I have document A, B, C in the same document type. All 3 has a property is_type = 'Normal', is_type = 'Normal', is_type = 'AbNormal'. I want to get search Response in one single query and then just use Search Response API to get the list of Documents which were having type as normal and abnormal. I know aggregation will not help in getting the document as it's just aggregation. Any help would be appreciated.
Related
i have a query and i want to go through two different documents, is it possible to do it ?
Document A { _id, senders_ID[sender_id]}
Document B { sender_id, firstname}
// i want to loop through document A and get each sender_id and go to document B to get the firstname.
Is it what you are looking for ?
I have an index in elasticsearch which contains a Id field and a geopoint.
right now in order to get the nearest documents I have to make two queries, one to get the original document by its id and after that use its coordinates to do a geosort. I was wondering if there is anyway to execute this as a single query.
public IEnumerable<RestaurantSearchItem> GetNearbyRestaurants(double latitude, double longitude)
{
var query = _elasticClient.Search<RestaurantSearchItem>(s =>
s.Index(RestaurantSearchItem.IndexName)
.Sort(
ss =>ss.GeoDistance(
g => g
.Field(p => p.Location)
.DistanceType(GeoDistanceType.Plane)
.Unit(DistanceUnit.Meters)
.Order(SortOrder.Ascending)
.Points(new GeoLocation(latitude,longitude)))));
var nearByRestaurants = query.Documents;
foreach (var restaurant in nearByRestaurants)
{
restaurant.Distance = Convert.ToDouble(query.Hits.Single(x => x.Id == restaurant.Id).Sorts.Single());
}
return nearByRestaurants;
}
I don't think it's possible to do this in one query; the latitude and longitude used for sorting can't be looked up from elsewhere in the data, so needs to be supplied in the request.
As of my knowledge, the only Elasticsearch query that accepts id of a document as its parameter is terms query, which fetches list of terms for the query from the given document.
But you want to find relevant documents based on location, not exact terms.
This can be achieved with denormalization of your data. It might look like storing the list of nearby restaurants in a nested field.
In the case of denormalization you will have to pre-compute all nearby restaurants before inserting the document in the index.
For a given query I want to get only the list of _id values without getting any other information (without _source, _index, _type, ...).
I noticed that by using _source and requesting non-existing fields it will return only minimal data but can I get even less data in return ?
Some answers suggest to use the hits part of the response, but I do not want the other info.
Better to use scroll and scan to get the result list so elasticsearch doesn't have to rank and sort the results.
With the elasticsearch-dsl python lib this can be accomplished by:
from elasticsearch import Elasticsearch
from elasticsearch_dsl import Search
es = Elasticsearch()
s = Search(using=es, index=ES_INDEX, doc_type=DOC_TYPE)
s = s.fields([]) # only get ids, otherwise `fields` takes a list of field names
ids = [h.meta.id for h in s.scan()]
I suggest to use elasticsearch_dsl for python. They have a nice api.
from elasticsearch_dsl import Document
# don't return any fields, just the metadata
s = s.source(False)
results = list(s)
Afterwards you can get the the id with:
first_result: Document = results[0]
id: Union[str,int] = first_result.meta.id
Here is the official documentation to get some extra information: https://elasticsearch-dsl.readthedocs.io/en/latest/search_dsl.html#extra-properties-and-parameters
My ElasticSearch 2.x NEST query string search contains a wildcard:
Using NEST in C#:
var results = _client.Search<IEntity>(s => s
.Index(Indices.AllIndices)
.AllTypes()
.Query(qs => qs
.QueryString(qsq => qsq.Query("Micro*")))
.From(pageNumber)
.Size(pageSize));
Comes up with something like this:
$ curl -XGET 'http://localhost:9200/_all/_search?q=Micro*'
This code was derived from the ElasticSearch page on using Co-variants. The results are co-variant; they are of mixed type coming from multiple indices. The problem I am having is that all of the hits come back with a score of 1.
This is regardless of type or boosting. Can I boost by type or, alternatively, is there a way to reveal or "explain" the search result so I can order by score?
Multi term queries like wildcard query are given a constant score equal to the boosting by default. You can change this behaviour using .Rewrite().
var results = client.Search<IEntity>(s => s
.Index(Indices.AllIndices)
.AllTypes()
.Query(qs => qs
.QueryString(qsq => qsq
.Query("Micro*")
.Rewrite(RewriteMultiTerm.ScoringBoolean)
)
)
.From(pageNumber)
.Size(pageSize)
);
With RewriteMultiTerm.ScoringBoolean, the rewrite method first translates each term into a should clause in a bool query and keeps the scores as computed by the query.
Note that this can be CPU intensive and there is a default limit of 1024 bool query clauses that can be easily hit for a large document corpus; running your query on the complete StackOverflow data set (questions, answers and users) for example, hits the clause limit for questions. You may want to analyze some text with an analyzer that uses an edgengram token filter.
Wildcard searches will always return a score of 1.
You can boost by a particular type. See this:
How to boost index type in elasticsearch?
does anybody know how to do facet search with Nest?
My index is https://gist.github.com/3606852
would like to search for some keyword in 'NumberEvent' and dispaly the result if the keyword exist.Please help me !!!
This is using the assumption that the MyPoco class exists and maps to your elasticsearch document. If it doesn't you can use dynamic but you'l have to swap the lambda based field selectors with strings.
var result = client.Search<MyPoco>(s=>s
.From(0)
.Size(10)
.Filter(ff=>ff.
.Term(f=>f.Categories.Types.Events.First().NumberEvent.event, "keyword")
)
.FacetTerm(q=>q.OnField(f=>f.Categories.Types.Facets.First().Person.First().entity))
);
result.Documents now holds your documents
result.Facet<TermFacet>(f => f.Categories.Types.Facets.First().Person.First().entity); now holds your facets
Your document seems a bit strange though in the sense that it already has Facets with counts in them.