Is there an available JSON schema for the request object required by Elasticsearch Create Index API?
I didn't find any schema in the JSON Schema Store.
I want to validate the JSON object in IntelliJ IDEA and have the assisted edit.
Alternatively, is there any IntelliJ plugin with built-in support for editing these files? I did not find the support in any of the existing Elasticsearch* plugins.
You can use the create index API to add a new index to an Elasticsearch cluster. When creating an index, you can specify the following:
Settings for the index
Mappings for fields in the index
Index aliases
The JSON object to create Elasticsearch index looks like this:
{
"settings": {
...
},
"mappings": {
...
},
"aliases": {
...
}
}
Related
Elasticsearch - Update field of existing documents when changing mapping
I would like to add new field of type boolean to existing elastic mapping which can be described as follows:
{
"properties": {
"newBooleanField": {
"type": "boolean",
"null_value": true
}
}
}
After updating mapping I realised that existing documents doesn't have this field set to true. Only new documents created after changing mapping have these fields with default value true.
Is it possible to set default value to all existing documents when changing mapping without reindexing or manually change documents via script?
Here it is my requirement, This is my 3levels of data which I am gettting from DB , my requirement is when I search for Developer I should get all the values of Developer such as Geo and Graph from Data2 in a list and while coming to support my values should contain Server and Data in a list and then on the basis of selection of Data1 . Data3 should be able to do the search , like suppose when we select developer then Geopos and Graphpos...
the logic which i need to use here is of elasticsearch
data1 data2 data3
Developer GEO GeoPos
Developer GRAPH GraphPos
Support SERVER ServerPos
Support Data DataPos
this is what I have done to crete the index and to get the values
curl -X PUT http://localhost:9200/mapping_log
{ "mappings":{ "properties":{"data1:{"type": "text","fields":{"keyword":{"type":"keyword"}}}, {"data2":{"type": "text","fields":{"keyword":{"type":"keyword"}}}, {"data3":{"type": "text","fields":{"keyword":{"type":"keyword"}}}, } } }
searching values , I am not sure what I am going to get can u pls help with search dsl query too
curl -X GET "localhost:9200/mapping_log/_search?pretty" -H 'Content-Type: application/json' -d'
{
"query": {
"match": {
"data1.data2": "product"
}
}
}
How to create document for such type of Data can we create json and post it through postman or curl ?
If your documents are not indexed in elastic search first you need to ingest them to an existing index in elastic with the aid of Logstah , you can find many configuration file related to you input database.
Before transforming your documents create and index in elastic with multi fields mapping, you can use dynamic mapping(elastic default mapping) also and change your Dsl query but I recommend to use multi fields mapping as follow
PUT /mapping{
"mappings":
{"properties": {"rating":{"type": "float"},
"content":{"type": "text"},
"author":{"properties": {
"name":{"type": "text"},
"email":{"type": "keyword"}
}}
}}
}
The result will be
Mapping result
then you can query the fields in kibana Dev tools with DSL query like below
GET /mapping/_search{
"query": {"match":
{ "author.email": "SOMEMAIL"}}
}
I realise mapping types are being removed in 7.x but I am working with a solution that uses 6.x.
I have an index I am creating which has a location property. When creating the index I add the following mapping property:
mappings: {
_doc: {
properties: {
location: {
type: 'geo_point'
}
}
}
}
There are other properties that will be in the index but I'm happy for those to be defined automatically (I presume I can do that as elsewhere in the application it has been done this way with no problems).
The index is created ok but when I index my first entity and run a query using the location field I get the following error: failed to find geo_point field [location]
Looking at the mappings now defined in ElasticSearch I can see my location field has now become an object with two float values instead of a geo_point:
{"job-posts":{"aliases":{},"mappings":{"_doc":{"properties":{"location":{"properties":{"lat":{"type":"float"},"lon":{"type":"float"}}},"settings":{"index":{"creation_date":"1591636220162","number_of_shards":"5","number_of_replicas":"1","uuid":"qwAybNlFQ4i3q7IecdZFvA","version":{"created":"6040099"},"provided_name":"job-posts"}}}}
Any ideas as to what I'm doing wrong and why my mapping is being overwritten?
Updated
Right after I create the index the mapping looks like this:
{"job-posts":{"mappings":{"_doc":{"properties":{"location":{"type":"geo_point"}}}}}}
Looks like you forgot to include properties:
PUT myindex?include_type_name=true
{
"mappings": {
"_doc": {
"properties": {
"location": {
"type": "geo_point"
}
}
}
}
}
If that doesn't help, what's the index mapping right after you create the index but before you sync the first doc?
How to dynamically add an index to alias when index is dynamically created every day? I'm using Logstash to send data to our ElasticSearch engine, version 6.1.1, with the following convention:
elasticsearch {
hosts => "10.01.01.01:9200"
index => "%{[#metadata][beat]}-%{[#metadata][version]}-%{+YYYY.MM.dd}"
}
This dynamically creates a new index per day. I configured the system based on install instructions for this version.
I created an alias to be able to query across all index types (Filebeat/Winlogbeat/etc).
How can I dynamically make all dynamic indexes be added to this alias to avoid having a system administrator perform a daily task to add the index, like: (using Kibana DevTools)
POST /_aliases
{
"actions": [
{ "add": { "index": "winlogbeat-6.1.1-2018.02.16", "alias": "myaliasname"}}
]
}
If I change the mapping so certain properties have new/different boost values, does that work even if the documents have already been indexed? Or do the boost values get applied when the document is indexed?
You cannot change field level boost factors after indexing data. It's not even possible for new data to be indexed once the same fields have been indexed already for previous data.
The only way to change the boost factor is to reindex your data. The pattern to do this without changing the code of your application is to use aliases. An alias points to a specific index. In case you want to change the index, you create a new index, then reindex data from the old index to the new index and finally you change the alias to point to the new index. Reindexing data is either supported by the elasticsearch library or can be achieved with a scan/scroll.
First version of mapping
Index: items_v1
Alias: items -> items_v1
Change necessary, sencond version of the index with new field level boost values :
Create new index: items_v2
Reindex data: items_v1 => items_v2
Change alias: items -> items_v2
This might be useful in other situations where you want to change your mapping.
Field level boosts are, however, not recommended. The better approach is to use boosting at query time.
Alias commands are:
Adding an alias
POST /_aliases
{
"actions": [
{ "add": {
"alias": "tems",
"index": "items_v1"
}}
]
}
Removing an alias
POST /_aliases
{
"actions": [
{ "remove": {
"alias": "tems",
"index": "items_v1"
}}
]
}
They do not.
Index time boosting is generally not recommended. Instead, you should do your boosting when you search.