It's seems like the underline index changed. Are those two documents in the same result set? Is it just one query? It's definitely curious, even if a commit happened search results are consistent in one searcher.
On Sun, 5 Dec 2021, 16:28 Sjoerd Smeets, <ssme...@gmail.com> wrote: > Hi all, > > I'm debugging the relevancy scores of my query and I see the following for > two documents hits. My question is, why is the idf score not the same for > both documents? This is Solr 6.6. > > Any guidance would be much appreciated. > > Thanks! > > *Doc1* > "71d72354eea23b9eae934ab616e8ce38de69d760": " > 104.994415 = sum of: > 104.994415 = sum of: > 82.89969 = weight(stemmed_data.timenote.narratives:remedi in 22470) > [SchemaSimilarity], result of: > 82.89969 = score(freq=9.0), computed as boost * idf * tf from: > 100.0 = boost > 0.87546873 = idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) > from: > *52 = n, number of documents containing term* > *125 = N, total number of documents with field* > 0.9469177 = tf, computed as freq / (freq + k1 * (1 - b + b * dl / > avgdl)) from: > 9.0 = freq, occurrences of term within document > 1.2 = k1, term saturation parameter > 0.75 = b, length normalization parameter > 12312.0 = dl, length of field (approximate) > 54179.03 = avgdl, average length of field > 22.09473 = weight(stemmed_data.timenote.matters:remedi in 22470) > [SchemaSimilarity], result of: > 22.09473 = score(freq=4.0), computed as boost * idf * tf from: > 10.0 = boost > 2.4308395 = idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) > from: > *9 = n, number of documents containing term* > *107 = N, total number of documents with field* > 0.9089341 = tf, computed as freq / (freq + k1 * (1 - b + b * dl / > avgdl)) from: > 4.0 = freq, occurrences of term within document > 1.2 = k1, term saturation parameter > 0.75 = b, length normalization parameter > 5656.0 = dl, length of field (approximate) > 50520.543 = avgdl, average length of field > 0.0 = FunctionQuery(int(s_integer_search.previews)), product of: > 0.0 = int(s_integer_search.previews)=0 > 1.0 = boost > 0.0 = FunctionQuery(int(s_integer_search.downloads)), product of: > 0.0 = int(s_integer_search.downloads)=0 > 1.0 = boost > " > > *Doc2* > "80302a1ecc44d1e556970ab96c25b1fd3328a854": " > 84.61461 = sum of: > 84.61461 = sum of: > 64.68881 = weight(stemmed_data.timenote.narratives:remedi in 0) > [SchemaSimilarity], result of: > 64.68881 = score(freq=493.0), computed as boost * idf * tf from: > 100.0 = boost > 0.65094686 = idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) > from: > *60 = n, number of documents containing term* > *115 = N, total number of documents with field* > 0.99376476 = tf, computed as freq / (freq + k1 * (1 - b + b * dl / > avgdl)) from: > 493.0 = freq, occurrences of term within document > 1.2 = k1, term saturation parameter > 0.75 = b, length normalization parameter > 229400.0 = dl, length of field (approximate) > 73913.91 = avgdl, average length of field > 19.9258 = weight(stemmed_data.timenote.matters:remedi in 0) > [SchemaSimilarity], result of: > 19.9258 = score(freq=340.0), computed as boost * idf * tf from: > 10.0 = boost > 2.0024805 = idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) > from: > *13 = n, number of documents containing term* > *99 = N, total number of documents with field* > 0.99505585 = tf, computed as freq / (freq + k1 * (1 - b + b * dl / > avgdl)) from: > 340.0 = freq, occurrences of term within document > 1.2 = k1, term saturation parameter > 0.75 = b, length normalization parameter > 147480.0 = dl, length of field (approximate) > 95534.95 = avgdl, average length of field > 0.0 = FunctionQuery(int(s_integer_search.previews)), product of: > 0.0 = int(s_integer_search.previews)=0 > 1.0 = boost > 0.0 = FunctionQuery(int(s_integer_search.downloads)), product of: > 0.0 = int(s_integer_search.downloads)=0 > 1.0 = boost > " >
