Hi team, Lately I have been using some ranking using blockjoin querries on nested documents. I haved added *score=total *to the queries which actually rings scores to the parent. When trying to understand results I see somwhow enabeling debug info only return first or best match as you can see below. Below results matchrd 17 children but only displays best match. Is it possible to see the full debug information?
Thanks Regards, Sergio Maroto <str name="8180777"> 239.1634 = sum of: 236.98985 = sum of: 236.98985 = Score based on *17 child docs in range from 80573436 to 80573514, best match:* 224.95201 = sum of: 224.5116 = sum of: 0.35355338 = weight(FunctionListFreeTextNS:finance in 315379) [SchemaSimilarity], result of: 0.35355338 = score(freq=1.0), product of: 1.0 = idf, computed as log((docCount+1)/(docFreq+1)) + 1 from: 34343 = docFreq, number of documents containing term 259843 = docCount, total number of documents with field 1.0 = tf(freq=1.0), with freq of: 1.0 = freq, occurrences of term within document 0.35355338 = fieldNorm 224.15805 = sum of: 7.071068 = weight(FunctionListFreeTextNS:finance in 315379) [SchemaSimilarity], result of: 7.071068 = score(freq=1.0), product of: 20.0 = boost 1.0 = idf, computed as log((docCount+1)/(docFreq+1)) + 1 from: 34343 = docFreq, number of documents containing term 259843 = docCount, total number of documents with field 1.0 = tf(freq=1.0), with freq of: 1.0 = freq, occurrences of term within document 0.35355338 = fieldNorm 14.353563 = weight(CurrentNSD:T in 315379) [SchemaSimilarity], result of: 14.353563 = score(freq=1.0), computed as boost * idf * tf from: 20.0 = boost 1.578892 = idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from: 7128118 = n, number of documents containing term 34568376 = N, total number of documents with field 0.45454544 = tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from: 1.0 = freq, occurrences of term within document 1.2 = k1, term saturation parameter 0.75 = b, length normalization parameter 1.0 = dl, length of field 1.0 = avgdl, average length of field 2.7334156 = weight(PrimaryNS:T in 315379) [SchemaSimilarity], result of: 2.7334156 = score(freq=1.0), computed as boost * idf * tf from: 20.0 = boost 0.30067572 = idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from: 22841134 = n, number of documents containing term 30853147 = N, total number of documents with field 0.45454544 = tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from: 1.0 = freq, occurrences of term within document 1.2 = k1, term saturation parameter 0.75 = b, length normalization parameter 1.0 = dl, length of field 1.0 = avgdl, average length of field 200.0 = sum of: 200.0 = JobBucketND:[0 TO 3]^200.0 0.44041252 = weight(type_level:job in 315379) [SchemaSimilarity], result of: 0.44041252 = score(freq=1.0), computed as boost * idf * tf from: 0.9689076 = idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from: 30853147 = n, number of documents containing term 81300026 = N, total number of documents with field 0.45454544 = tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from: 1.0 = freq, occurrences of term within document 1.2 = k1, term saturation parameter 0.75 = b, length normalization parameter 1.0 = dl, length of field 1.0 = avgdl, average length of field 2.173555 = sum of: 1.0 = sum of: 1.0 = *:* 1.173555 = weight(type_level:parent in 315400) [SchemaSimilarity], result of: 1.173555 = score(freq=1.0), computed as boost * idf * tf from: 2.5818212 = idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from: 6149219 = n, number of documents containing term 81300026 = N, total number of documents with field 0.45454544 = tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from: 1.0 = freq, occurrences of term within document 1.2 = k1, term saturation parameter 0.75 = b, length normalization parameter 1.0 = dl, length of field 1.0 = avgdl, average length of field </ str>
