Need help with building query through the array in ElasticSearch 6. I have documents that represent some property units with a number of attributes:
{
"Unit":{
"Attributes":{
"Attribute":[
{
"Name":"Elevator",
"Text":"No"
},
{
"Name":"Pet Friendly",
"Text":"Yes"
}
...
]
}
}
}
How can I filter my documents to find all pet friendly units or all units without elevator?
P.S. I am using NEST.
Map Attribute as a nested type, probably with Text mapped as keyword for term level matching. To query, use a bool query with filter clauses, where the clauses will be nested queries.
Related
I was trying to find how flattened type in Elasticsearch works under the hood, the documentation specifies that all leaf values will be indexed into a single field as a keyword, as a result, there will be a dedicated index for all those flattened keywords.
From documentation:
By default, Elasticsearch indexes all data in every field and each indexed field has a dedicated, optimized data structure. For example, text fields are stored in inverted indices, and numeric and geo fields are stored in BKD trees.
The specific case that I am trying to understand:
If I have flattened field and index object with nested objects there is the ability to query a specific nested key in the flattened object. See how to query by labels.release:
PUT bug_reports
{
"mappings": {
"properties": {
"labels": {
"type": "flattened"
}
}
}
}
POST bug_reports/_doc/1
{
"labels": {
"priority": "urgent",
"release": ["v1.2.5", "v1.3.0"]
}
}
POST bug_reports/_search
{
"query": {
"term": {"labels.release": "v1.3.0"}
}
}
Would flattened field have the same index structure as the keyword field, and how it is able to reference the specific child key of flattened object?
The initial design and implementation of the flattened field type is described in this issue. The leaf keys are also indexed along with the leaf values, which is how they are allowing the search for a specific sub-field.
There are some ongoing improvements to the flattened field type and Elastic would also like to support numeric values, but that's not yet released.
Given a document like this:
{
"id": "12345",
"elements": [
{
"type": "configure",
"time": 3000
}
]
}
Is it possible to query for documents with an object in the elements array that have a type of configure and then also retrieve that specific object in the array so that I can also get the time value associated with that element (In this case 3000)?
You can use nested inner_hits to retrieve details of the nested objects that match for a nested query. Note that elements will need to be mapped as a nested datatype field.
{
"query": {
"nested": {
"path": "product_vendors",
"query": {
"bool" :{
"must" : {
"bool" : {
"should" : [
{ "terms": {"product_vendors.manufacturer_style":["FSS235D-26","SG463-1128-5","SG463-2879-4"]}},
{ "terms": {"product_vendors.id":["71320"]}}
]
}
}
}
}
}
}
}
I have above elastic query, not able to understand this. Would anyone please explain what it means and what documents it will return?
Update : #christinabo , i tried your query , and results returned , but here some small issues , apart from the matched documents , two more additional documents are returning in those documents only vendor_id is matching , may i know why two extra unmatched documents are returning , do we need to some attribute or something to make sure strict search and return is allowed , can please suggest on this .
By observing the query, I can understand that there is a nested object in the data. I can imagine that it has this structure:
product_vendors: {
'id': 'the_id',
'manufacturer_style': 'some style'
}
In order to query a nested object, you need a nested query. This is why you have the nested keyword there. In a nested query, you need to specify the path (product_vendors) that leads to the embedded fields (id, manufacturer_style).
Then, the query defines a bool query with the must keyword, which means that the query which follows must appear in matching documents. In this case, what it must appear is another bool query, defined with the should keyword. This contains two terms sub-queries (one for manufacturer_style and one for id) and means that the matching documents should match one or two of them. Each sub-query queries the embedded field by specifying the whole route of the nested object, using the dot (i.e. product_vendors.manufacturer_style).
I would expect the query to return you the documents that match at least one of the terms queries, with the documents that match both to have higher score.
I hope that this explanation gives you an overall idea of this query.
More about bool queries from the documentation here.
I have two TYPES in my elasticsearch index. Both have same mapping. I am using one for active documents, while the other for archived ones.
Now, i want to archive a document i.e. change its _type from active to archived. Both are in same index, so i cannot reindex them as well.
Is there a way to do this in Elasticsearch 5.0 ?
Changing the type is tricky. You would have to remove and then index the document with the new type.
Why not have a field in your document indicating "activeness". Then you can use a bool query to filter by what you want:
{"query": {
"bool": {
"filter": [{"term": {"status", "active"}}],
"query": { /* your query object here */ }
}
}
}
Agree with having a field which indicates the activeness of the document.
(Or)
Use two different indices for "active" and "inactive" types.
Use aliases which map to these indices.
Aliases will give you flexibility to change your indices without downtimes.
I have tried, for example:
{
"sort": [
{
"retail_price": {
"reverse": true
}
}
]
}
... to no avail. Do I need to map the field a special way in order to enable sorting on it?
The field should satisfy two conditions: 1) it has to be indexed and 2) it shouldn't have more than one value per document or more than one token per field. If retail_price is indexed in your case and it still doesn't work for you, could you post a script that demonstrates the problem?