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https://issues.apache.org/jira/browse/SOLR-10377?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Munendra S N updated SOLR-10377:
--------------------------------
Status: Patch Available (was: Reopened)
> Improve readability of the explain output for JSON format
> ---------------------------------------------------------
>
> Key: SOLR-10377
> URL: https://issues.apache.org/jira/browse/SOLR-10377
> Project: Solr
> Issue Type: Improvement
> Reporter: Varun Thacker
> Priority: Minor
> Attachments: SOLR-10377.patch, Screenshot 2019-07-17 at 6.09.17
> PM.png, Screenshot 2019-07-17 at 6.09.27 PM.png
>
>
> Today when I ask solr for the debug query output In json with indent I get
> this:
> {code}
> 1: " 3.545981 = sum of: 3.545981 = weight(name:dns in 0) [SchemaSimilarity],
> result of: 3.545981 = score(doc=0,freq=1.0 = termFreq=1.0 ), product of:
> 2.3025851 = idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq +
> 0.5)) from: 2.0 = docFreq 24.0 = docCount 1.54 = tfNorm, computed as (freq *
> (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:
> 1.0 = termFreq=1.0 1.2 = parameter k1 0.75 = parameter b 7.0 = avgFieldLength
> 1.0 = fieldLength ",
> 2: " 7.4202514 = sum of: 7.4202514 = sum of: 2.7921112 = weight(name:domain
> in 1) [SchemaSimilarity], result of: 2.7921112 = score(doc=1,freq=1.0 =
> termFreq=1.0 ), product of: 2.3025851 = idf, computed as log(1 + (docCount -
> docFreq + 0.5) / (docFreq + 0.5)) from: 2.0 = docFreq 24.0 = docCount
> 1.2125984 = tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b *
> fieldLength / avgFieldLength)) from: 1.0 = termFreq=1.0 1.2 = parameter k1
> 0.75 = parameter b 7.0 = avgFieldLength 4.0 = fieldLength 2.7921112 =
> weight(name:name in 1) [SchemaSimilarity], result of: 2.7921112 =
> score(doc=1,freq=1.0 = termFreq=1.0 ), product of: 2.3025851 = idf, computed
> as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from: 2.0 = docFreq
> 24.0 = docCount 1.2125984 = tfNorm, computed as (freq * (k1 + 1)) / (freq +
> k1 * (1 - b + b * fieldLength / avgFieldLength)) from: 1.0 = termFreq=1.0 1.2
> = parameter k1 0.75 = parameter b 7.0 = avgFieldLength 4.0 = fieldLength
> 1.8360289 = weight(name:system in 1) [SchemaSimilarity], result of: 1.8360289
> = score(doc=1,freq=1.0 = termFreq=1.0 ), product of: 1.5141277 = idf,
> computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from: 5.0 =
> docFreq 24.0 = docCount 1.2125984 = tfNorm, computed as (freq * (k1 + 1)) /
> (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from: 1.0 =
> termFreq=1.0 1.2 = parameter k1 0.75 = parameter b 7.0 = avgFieldLength 4.0 =
> fieldLength "
> {code}
> When I run the same query with "wt=ruby" I get a much nicer output
> {code}
> '2'=>'
> 7.4202514 = sum of:
> 7.4202514 = sum of:
> 2.7921112 = weight(name:domain in 1) [SchemaSimilarity], result of:
> 2.7921112 = score(doc=1,freq=1.0 = termFreq=1.0
> ), product of:
> 2.3025851 = idf, computed as log(1 + (docCount - docFreq + 0.5) /
> (docFreq + 0.5)) from:
> 2.0 = docFreq
> 24.0 = docCount
> 1.2125984 = tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 -
> b + b * fieldLength / avgFieldLength)) from:
> 1.0 = termFreq=1.0
> 1.2 = parameter k1
> 0.75 = parameter b
> 7.0 = avgFieldLength
> 4.0 = fieldLength
> 2.7921112 = weight(name:name in 1) [SchemaSimilarity], result of:
> 2.7921112 = score(doc=1,freq=1.0 = termFreq=1.0
> ), product of:
> 2.3025851 = idf, computed as log(1 + (docCount - docFreq + 0.5) /
> (docFreq + 0.5)) from:
> 2.0 = docFreq
> 24.0 = docCount
> 1.2125984 = tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 -
> b + b * fieldLength / avgFieldLength)) from:
> 1.0 = termFreq=1.0
> 1.2 = parameter k1
> 0.75 = parameter b
> 7.0 = avgFieldLength
> 4.0 = fieldLength
> 1.8360289 = weight(name:system in 1) [SchemaSimilarity], result of:
> 1.8360289 = score(doc=1,freq=1.0 = termFreq=1.0
> ), product of:
> 1.5141277 = idf, computed as log(1 + (docCount - docFreq + 0.5) /
> (docFreq + 0.5)) from:
> 5.0 = docFreq
> 24.0 = docCount
> 1.2125984 = tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 -
> b + b * fieldLength / avgFieldLength)) from:
> 1.0 = termFreq=1.0
> 1.2 = parameter k1
> 0.75 = parameter b
> 7.0 = avgFieldLength
> 4.0 = fieldLength
> ',
> '1'=>'
> 3.545981 = sum of:
> 3.545981 = weight(name:dns in 0) [SchemaSimilarity], result of:
> 3.545981 = score(doc=0,freq=1.0 = termFreq=1.0
> ), product of:
> 2.3025851 = idf, computed as log(1 + (docCount - docFreq + 0.5) /
> (docFreq + 0.5)) from:
> 2.0 = docFreq
> 24.0 = docCount
> 1.54 = tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b
> * fieldLength / avgFieldLength)) from:
> 1.0 = termFreq=1.0
> 1.2 = parameter k1
> 0.75 = parameter b
> 7.0 = avgFieldLength
> 1.0 = fieldLength
> '}
> {code}
> Also the explain for the JSON output is not sorted by score
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