details, below are just some of the important points.
Field alias is only meant to be used when your index has a single mapping. Index has to be created post 6.xx version or be created in older version with the setting index.mapping.single_type: true
Can be used in querying, aggregations, sorting, highlighting and suggestion operations
Target field must be actual field on which inverted index is created
Cannot create alias of another alias field
Cannot use alias on multiple fields. Single alias, Single field.
Cannot be used as part of source filtering using _source.

There is no direct field alias functionality. However, you could rename the fields upon indexing using the index_name property in your mappings.
index_name : The name of the field that will be stored in the index.
Defaults to the property/field name.
See here for more information: http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/mapping-core-types.html

Adding alias fn for existing field firstname
PUT myindex/_mapping
{
"properties": {
"fn": {
"type": "alias",
"path": "firstname"
}
}
}
Should work this way as of Elasticsearch 7.

Probably you can try creating an alias on your index with filter on the desired field. Your filter must be written in such a way that it selects all the entries from your field. Please refer Filtered aliases section in here. But I am interested in knowing your use case. Why you want to create alias on particular field.

Related

Elasticsearch nested objects with query_string as first class attributes

I'm trying to index a nested field as a first-class attribute in my document so that I can search them using query_string without dot syntax.
For example, if I have a document like
"data": { "name": "Bob" }
instead of searching for data.name:Bob I would like to be able to search for name:Bob
The root of my issue is that we index a jsonb column that may have varying attributes. In some instances the data property may contain a data.business attribute, etc. I would like users to be able to search on these attributes without needing to "dig" into the object.
The data field does not have to be indexed as a nested type unless necessary; I was indexing it as an object previously.
I have tried to leverage the _all field as suggested in this post.
I have also tried to use include_in_parent:true and set the datatype as nested for my data field as suggested in this post.
I have also looked into the inner_hits feature to no avail.
Here's an example of my mapping for the data attribute.
PUT my_index
{
"mappings": {
"my_type": {
"properties": {
"data": {
"type": "object"
}
}
}
}
}
Example document
PUT my_index/_doc/1
{
"data": {
name: "bob",
business: "None of yours"
}
}
And how my query currently looks:
GET my_index/_search
{
"query": {
"query_string": {
"query": "name:bob",
"fields": ["data.*"]
}
}
}
With the current setup I almost get my desired results. I can search on individual properties like data.name:bob and data.business:"None of yours" and get back the correct documents.
However I want to be able to get the exact same results with business:"None of yours" or name:bob.
Thanks in advance for any help!
I figured it out using dynamic templates. For anyone coming across this in the future, here is how I solved the issue:
I used path_match to match the data object (data.*).
Then using copy_to and {name} I dynamically created top-level fields on my parent object.
{
"dynamic_templates":[
{"template_1":
{"mapping":
{"copy_to":"{name}"},
"path_match":"data.*"
}
}
]
}

Elasticsearch 6.2: terms query require lowercase input when searching on keyword

I've created an example index, with the following mapping:
{
"_doc": {
"_source": {
"enabled": False
},
"properties": {
"status": { "type": "keyword" }
}
}
}
And indexed a document:
{"status": "CMP"}
When searching the documents with this status with a terms query, I find no results:
{
"query" : {
"terms": { "status": ["CMP"]}
}
}
However, if I make the same query by putting the input in lowercase, I will find my document:
{
"query" : {
"terms": { "status": ["cmp"]}
}
}
Why is it? Since I'm searching on a keyword field, the indexed content should not be analyzed and should match an uppercase value...
no more #Oliver Charlesworth Now - in Elastic 6.x - you could continue to use a keyword datatype, lowercasing your text with a normalizer,doc here. However in every cases you should change your index mapping and reindex your docs
The index and mapping creation and the search were part of a test suite. It seems that the setup part of the test suite was not executed, and the mapping was not applied to the index.
The index was then using the default types instead of the mapping types, resulting of the use of string fields instead of keywords.
After changing the setup method of the automated tests, the mappings are well applied to the index, and the uppercase values for the status "CMP" are now matching documents.
The symptoms you're seeing shouldn't occur, unless something else is wrong.
A keyword index is not analysed, so your index should contain only CMP. A terms query is also not analysed, etc. so your index is searched only for CMP. Hence there should be a match.

