I am using Apache Solr 8 with products as documents. Each document includes sales within the last X days that I want to boost, as well as a title and other fields.
Say productA has been sold 5 times, I want to boost it with score+10; a productB has been sold 50 times, I want to boost the score by 30.
I tried to use a boostFunction that looks like (edismax query parser)
q=Coffee&qf=title&bf=if(lt(sales,5),10,if(lt(sales,50),30))
Solr now returns documents that have nothing to do with my "Coffee"-Query but just match the boostfunction. There are even results with score "0".
E.g.
Rank;Score;Sales;Title
1;58.53;55;Coffee big
2;38.11;50;Coffee
3;30;55;Tea
Any idea to get rid of those "only boost function"-matches?
Found the answer!
My Query-Fields actually included boostings like
&qf=title^2 longDescription^0 whatever^0...
Instead of excluding the results found in those 0-boosted fields, solr adds them and matches with - well score 0.
When I remove the 0-boostings, everything works as intended.
Related
I'm generating facet counts for a multivalued field and sorting them by index in order to see them in alphabetical order. Given a particular facet prefix, I would like to jump to its place in the facet count list and show the facet counts surrounding it. For example, if my prefix is "wha" then I would want the following returned (four before and four after):
weld 1
welsh 5
west 4
wetland 1
whale 99
wheat 123
wheel 1
whey 9
There are millions of values in the field and so I can't just ask for them all. I need to be able to jump to that location or use some kind of filter on the facet counts themselves. I've tried using facet.offset, but I have to basically do a binary search in order to find the appropriate offset which is too slow.
I could probably get close enough if I could put in a range for a facet prefix. For example facet.prefix=[we TO wk] or even multiple prefixes like facet.prefix=we,wf,wg,wh,wi,wj,wk.
I'm currently using other non-Solr solutions to accomplish this, but I would like to use Solr 6.6 in order to take advantage of filter queries.
I am new to solr, please help me in boosting fields.
I have a query like this,
q=name:test* OR description:test*
i want to apply boosting/weight age for name its 500 and for description its 50.
for example:
lets consider "test" term is appearing for 1 time in name field in one record and 20 times in description field its from another record, then boosting calculation should happen like below.
for name: 1 X 500 = 500
for Description: 20 X 50 = 1000.
as result the records with high boosting value should come at top.
so based on above calculation the record which having description field with 20 matches should come on top after that record with 1 match in name field.
If any one have solution for this, please provide
Thanks in advance.
You can boost a field at index time with the boost attribute, or you can apply a boost in the query, such as q=name:test*^50 OR description:test* (and there are some more advanced features here as well).
I bears noting though, Lucene, by default, applies a length normalization that effectively weighs matches on shorter fields more heavily than longer fields. It sounds a bit like that is what you are trying to recreate.
If you need the scoring calculation to be as simple as what you have provided, you would need to write your own Similarity class, I believe.
I have two indexed fields in my Solr schema
Employee Name
Manager Name
Which are plain strings.
my Question is: Given a search term, I want to display top 5 suggested completions from Manager Names and the next 5 from Employee Names.
I can use copy fields, but sometimes I get all top 10 results from Employee Names.
I have a hunch that boosting can help me.. but could not figure out how?
Boost can't help you control the results and distribute 5 each in the top 10 results.
Probably you can check on Field Collapsing, where you can group per role (Manager and Name) and limit 5 results for the group.
So you would have 2 groups returned back to you with 5 results each.
I'm trying to get SOLR range query working. I have a database with over 12 milion documents, and i am filtering by few parameters for example:
product_category:"category1" AND product_group:"group1" AND product_manu:"manufacturer1"
The query itself returns about 700 documents and executes in two-three seconds on average.
But when i want to add date range facet to that query (i want to see how many products were added each day for past x years) it executes in 50 seconds or more. So it seems that it would be faster to just retrieve all matching documents and perform manual counting in java.
So i guess i must be doing something wrong with faceting?
here is an example faceted query:
start=0&rows=0&facet.query=productDate%3A[0999-12-26T23%3A36%3A00.000Z+TO+2012-05-22T15%3A58%3A05.232Z]&q=source%3A%22source1%22+AND+productCategory%3A%22category1%22+AND+type%3A%22type1%22&facet=true&facet.limit=-1&facet.sort=count&facet.range=productDate&facet.range.start=NOW%2FDAY-5000DAYS&facet.range.end=NOW%2FDAY%2B1DAY&facet.range.gap=%2B1DAY
My only explanation is that SOLR is counting fields on some larger document pool than my 700 documents resulting from "q=" parameter. Or maybe i should filter documents in another way?
I have tried changing filterCache size and it works, but it seems to be a waste of memory for queries like these. After all aggregating over 700 documents should be very fast shouldnt it?
Using Solr 3.3
Key Store Item Name Description Category Price
=========================================================================
1 Store Name Xbox 360 Nice game machine Electronic Games 199.99
2 Store Name Xbox 360 Nice game machine Electronic Games 199.99
3 Store Name Xbox 360 Nice game machine Electronic Games 249.99
I have data similar to above table and loaded into Solr. Item Name,
description Category, Price are searchable.
Expected result
Facet Field
Category
Electronic(1)
Games(1)
**Store Name**
XBox 360 Nice game machine priced from 199.99 - 249.99
What will be the query parameters that I can send to Solr to receive results above, basically I wan to group it by Store, ItemName, Description and min max price
And I want to keep paging consistent with the main (StoreName). The paging should be based on the Store Name group. So if 20 stores were found. I should be able to correctly page.
Please suggest
If using Solr 4.0, the new "Grouping" (which replaces FieldCollapsing) fixes this issue when you add the parameter "group.facet=true".
So to group your fields you would have add the following parameters to your search request:
group=true // Enables grouping
group.facet=true // Facet counts to be number of groups instead of documents
group.field=Store // Groups results by the field "Store"
group.ngroups=true // Tells Solr to return the number of groups found
The number of groups found is what you would show to the user and use for paging, instead of the normal total count, which would be the total number of documents in the index.
Have you looked into field collapsing? It is new in Solr 3.3.
http://wiki.apache.org/solr/FieldCollapsing
What I did is I created another field that grouped the required fields in a single field and stored it, problem solved, so now I just group only on that field and I get the correct count.