as mentioned in the title, I want to disable index a specified field in elasticsearch, for example, I have a fields named #fileds which contains three sub-fields like name、age、salary, now I do not want to index the field #fields.age in elasticsearch, how can I achieve that? I have tried to use include_in_all parameters, but it doesn't work. mapping configuration like:
"mappings": {
"fluentd": {
"properties": {
"#fields": {
"properties": {
"age": {
"type": "text",
"include_in_all": false,
"index": "no"
}
}
}
}
}
}
when I use this mapping configuration above, I can only see #fields.age in the index's mapping, #fields.name and #fields.salary should appear on the index's mapping not the #fields.age, how can this happen? any answers will be appreciated.
Related
I put an object with some field and i wanna figure out how to mapping the index to handle and show the values like elasticsearch. I dunno why opensearch separate to individual fields the values. Both app has the same index mappings but the display is different for something.
I tried to map the object type set to nested but nothing changes
PUT test
{
"mappings": {
"properties": {
"szemelyek": {
"type": "nested",
"properties": {
"szam": {
"type": "integer"
},
"nev": {
"type": "text"
}
}
}
}
}
}
I am new to elastic search. I have an index named users, which has a lot of fields I know. But a few more fields can be added in the future.
So when defining my mapping, I want to include the fields that I know currently with dynamic "strict", but in the future, if I want to add the new field, how will update the new mapping and if I do it, will I have to reindex everything.
I found in the ES documents that mappings are applied only during index creation time. So I am a little confused here, what's the right way to approach this.
You can always update the mapping in future, even after keeping it strict using the put mapping api. You'll not require existing data to be re-indexed unless you want the newly added field have some value for the older documents which were added before updating the mapping with the new field.
Lets assume you already have an index test with one field say field1 of type keyword. Now in future you have a requirement to add new field say field2 of integer type. You can do so by the put mapping api as below,
PUT test/_mapping
{
"properties": {
"field2": {
"type": "integer"
}
}
}
After executing the above if you check the mapping using
GET test/_mapping
You can see the new field as well in the response,
{
"test" : {
"mappings" : {
"dynamic" : "strict",
"properties" : {
"field1" : {
"type" : "keyword"
},
"field2" : {
"type" : "integer"
}
}
}
}
}
Inner objects inherit the dynamic setting from their parent object or from the mapping type. In the following example, dynamic mapping is disabled at the type level, so no new top-level fields will be added dynamically.
However, the user.social_networks object enables dynamic mapping, so you can add fields to this inner object.
https://www.elastic.co/guide/en/elasticsearch/reference/current/dynamic.html
PUT my-index-000001
{
"mappings": {
"dynamic": false,
"properties": {
"user": {
"properties": {
"name": {
"type": "text"
},
"social_networks": {
"dynamic": true,
"properties": {}
}
}
}
}
}
}
I have a big size field in MySQL and do not want to save the original value to ElasticSearch. Is there a method just like Lucene Field.Store.NO?
Thanks.
You just need to define the "store" mapping accordingly, eg. :
PUT your-index
{
"mappings": {
"properties": {
"some_field": {
"type": "text",
"index": true,
"store": false
}
}
}
}
You may also want to disable the _source field :
#disable-source-field
The _source field contains the original JSON document body that was passed at index time [...] Though very handy to have around, the source field does incur storage overhead within the index.
For this reason, it can be disabled as follows:
PUT your-index
{
"mappings": {
"_source": {
"enabled": false
}
}
}
I would like to use elastic search to index the JSON schema provided below
{
"data": "etc",
"metadata": {
"foo":"bar",
"baz": "etc"
}
}
However the metadata can vary and I do not know all the fields that could be present. Is there a way to tell elastic search that if it sees a value in the metadata object to index it in a certain way? (I do know that all the values would be strings)
Thanks
Yes, you can do that using dynamic templates, basically like this:
PUT my_index
{
"mappings": {
"_doc": {
"dynamic_templates": [
{
"full_name": {
"path_match": "metadata.*",
"mapping": {
"type": "text" <---- add your desired mapping here
}
}
}
]
}
}
}
I'm mapping a couchbase gateway document and I'd like to tell elasticsearch to avoid indexing the internal attributes added by the gateway like the "_sync", this object contains another object named "channels" which has the following form:
"channels": {
"i7de5558-32ad-48ca-bf91-858c3a1e4588": 12
}
So I guess the mapping of this object would be like:
"channels": {
"type": "object",
"properties": {
"i7de5558-32ad-48ca-bf91-858c3a1e4588": {
"type": "integer",
"index": "not_analyze"
}
}
}
The problem is that the keys are always changing, so I don't know if I should use a wildcard like this "*": {"type": "integer", "index": "not_analyze"} for this property or do something else.
Any advice please?
If the fields are of integer types, you don't have to provide them explicitly in the mapping. You can create an empty mapping ,index documents with these fields. Elasticsearch will infer the type of field and update the mapping dynamically. You can also use dynamic templates for this.
{
"mappings": {
"my_type": {
"dynamic_templates": [
{
"analysed_string_template": {
"path_match": "channels.*",
"mapping": {
"type": "integer"
}
}
}
]
}
}
}
There`s a dynamic way to do that as you need, is called dynamic template
Using templates you are able to create rules like this:
PUT /my_index
{
"mappings": {
"my_type": {
"date_detection": false
}
}
}
In your case you could create a template to set all news fields inside the channel object as not_analyzed.
Hope it will help