ElasticSearch 6, copy_to with dynamic index mappings

Maybe I'm missing something simple, but still could not figure out the following thing:
As of ES 6.x the _all field is deprecated, and instead it's suggested to use the copy_to instruction (https://www.elastic.co/guide/en/elasticsearch/reference/current/copy-to.html).
However, I got an impression that you need to explicitly specify the fields which you want to copy to the custom _all field. But if I use dynamic mappings, I don't know the fields in advance, and therefore cannot use copy_to?
Any way I can tell ES to copy all encountered fields to the custom _all field so that I can search across all fields?
Thanks in advance!
You could use Dynamic Templates. Basically create an index, add the custom catch_all field and then specify that particular property for all the fields that are strings. (Haven't done this before, but I believe this is the only way now. Since the field catch_all will be already present when you put the dynamic template, it will not match the catch_all - meaning that the catch_all will not copy to itself, but check it out yourself to make sure).
PUT my_index
{
"mappings": {
"_doc": {
"dynamic_templates": [
{
"strings": {
"match_mapping_type": "string",
"mapping": {
"type": "text",
"copy_to": "catch_all"
}
}
}
]
}
}
}

Unanalyzed fields on Kibana

i need help to correct kibana field. when I try to visualizing the fields, shown me the following warning:
Careful! The field contains Analyzed selected strings. Analyzed
strings are highly unique and can use a lot of memory to visualize.
Values: such as bar will be foo-foo and bar broken into. See Core
Mapping Types for more information on setting esta field Analyzed as
not
Elasticsearch default dynamic mapping is to analyze any string field (break the field into tokens, for instance: aaa_bbb_ccc will be break down into aaa,bbb and ccc).
If you do not want such behavior you must change the mapping settings
before any document was pushed into the index.
You have two options to do that:
Change the mapping for a particular index using mapping API, in a static way or dynamic way (dynamic means that the mapping will be applies also to fields that still does not exist in the index)
You can change the behavior of any index according to a pattern, using the template API
This example shows a template that changes the mapping for any index that starts with "app", applying "not analyze" to any field in any type and make sure "timestamp" is a date (good for cases in with the timestamp is represented as a number of seconds from 1970):
{
"template": "myindciesprefix*",
"mappings": {
"_default_": {
"dynamic_templates": [
{
"strings": {
"match_mapping_type": "string",
"mapping": {
"type": "string",
"index": "not_analyzed"
}
}
},
{
"timestamp_field": {
"match": "timestamp",
"mapping": {
"type": "date"
}
}
}
]
}
}
}
Really you dont have any problem is only a message of info, but if you dont want analyzed fields when you build your index in elasticsearch you must indicate that one field is a not analyzed field.

Is there a way to apply the synonym token filter in ElasticSearch to field names rather than the value?

Consider the following JSON file:
{
"titleSony": "Matrix",
"cast": [
{
"firstName": "Keanu",
"lastName": "Reeves"
}
]
}
Now, I know in ElasticSearch, you can apply a synonym token filter to field values as given in the following link: Elasticsearch Analysis: Synonym token filter.
Hence, I can create a "synonym.txt" file with Matrix => Matx, then if I search for titleSony:Matx, it will return the documents with Matrix as well.
Now, what I would like is to create a synonym for the field name titleSony. For example - titleSony => titleAll, such that when I search for titleAll, I should get all documents with titleSony as well.
Is there any way to accomplish this in ElasticSearch?
Now, what I would like is to create a synonym for the field name "titleSony". For example - titleSony => titleAll , hence when I search for "titleAll", I should get all documents with "titleSony" as well.
Yes, somewhat. Elasticsearch has some default behavior very similar to this, which I'll touch on in a bit.
The feature you're looking for is called "Copy to field." It allows you to specify that the terms in one field should be copied into another. This is useful for consolidating terms you expect to match into a single field, to help simplify your query when you would like to match against any one of a number of fields.
In this example, you would specify in your mapping that the terms in the titleSony field ought to be copied into the titleAll field. Presumably you'd have other fields (say, titleDisney) which also copy into that field as well. So a search against titleAll will effectively match the other fields whose terms are copied into it.
An excerpt of your mapping might look something like this:
{
"movies" : {
"properties" : {
"titleSony" : { "type" : "string", "copy_to" : "titleAll" },
"titleDisney" : { "type" : "string", "copy_to" : "titleAll" },
"titleAll" : { "type" : "string" },
"cast" : { ... },
...
}
}
I mentioned earlier that Elasticsearch does something like this. By default it creates a special field called _all into which all the document's terms are copied. This field lets you construct very simple queries to match against terms that occur in any field on the document. So as you see, this is a fairly common convention in Elasticsearch. (Elasticsearch mapping: _all field.)

Resources