"kibanaSavedObjectMeta": {
"searchSourceJSON": "{\"index\":\"4eb9f840-3969-11e8-ae19-552e148747c3\",\"filter\":[],\"query\":{\"language\":\"lucene\",\"query\":\"\"}}"
}
The above mentioned snippet is a exported JSON of a Kibana visualization. Without exporting this json is there a direct way to get this
\"index\":\"4eb9f840-3969-11e8-ae19-552e148747c3\ index id.
And if i am not wrong this is supposed to be the index id as its common across visualization with same index.
So, you can retrieve all index patterns using this query
GET .kibana/_search?q=type:index-pattern&size=100
Additionally, you can retrieve a specific set of index pattern given its name using
GET .kibana/_search?q=type:index-pattern%20AND%20index-pattern.title:indexname
Similarly, regarding visualizations, you can retrieve one by name using
GET .kibana/_search?q=type:visualization%20AND%20visualization.title:vizname
Related
I am new to apache NiFi.
I am trying to put data into elasticsearch using nifi.
I want to specify an index name by combining a specific string and the value converted from a timestamp field into date format.
I was able to create the desired shape with the expression below, but failed to create the index name with the value of the timestamp field of the content.
${now():format('yyyy-MM-dd')}
example json data
{
"timestamp" :1625579799000,
"data1": "abcd",
"date2": 12345
}
I would like to get the following result:
index : "myindex-2021.07.06"
What should I do? please tell me how
I know that if you use the PutElasticSearch Processor, you can provide it with a specific index name to use. And as long as the index name meets the proper ElasticSearch format for naming a new index, if the enable auto index creation in ElasticSearch is turned on, then when sent, Elastic will create the new index with the desired name. This has worked for me. Double check the Elastic Naming Rules that can be found here or https://docs.aws.amazon.com/elasticsearch-service/latest/developerguide/es-indexing.html
I am new to Elastic Search. I would like to know if the following steps are how typically people use ES to build a search engine.
Use Elastic Search to get a list of qualified documents/results based on a user's input.
Build and use a search ranking model to sort this list.
Use this sorted list as the output of the search engine to the user.
I would probably add a few steps
Think about your information model.
What kinds of documents are you indexing?
What are the important fields and what field types are they?
What fields should be shown in the search result?
All this becomes part of your mapping
Index documents
Are the underlying data changing or can you index it just once?
How are you detecting new docuemtns/deletes/updates?
This will be included in your connetors, that can be set up in multiple ways, for example using the Documents API
A bit of trial and error to sort out your ranking model
Depending on your use case, the default ranking may be enough.
have a look at the Search API to try out different ranking.
Use the search result list to present the results to the end user
I am using Elasticsearch 6.2.
I have an index products with index_type productA having data with following structure:
{
"id": 1,
"parts": ["part1", "part2",...]
.....
.....
}
Now during the query time, I want to add or project a field parts_count to the response which simply represents the number of parts i.e the length of parts array. Also, if possible, I would also like to sort the documents of productA based on the generated field parts_count.
I have gone through most of the docs but haven't found a way to achieve this.
Note:
I don't want to update the mapping and add dynamic fields. I am not sure if Elasticsearch allows it. I just wanted to mention it.
Did you read about Script Fields and on Script Based Sorting?
I think you should be able to achieve both things and this not require any mapping updates.
I want to have in the search response only documents with specified doc id. In stackoverflow I found this question (Lucene filter with docIds) but as far as I understand there is created the additional field in the document and then doing search by this field. Is there another way to deal with it?
Lucene's docids are intended only to be internal keys. You should not be using them as search keys, or storing them for later use. Those ids are subject to change without warning. They will be changed when updating or reindexing documents, and can change at other times, such as segment merges, as well.
If you want your documents to have a unique identifier, you should generate that key separate from the docId, and index it as a field in your document.
I'm looking to search for a particular JSON document in a bucket and I don't know its document ID, all I know is the value of one of the sub-keys. I've looked through the API documentation but still confused when it comes to my particular use case:
In mongo I can do a dynamic query like:
bucket.get({ "name" : "some-arbritrary-name-here" })
With couchbase I'm under the impression that you need to create an index (for example on the name property) and use startKey / endKey but this feels wrong - could you still end up with multiple documents being returned? Would be nice to be able to pass a parameter to the view that an exact match could be performed on. Also how would we handle multi-dimensional searches? i.e. name and category.
I'd like to do as much of the filtering as possible on the couchbase instance and ideally narrow it down to one record rather than having to filter when it comes back to the App Tier. Something like passing a dynamic value to the mapping function and only emitting documents that match.
I know you can use LINQ with couchbase to filter but if I've read the docs correctly this filtering is still done client-side but at least if we could narrow down the returned dataset to a sensible subset, client-side filtering wouldn't be such a big deal.
Cheers
So you are correct on one point, you need to create a view (an index indeed) to be able to query on on the content of the JSON document.
So in you case you have to create a view with this kind of code:
function (doc, meta) {
if (doc.type == "youtype") { // just a good practice to type the doc
emit(doc.name);
}
}
So this will create a index - distributed on all the nodes of your cluster - that you can now use in your application. You can point to a specific value using the "key" parameter