I want to demote all documents that have inv=0(possible values from 0 to 1000) to the end of the result set. i have got other sorting options like name desc also as part of the query.
For example below are my solr documents
Doc1 : name=apple , Inv=2
Doc2 : name=ball , Inv=1
Doc3 : name=cat , Inv=0
Doc4 : name=dog , Inv=0
Doc5 : name=fish , Inv=4
Doc6 : name=Goat , Inv=5
I want achieve below sorting ...here, i want to push all documents with inv=0 down to bottom and then apply "name asc" sorting.
Doc1
Doc2
Doc5
Doc6
Doc3
Doc4
my solr request is like
bq: "(: AND -inv:"0")^999.0" & defType: "edismax"
here 999 is the rank that i gave to demote results.
this boosting query works fine. it moves all documents with inv=0 down to the bottom.
But when i add &sort=name asc to the solr query, it prioritizes "sort" over bq..i am seeing below results with "name asc".
Doc1 : name=apple , Inv=2
Doc2 : name=ball , Inv=1
Doc3 : name=cat , Inv=0
Doc4 : name=dog , Inv=0
Doc5 : name=fish , Inv=4
Doc6 : name=Goat , Inv=5
can anyone please help me out. ?
Sort will override the boost.
So, you either move your sort into boost by making that condition map into boost values.
Or you move your boost condition into sort, using query() syntax. This was one of the gems from the Lucene/Solr Revolution 2016 presentation by hoss (click start presentation):
qq = Harry
q = +{!edismax v=$qq}
qf = title actor writer director keywords
sort = query($title_sort,0) desc, title asc
title_sort = {!field f=title v=$qq}
Default sorting criteria in Solr is score desc, where score is a virtual field and it actually represents the document's score.
Once one is passing &sort=name asc it will override default sorting.
Possible solution here might be something like this: &sort=score desc, name asc. Which literally means: please sort by score first and for documents with equal score please make a tie-break by name ascending.
It should work as long as you will have equal scores for doc1, doc2, doc5, doc6.
If it is not the case - then check out this Solr Wiki link for more details how to penalize docs with inv:0.
Related
There's an index_A that contains say about 10K docs. It has many fields like field_1, field_2, ...field_n and one of the fields is product_name.
Then there's another index_B that contains about 10 docs only and is a master catalogue sort of index. It has 2 fields: product_name and product_description.
e.g
{
"product_name" : "EES",
"product_desc" : "Elastic Enterprise Search"
}
{
"product_name" : "EO",
"product_desc" : "Elastic Observability"
}
index_A contains many fields, from that one of the fields is product_name. index_A does not have the field product_desc
I want to insert product_desc field into each document in index_A such that the value of product_name in index_A matches value of product_name in index_B.
i.e. something like set index_A.prod_desc = index_B.prod_desc where index_A.prod_name = index_B.prod_name
How can I achieve that?
Elasticsearch cannot do joins like that
the best approach would be to do this during indexing, using something like an ingest pipeline, or Logstash, or some other piece of code that pulls the description into the product document
solr query : http://192.168.106.58:8983/solr/search/select?q=:&rows=0&facet=true&facet.pivot=location.comm,search.resourcetype
I use facet.pivot to query, but I want to sort with count of (search.resourcetype=somevalue)， for example :
I have documents like this:
{
title:'...',
body: '...'
}
I want to get documents which are more than 90% similar to the with a specific document. I have used this query:
query = {
"query": {
"more_like_this" : {
"fields" : ["title", "body"],
"like" : "body of another document",
"min_term_freq" : 1,
"max_query_terms" : 12
}
}
}
How to change this query to check for 90% similarity with specified doc?
Take a look at the Query Formation Parameter minimum_should_match
You should specify minimun_should_match
minimum_should_match
After the disjunctive query has been formed, this parameter controls
the number of terms that must match. The syntax is the same as the
minimum should match. (Defaults to "30%").
It form query using this
The MLT query simply extracts the text from the input document,
analyzes it, usually using the same analyzer at the field, then
selects the top K terms with the highest tf-idf to form a disjunctive
query of these terms
So if you would like to boost you title field you should boost your title field because if the title contains most of the terms present in the term frequency/ Inverse document frequency. the result should be boosted because it has more relevance. You can boost your title field by 1.5.
Refer this document for referenceren on the more_like_this query
I am very new to elastic search, I need to search the words with particular word match
ex: I have words as
cricketnplay, cricket23, cricket, criketlegend
when I search a word cricket
the result will be like 1st one exact match and next followed matches
cricket
cricket23
cricketlegend
cricketnplay
how to query to get output like this please help,
Thanks in advance
You need to search with _search query.
GET /twitter/tweet/_search
{
"query" : {
"term" : { <field> : "cricket" }
}
}
This query will return all matched elements with match score sorted in descending order of score.
Read more about _search query here
I am moving from ElasticSearch 1.7 to 2.0. Previously while calculating Term Facets I got the Total Count as well. This will tell in how many documents that field exists. This is how I was doing previously.
TermsFacet termsFacet = (TermsFacet) facet;
termsFacet.getTotalCount();
It worked with Multivalue field as well.
Now in current version for Term Aggregation we don't have anything as Total Count. I am getting DocCount inside Aggregation bucket. But that will not work for muti-valued fields.
Terms termsAggr = (Terms) aggr;
for (Terms.Bucket bucket : termsAggr.getBuckets()) {
String bucketKey = bucket.getKey();
totalCount += bucket.getDocCount();
}
Is there any way I can get Total count of the field from term aggregation.
I don't want to fire exists Filter query. I want result in single query.
I would use the exists query:
https://www.elastic.co/guide/en/elasticsearch/reference/2.x/query-dsl-exists-query.html
For instance to find the documents that contain the field user you can use:
{
"exists" : { "field" : "user" }
}
There is of course also a java API:
https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/java-term-level-queries.html#java-query-dsl-exists-query
QueryBuilder qb = existsQuery("name");