I am newbie to elastic search
I have an education index in es
index creation
when i search 'btech' with match query as
"match" : { "name" : "btech" }
the result is like
result json object
but i need btech(exact match word) as the first document and remaining documents followed by it.
so for that what i have to change in my index creation
can anybody please help me
You can use term query
"term" : { "name" : "btech" }
Or regexp query
"regexp" : { "name" : "btech" }
You are using text type, make sure to check keyword type too
from documentation
If you need to index structured content such as email addresses,
hostnames, status codes, or tags, it is likely that you should rather
use a keyword field.
Related
Is it possible to do conditional field query if match was not found for another field ?
for eg: if I have a 3 fields in the index local_rating , global_rating and default_rating , I need to first check in local_rating and if there is no match then try for global_rating and finally for default_rating .
is this possible to do with one query ? or any other ways to achieve this
thanks in advance
Not sure about any existing features of Elasticsearh to fulfill your current requirements but you can try with fields and per-fields boosting, Individual fields can be boosted with the caret (^)notation. Also I don't know boosting is possible with numeric value or not?
GET /_search
{
"query": {
"multi_match" : {
"query" : 10,
"fields" : [ "local_rating^6", "global_rating^3","default_rating"]
}
}
}
See: https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-multi-match-query.html#field-boost
i have been using ES 5.x version and this is my sample data set json.
{"id":"1"}
{.... "company" : "HCL-US",....}
{"id":"2"}
{.... "company" : "HCL",....}
{"id":"3"}
{.... "company" : "HCL-IND",....}
{"id":"4"}
{.... "company" : "HCL-AUS",....}
How can i search and get who is belonging to "HCL-US". i tried using this query "_search?q=company:"HCL-US"" , it is returning HCL * result. How can i match exact string with special string.
You can use Term Query that matches exact term. Assuming company is a text field, you will get a keyword version of the same , following query should do the needful
{
"query": {
"term": {
"company.keyword": {
"value": "HCL-US"
}
}
}
}
1/ You can specify a whitespace analyzer in the mapping for the field company. This analyzer will split the query only on whitespace while the standard will split on non-alphanumeric characters.
The standard analyzer is the one used when no analyzer is defined.
2/ Or your can query on company.keyword which is a field automatically created for text field since 5.X . This keyword is not analyzed and you can safely use a term query on it to do exact matching.
I wrote the following query concerning a field that is tokenized by whitespace :
"match" {
"field" : {
"query" : "bora"
}
}
I have two documents that matches the query on my index, one with "bora" on that field, another with "bora bora".
My problem is that "bora bora" document ends up with a better score than the other and this is not the required behaviour.
Do you see a way to do the same query but prioritizing the records which are not a repetition of the searched word ?
I can't update the index / remove the tokenization.
here is elasticsearch official website about terms:
https://www.elastic.co/guide/en/elasticsearch/reference/2.1/query-dsl-terms-query.html
As we can see, if we want to do terms lookup mechanism query, we should use command like this:
curl -XGET localhost:9200/tweets/_search -d '{
"query" : {
"terms" : {
"user" : {
"index" : "users",
"type" : "user",
"id" : "2",
"path" : "followers"
}
}
}
}'
But what if i want to do query by other field of users.
Assume that users has some other fields such as name and can i use terms lookup mechanism finding the tweets by giving users name but not id.
I have tried to use command like this:
curl -XGET localhost:9200/tweets/_search -d '{
"query" : {
"terms" : {
"user" : {
"index" : "users",
"type" : "user",
"name" : "Jane",
"path" : "followers"
}
}
}
}'
but it occurs error.
Looking forward to your help. Thank you!
The terms lookup mechanism is basically a built-in optimization to not have to make two queries to JOIN two indices, i.e. one in index A to get the ids to lookup and a second to fetch the documents with those ids in index B.
In contrary to SQL, such a JOIN can only work on the id field since this is the only way to uniquely retrieve a document from Elasticsearch via a GET call, which is exactly what Elasticsearch will do in the terms lookup.
So to answer your question, the terms lookup mechanism will not work on any other field than the id field since the first document to be retrieved must be unique. In your case, ES would not know how to fetch the document for the user with name Jane since name is just a field present in the user document, but in no way a unique identifier for user Jane.
I think you did not understand exactly how this works. Terms lookup query works by reading values from a field of a document with the given id. In this case, you are trying to match the value of field user in tweets index with values of field followers in document with id "2" present in users index and user type.
If you want to read from any other field then simply mention that in "path".
What you mainly need to understand is that the lookup values are all fetched from a field of a single document and not multiple documents.
I am using Elasticsearch to search for a group a user should join. I have the user data nested into the search query. On return I get back the closest matched group that user should be in.
The field I am searching on is a nested field as follows:
`{"interests": [
{"topics":["python", "stackoverflow", "elasticsearch"]},
{"topics":["arts", "textiles"]}
]}`
However if you want an understanding of a match - how do you do this?
Elasticsearch does have an explain function which says what the scoring is made up of using tfidf, but not specifically what terms were used.
For example, if I search for 'Textile', the doc should match on 'textiles'. Thus I want the term 'textiles' to be returned in explain or some other way.
The only way I see that provides this need, is to store the search and the document retrieved and then process both to discover words ES has most likely matched on.
EDIT - for some more clarity of the question
An example in my index of a group which has "interests": ['arts', 'fine arts', 'art painting', 'arts and crafts', 'sports']
Now my search, I am looking for Arts and many other things. Now the term I am searching for comes up in this list many times, thus should always be a contributor.
What I want in the response is to say these words were matched ['arts', 'fine arts', 'art painting', 'arts and crafts']along with the degree to which they match i..e 'arts' should be higher than the others, but all others are also relevant
Elasticsearch allows you to specify the _name field for all queries and
filters. This means that you can separate your query into different parts with
separate names, which will allow you to determine which parts matched.
For example:
{
"query" : {
"bool" : {
"should" : [
{"match" : { "interests.topics" : {"query" : "python", "_name" : "py-topic"} }},
{"match" : { "interests.topics" : {"query" : "arts", "_name" : "arts-topic"} }}
]
}
}
}
Then, in your response, you will get back any array of which queries (or
filters) matched and you can determine if the py-topic query and/or the
arts-topic query matched above.