Can someone explain with example that how Solr function query is used.
I could not find any concrete example which shows the result difference with function queries and without function queries.
I want something with example URL and what is shows in response result.
A function query is a query that invokes a function on one (or more) of the fields available. You add a function query if the value you have in a field has to be processed to get the value you want - just as you'd do in a mathematical sense.
Showing "the difference between a query with function queries and without" isn't really possible, as they don't do the same thing. You pick one (or both) depending on what you need.
An adopted example from the reference manual - Lets imagine we have a set of documents that describe users, and these users have two fields - mails_read and mails_received. To get anyone that has read less than 50% of their mails, we can apply a filter query as a function (with the frange query parser) (fq here means filter query - the frange is what makes it a function query):
fq={!frange l=0 u=0.5}div(mails_read,mails_received)
Otherwise we'd be limited to receive those who just had read a specific range of emails or that had received a specific range of emails - or we'd have to index a value that kept the updated value for mails_read / mails_received each time we updated the document (which is a perfectly valid strategy, and usually more efficient).
Another example is to use a function query for boosting documents, and the most common one is to boost by recency (i.e. that a more recent document receives a larger boost):
bf=recip(ms(NOW/HOUR,mydatefield),3.16e-11,1,1)
This applies the recip function to the difference (expressed in milliseconds) between the mydatefield field and the current hour.
recip: Performs a reciprocal function with recip(x,m,a,b) implementing a/(m*x+b) where m,a,b are constants, and x is any arbitrarily complex function.
Yet another fine use case is to use the special _val_ field - if you query against this magic field with a function, the value returned by the function will be used as the score of the document (instead of affecting it through boosting or limiting the resulting set of documents as a query).
_val_:"div(popularity, price)"
.. would give the score of the document based on the result of the division (what the values represent is up to you).
Related
I'm attempting to query solr for documents, given a basic schema with the following field names, data types irrelevant:
I'm attempting to match documents that match at least one of the following:
occupation, name, age, gender but i want to OR them together
How do you OR together many terms, and enforce the document to match at least one?
This seems to be failing: +(name:Sarah age:24 occupation:doctor gender:male)
How do you convert a boolean expression into solr query syntax? I can't figure out the syntax with + and - and the default operator for OR.
Still I don't get your requirement but you just need to query like:
+(age:24 OR gender:male)
Or if you want data for multiple value in same field with OR condition like.
i.e. You get data of age:24 and age:25 both.
+(age:24 OR age:25 OR gender:male)
Then you can:
+(age:(24 25) OR gender:male)
If it is't your requirement, then let me know.
If you want to make it as simple as possible for the client, just go for the dismax[1] or edismax[2] query parser.
Specifically you can configure a request parameter called "qf" :
"The qf parameter introduces a list of fields, each of which is assigned a boost factor to increase or decrease that particular field’s importance in the query. For example, the query below:
qf=fieldOne^2.3 fieldTwo fieldThree^0.4
assigns fieldOne a boost of 2.3, leaves fieldTwo with the default boost (because no boost factor is specified), and fieldThree a boost of 0.4.
These boost factors make matches in fieldOne much more significant than matches in fieldTwo, which in turn are much more significant than matches in fieldThree." from the wiki
Then you can just pass a free text query, and it will be searched in the fields you specified, giving also different importance to each one, if necessary.
[1] https://lucene.apache.org/solr/guide/6_6/the-dismax-query-parser.html
[2] https://lucene.apache.org/solr/guide/6_6/the-extended-dismax-query-parser.html
I implementing Solr search using an API. When I call it using the parameters as, "Chillout Lounge", it returns me the collection which are same/similar to the string "Chillout Lounge".
But when I search for "Chillout Lounge Box", it returns me results which don't have any of these three words.(in the DB there are values which have these 3 values, but they are not returned.)
According to me, Solr uses Fuzzy search, but when it is done it should return me some values, which will have at least one these value.
Or what could be the possible changes I should to my schema.XML, such that is would give me proper values.
First of all - "Fuzzy search" is a feature you'll have to ask for (by using ~ in standard Lucene query syntax).
If you're talking about regular searches, you can use q.op to select which operator to use. q.op=AND will make sure that all the terms match, while q.op=OR will make any document that contain at least one of the terms be returned. As long as you aren't using fq for this, the documents that match more terms should be scored higher (as the score will add up across multiple terms), and thus, be shown higher in the result set.
