Lucene document score appears to be lost after search - lucene

In lucene 3.1 i have a large boolean query, that i execute like so:
IndexSearcher is = new IndexSearcher(myDir);
is.search(query, 10);
I get 10 results just fine, but they are sorted by docId, and contain no score information. All documentation i can find, says that lucene by default sorts by relevance/score but this is not the case for me. If I ask for explain, there is no score information, just "0.0". Funny thing is that if I execute the same query in Luke on the same index, i get a result sorted by score just fine, but I can't see how to get the scores to stay and be used for sorting when launched from app. So I believe the query is just fine, seeing how it works in Luke.
What am I doing wrong ? I have also tried setting is.setDefaultFielsSortScoring(true,true) but this makes no difference. I tried using TopScoreDocColletor with no success.

Look at Lucene scoring, particularly the query norm. If one of your weights is Float.MAX_VALUE everything else will be close enough to zero that it's smaller than machine precision.

Related

Elasticsearch much slower when returning all results

I have about 20,000 documents stored in elastic search, at about 200kb each.
I have a search which has 733 hits total, I'm running that takes about 50ms to complete when returning 10 results.
If I set the size to 1000 so that it returns all results, the search takes 3-5 seconds to return.
Normally I would see that this is because it has to continue searching until it finds all of them, which takes extra time. However when returning 10 results only, the search still says 733 hits in total, so it already knows which documents are to be returned!
Note that I am not returning the _source field here, all I want it the list of _ids back, so I can't imagine that it would have to read any more data from the disk, as all the _ids are surely stored in the indices anyway.
Am I missing something in the way this works?
(My _ids are guids that we use internally).
EDIT: Since posting I've re-indexed with two changes to the mapping:
Set _source to false, so now the actual documents aren't stored.
Changed the index for the field that I was searching on to be not_analyzed.
This solves the problem, now I'm getting all 733 _ids back in ~50ms. Not sure which change solved it though. I'll take one of them back out and re-index.
It will take that Time. Because it need to fetch all data from ES and calculate score for your query.
Try
1)set fields to not analyzed which you Don search in.
2)change the store type of ES from simplfs to mmaps.. ( mention "index.store.type:mmaps" in elasticsearch.yml..)
3)configure less shard as much possible.. Shard more must be equal to move on nodes you gonna use..

Querying Apache Solr based on score values

I am working on an image retrieval task. I have a dataset of wikipedia images with their textual description in xml files (1 xml file per image). I have indexed those xmls in Solr. Now while retrieving those, I want to maintain some threshold for Score values, so that docs with less score will not come in the result (because they are not of much importance). For example I want to retrieve all documents having similarity score greater than or equal to 2.0. I have already tried range queries like score:[2.0 TO *] but can't get it working. Does anyone have any idea how can I do that?
What's the motivation for wanting to do this? The reason I ask, is
score is a relative thing determined by Lucene based on your index
statistics. It is only meaningful for comparing the results of a
specific query with a specific instance of the index. In other words,
it isn't useful to filter on b/c there is no way of knowing what a
good cutoff value would be.
http://lucene.472066.n3.nabble.com/score-filter-td493438.html
Also, take a look here - http://wiki.apache.org/lucene-java/ScoresAsPercentages
So, in general it's bad to cut off by some value, because you'll never know which threshold value is best. In good query it could be score=2, in bad query score=0.5, etc.
These two links should explain you why you DONT want to do it.
P.S. If you still want to do it take a look here - https://stackoverflow.com/a/15765203/2663985
P.P.S. I recommend you to fix your search queries, so they will search better with high precision (http://en.wikipedia.org/wiki/Precision_and_recall)

Lucene Paging with search

Hello I am currently using Lucene 4.6.1
In my design I need to be able to search and page possibly many results, so i have some general questions for optimization.
First in the "search(query q, int n)" What is the goal of the variable "n" , Is "n" different from ".totalHits()" ? How should this number be chosen and with what specifications?
Second, it seems that there are two general algorithms for paging. I can either use "searchAfter" or process the "ScoreDoc[]" given a page size.
Currently what way do most people recommend, and what are the design ideas that are required?
searchAfter can be used for efficient "deep paging".
A tutorial on using it with Solr
http://heliosearch.org/solr/paging-and-deep-paging/
The int passed to search is the maximum number of hits the search will retrieve. totalHits, from the TopDocs is the total number of hits for the query. It may be more or less than the value passed in.
Not clear to me what you mean by processing the ScoreDoc array. searchAfter is specifically intended to be used for pagination. Use it.

understanding the relationship between boosting a document in lucene at index time and its corresponding score at search time

When indexing, I boost certain documents, but they do not appear on the top of the list of retrieved documents. I looked at the score of those documents, and somehow, the score of the documents retrieved is always NaN.
What is the relationship between a boost of a document at index time and its score at retrieve time? I thought these would be correlated, and further, I thought I would get a wide range of scores in my scoredocs, not just NaN. If you can shed some light on this I would be grateful.
I have read http://lucene.apache.org/java/2_3_2/api/org/apache/lucene/search/Similarity.html
and cant figure out what is missing.
Here is the simple boosting code:
if (myCondition)
{
myDocument.SetBoost(1.1f);
}
myIndexWriter.AddDocument(document);
I'm gonna go on a wild guess here since you havent provide a sample of you search code, but a common reason why the score of retreived docs is NaN is because you use a Sort. When sorting, most of the time the score of the documents is not used, and therefore disabled by default.
If you use a Sort for your search, and want the score, check the method setDefaultFieldSortScoring of the IndexSearcher class. This method allows you to enable scoring the documents in a search that uses a Sort.
http://lucene.apache.org/java/2_9_4/api/all/org/apache/lucene/search/IndexSearcher.html#setDefaultFieldSortScoring(boolean, boolean)

Youtube API problem - when searching for playlists, start-index does not work past 100

I have been trying to get the full list of playlists matching a certain keyword. I have discovered however that using start-index past 100 brings the same set of results as using start-index=1. It does not matter what the max-results parameter is - still the same results. The total results returned however is way above 100, thus it cannot be that the query returned only 100 results.
What might the problem be? Is it a quota of some sort or any other authentication restriction?
As an example - the queries bring the same result set, whether you use start-index=1, or start-index=101, or start-index = 201 etc:
http://gdata.youtube.com/feeds/api/playlists/snippets?q=%22Jan+Smit+Laura%22&max-results=50&start-index=1&v=2
Any idea will be much appreciated!
Regards
Christo
I made an interface for my site, and the way I avoided this problem is to do a query for a large number, then store the results. Let your web page then break up the results and present them however is needed.
For example, if someone wants to do a search of over 100 videos, do the search and collect the results, but only present them with the first group, say 10. Then when the person wants to see the next ten, you get them from the list you stored, rather than doing a new query.
Not only does this make paging faster, but it cuts down on the constant queries to the YouTube database.
Hope this makes sense and helps.