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Introduce the words pairs proximities stats info subcommand
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@ -88,6 +88,10 @@ enum Command {
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/// Outputs the average number of documents for each words pair.
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AverageNumberOfDocumentByWordPairProximity,
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/// Outputs some statistics about the words pairs proximities
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/// (median, quartiles, percentiles, min, max).
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WordPairProximityStats,
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/// Outputs the size in bytes of the specified database.
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SizeOfDatabase {
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#[structopt(possible_values = DATABASE_NAMES)]
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@ -153,7 +157,8 @@ fn main() -> anyhow::Result<()> {
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SizeOfDatabase { database } => size_of_database(&index, &rtxn, &database),
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AverageNumberOfDocumentByWordPairProximity => {
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average_number_of_document_by_word_pair_proximity(&index, &rtxn)
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}
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},
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WordPairProximityStats => word_pair_proximity_stats(&index, &rtxn),
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WordPairProximitiesDocids { full_display, word1, word2 } => {
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word_pair_proximities_docids(&index, &rtxn, !full_display, word1, word2)
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},
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@ -392,24 +397,61 @@ fn average_number_of_document_by_word_pair_proximity(
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use heed::types::DecodeIgnore;
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use milli::RoaringBitmapCodec;
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let mut values_length = Vec::new();
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let mut values_length_sum = 0;
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let mut count = 0;
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let db = index.word_pair_proximity_docids.as_polymorph();
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for result in db.iter::<_, DecodeIgnore, RoaringBitmapCodec>(rtxn)? {
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let ((), val) = result?;
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values_length.push(val.len() as u32);
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values_length_sum += val.len() as u64;
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count += 1;
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}
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let values_length_sum = values_length.into_iter().map(|c| c as usize).sum::<usize>() as f64;
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let values_length_sum = values_length_sum as f64;
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let count = count as f64;
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println!("average number of documents by words pairs proximities: {}", values_length_sum / count);
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Ok(())
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}
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fn word_pair_proximity_stats(index: &Index, rtxn: &heed::RoTxn) -> anyhow::Result<()> {
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use heed::types::DecodeIgnore;
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use milli::RoaringBitmapCodec;
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let mut values_length = Vec::new();
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let db = index.word_pair_proximity_docids.as_polymorph();
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for result in db.iter::<_, DecodeIgnore, RoaringBitmapCodec>(rtxn)? {
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let ((), val) = result?;
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values_length.push(val.len() as u32);
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}
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values_length.sort_unstable();
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let median = values_length.get(values_length.len() / 2).unwrap_or(&0);
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let first_quartile = values_length.get(values_length.len() / 4).unwrap_or(&0);
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let third_quartile = values_length.get(values_length.len() / 4 * 3).unwrap_or(&0);
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let ninety_percentile = values_length.get(values_length.len() / 100 * 90).unwrap_or(&0);
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let ninety_five_percentile = values_length.get(values_length.len() / 100 * 95).unwrap_or(&0);
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let ninety_nine_percentile = values_length.get(values_length.len() / 100 * 99).unwrap_or(&0);
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let minimum = values_length.first().unwrap_or(&0);
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let maximum = values_length.last().unwrap_or(&0);
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let count = values_length.len();
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println!("words pairs proximities stats");
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println!("\tnumber of proximity pairs: {}", count);
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println!("\tfirst quartile: {}", first_quartile);
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println!("\tmedian: {}", median);
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println!("\tthird quartile: {}", third_quartile);
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println!("\t90th percentile: {}", ninety_percentile);
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println!("\t95th percentile: {}", ninety_five_percentile);
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println!("\t99th percentile: {}", ninety_nine_percentile);
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println!("\tminimum: {}", minimum);
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println!("\tmaximum: {}", maximum);
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Ok(())
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}
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fn word_pair_proximities_docids(
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index: &Index,
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rtxn: &heed::RoTxn,
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