You can use the debug query feature in the web interface to see scores for each term for a document, and find out why the document was returned at all. If the document doesn't match any terms, it shouldn't be returned, unless you're asking for all documents to be returned.
Be aware that the analyzer chain defined for the field you're searching might affect what's considered a match and not.
You'll have to add a proper example to get a more detailed answer.
Is it possible to boost a document on the indexing stage depending on the field value?
I'm indexing a text field pulled from the database. I would like to boost results that are shorter over the longer ones. So the value of boost should depend on the length of the text field.
This is needed to alter the standard SOLR behavior that in my case tends to return documents with multiple matches first.
Considering I have a field that stores the length of the document, the equivalent in the query of what I need at indexing would be:
q={!boost b=sqrt(length)}text:abcd
Example:
I have two items in the DB:
ABCDEBCE
ABCD
I always want to get ABCD first for the 'BC' query even though the other item contains the search query twice.
The other solution to the problem would be ability to 'switch off' the feature that scores multiple matches higher at query time. Don't know if that is possible either...
Doing this at index time is important as the hardware I run the SOLR on is not too powerful and trying to boost on query time returns with OutOfMemory Exception. (Even If I could work around that increasing memory for java I prefer to be on the safe side and implement the index the most efficient way possible.)
Yes and no - but how you do it depends on how you're indexing your documents.
As far as I know there's no way of resolving this only on the solr server side at the moment.
If you're using the regular XML based interface to submit documents, let the code that generates the submitted XML add boost=".." values to the field or to the document depending on the length of the text field.
You can check upon DIH Special Commands which has a $docBoost command
$docBoost : Boost the current doc. The value can be a number or the
toString of a number
However, there seems no $fieldBoost Command.
For you case though, if you are using DefaultSimilarity, shorter fields are boosted higher then longer fields in the Score calculation.
You can surely implement your own Simiarity class with a changed TF (Term Frequency) and LengthNorm Calculation as your needs.
I'd like to submit a query to SOLR/Lucene, plus a list of document IDs. From the query, I'd like the usual top-N scored results, but I'd also like to get the scores for the named documents... no matter how low they are.
Can anyone think of an easy/supported way to do this in a single index scan, where the scores for the 'added' (non-ranking/pinned-for-inclusion) docs are comparable/same-scaled as those for the top-N results? (Patching SOLR with specialized classes would be OK; I figure that's what I may have to do if there's no existing support.)
Or failing that, could it be simulated with a followup query, ideally in a way that the named-document scores could be scaled to be roughly comparable to the top-N for the reference query?
Alternatively -- and perhaps as good or better for my intended use -- could I make a single request against a SOLR/Lucene index which includes M (with M=2 or more) distinct queries, and return the results that are in the top-N for any of the M queries, and for every result include its score against all M of the distinct queries?
(Even in my above formulation, the list of documents that I want scored along with a new query will typically have been the results from a prior query.)
Solutions or even just fragments of possible approaches appreciated!
I am not sure if I understand properly what you want to achieve but wouldn't a simple
q: (somequery) OR id: (1 OR 2 OR 4)
be enough?
If you would want both parts to be boosted by the same scale (I am not sure if this isn't the default behaviour of Solr) you would want to use dismax or edismax and your query would change to something like:
q: (somequery)^10 OR id: (1 OR 2 OR 4)^10
You would then have both the elements defined by the IDs and the query results scored the same way.
To self-answer, reporting what I've found since posting...
One clumsy option is the explainOther parameter, which takes another query. (This query could be a OR list of interesting document IDs.) The response will then include a full scoring explanation for documents which match this other query. explainOther only has effect when combined with the also-required debugQuery parameter.
All that debug/explain information is overkill for the need, but may be useful, or the code paths that implement it might provide a guide to making a hypothetical new more narrowly-focused 'scoreOther' option.
Another option would be to make use of pseudo-field calculated using the query() function to report how any set of results score on some other query/queries. So if for example the original document set was the top-N from query_A, and then those are the exact documents that you also want to score against query_B, you would execute query_A again with a reporting-field …&fl=bscore:query({!dismax v="query_B"})&…. Then the document's scores against query_B would be included in the output (as bscore).
Finally, the result-grouping functionality can be used both collect the top-N for one query and scores for lesser documents intersecting with other queries in one go. For example, if querying for query_B and adding …&group=true&group.query=query_B&group.query=query_A&…, you'll get back groups that satisfy query_B (ranked by query_B), and that satisfy both query_B and query_A (but again ranked by query_B). This could be mixed with the functional field above to get the scores by another query (like query_A) as well.
However, all groups will share the same sort order (from either the master query or something specified by a group.sort parameter), so it's not currently possible (SOLR-4.0.0-beta) to get several top-N results according to different scorings, just the top-Ns according to one scoring, limited by certain groups. (There's a comment in the source code suggesting alternate sorts per group may be envisioned as a future capability.)
I currently have a SOLR query which uses the query (q), query fields (qf) and phrase fields (pf) to retrieve the results I want. An example is:
/solr/select
?q=superbowl
&qf=title^3+headline^2+intro+fulltext
&pf=title^3+headline^2+intro+fulltext
&fl=id,title,ts_modified,score
&debugQuery=true
The idea is that the title and headline of the "main item" give the best indication of what the result is "about", but the intro and fulltext provides some input too. Ie, imagine a collection of links, where the collection itself has metadata (what it's a collection of), but each link has it's own data (title of the link, synopsis, etc). If we search for "superbowl", the most relevant results are the ones with "superbowl" in the collection metadata, the least relevant results are those with "superbowl" in just the synopsis of one of the links... but they're all valid results.
What I'm trying to do is add a boost to the relevancy score so that the most recent results float towards the top, but retaining title,headline,intro,fulltext as part of the formula. A recent result with the search string in the collection metadata would be more relevant than one with it only in the links metadata... but that "links only" recent result might be more relevant than a very old result with the search string in the collection metadata. (I hope that's somewhat clear).
The problem is that I can't figure out how to combine the boost function documented on the SOLR site with the use of the qf/pf fields. Specifically...
From the SOLR site, something like the following works to boost the results by date:
/solr/select
?q={!boost%20b=$dateboost%20v=$qq}
&dateboost=ord(ts_modified)
&qq=superbowl
&fl=ts_modified,score
&debugQuery=true
However, I can't figure out how to combine that query with the use of qf and pf. Any suggestions would be more than welcome.
Thanks to danben's response, I was able to come up with the following:
/solr/select
?q={!boost%20b=$dateboost%20v=$qq%20defType=dismax}
&dateboost=ord(ts_modified)
&qq=superbowl
&qf=title^3+headline^2+intro^2+fulltext
&pf=title^3+headline^2+intro^2+fulltext
&fl=ts_modifieds,score
&debugQuery=true
It looks like the actual problems I was having were:
I left spaces in the q param instead of escaping them (%20) when copy/pasting
I didn't include the defType=dismax in my q param, so that it would pay attention to the qf/pf parameters
Check out http://wiki.apache.org/solr/SolrRelevancyFAQ#How_can_I_boost_the_score_of_newer_documents
This is based on the ms function, which returns the difference in milliseconds between two timestamps / dates, and ReciprocalFloatFunction which increases as the value passed decreases.
Since you are using the DisMaxRequestHandler, you may need to specify your query using the bq/bf parameters. From http://lucene.apache.org/solr/api/org/apache/solr/handler/DisMaxRequestHandler.html:
bq - (Boost Query) a raw lucene query that will be included in the
users query to influence the score. If
this is a BooleanQuery with a default
boost (1.0f), then the individual
clauses will be added directly to the
main query. Otherwise, the query will
be included as is. This param can be
specified multiple times, and the
boosts are are additive. NOTE: the
behaviour listed above is only in
effect if a single bq paramter is
specified. Hence you can disable it by
specifying an additional, blank, bq
parameter.
bf - (Boost Functions) functions (with optional boosts) that will be
included in the users query to
influence the score. Format is:
"funcA(arg1,arg2)^1.2
funcB(arg3,arg4)^2.2". NOTE:
Whitespace is not allowed in the
function arguments. This param can be
specified multiple times, and the
functions are additive.
Here is a nice article about Date-boosting Solr search results:
http://www.metaltoad.com/blog/date-boosting-solr-drupal-search-results
In Drupal this can be simply achieved by the following code:
using Apachesolr module
/**
* Implements hook_apachesolr_query_alter().
*/
function hook_search_apachesolr_query_alter(DrupalSolrQueryInterface $query) {
$query->addParam('bf', array('freshness' =>
'recip(abs(ms(NOW/HOUR,dm_field_date)),3.16e-11,1,.1)'
));
}