use std::path::PathBuf; use std::{str, io}; use anyhow::Context; use heed::EnvOpenOptions; use milli::Index; use structopt::StructOpt; use Command::*; #[cfg(target_os = "linux")] #[global_allocator] static ALLOC: jemallocator::Jemalloc = jemallocator::Jemalloc; #[derive(Debug, StructOpt)] #[structopt(name = "milli-info", about = "A stats crawler for milli.")] struct Opt { /// The database path where the database is located. /// It is created if it doesn't already exist. #[structopt(long = "db", parse(from_os_str))] database: PathBuf, /// The maximum size the database can take on disk. It is recommended to specify /// the whole disk space (value must be a multiple of a page size). #[structopt(long = "db-size", default_value = "107374182400")] // 100 GB database_size: usize, /// Verbose mode (-v, -vv, -vvv, etc.) #[structopt(short, long, parse(from_occurrences))] verbose: usize, #[structopt(subcommand)] command: Command, } #[derive(Debug, StructOpt)] enum Command { /// Outputs a CSV of the most frequent words of this index. /// /// `word` are displayed and ordered by frequency. /// `document_frequency` defines the number of documents which contains the word. /// `frequency` defines the number times the word appears in all the documents. MostCommonWords { /// The maximum number of frequencies to return. #[structopt(default_value = "10")] limit: usize, }, /// Outputs a CSV with the frequencies of the specified words. /// /// Read the documentation of the `most-common-words` command /// for more information about the CSV headers. WordsFrequencies { /// The words you want to retrieve frequencies of. words: Vec, }, /// Outputs a CSV with the biggest entries of the database. BiggestValueSizes { /// The maximum number of sizes to return. #[structopt(default_value = "10")] limit: usize, }, /// Outputs a CSV with the document ids for all the positions of the given words. WordPositionDocIds { /// Show the value entirely, not just the debug version. #[structopt(long)] full_display: bool, /// The words you want to display the values of. words: Vec, }, /// Outputs a CSV with all the positions of the given words. WordPositions { /// Show the value entirely, not just the debug version. #[structopt(long)] full_display: bool, /// The words you want to display the values of. words: Vec, }, } fn main() -> anyhow::Result<()> { let opt = Opt::from_args(); stderrlog::new() .verbosity(opt.verbose) .show_level(false) .timestamp(stderrlog::Timestamp::Off) .init()?; let env = EnvOpenOptions::new() .map_size(opt.database_size) .max_dbs(10) .open(&opt.database)?; // Open the LMDB database. let index = Index::new(&env)?; let rtxn = env.read_txn()?; match opt.command { MostCommonWords { limit } => most_common_words(&index, &rtxn, limit), WordsFrequencies { words } => words_frequencies(&index, &rtxn, words), BiggestValueSizes { limit } => biggest_value_sizes(&index, &rtxn, limit), WordPositionDocIds { full_display, words } => word_position_doc_ids(&index, &rtxn, !full_display, words), WordPositions { full_display, words } => word_positions(&index, &rtxn, !full_display, words), } } fn most_common_words(index: &Index, rtxn: &heed::RoTxn, limit: usize) -> anyhow::Result<()> { use std::collections::BinaryHeap; use std::cmp::Reverse; use roaring::RoaringBitmap; let mut heap = BinaryHeap::with_capacity(limit + 1); let mut prev = None as Option<(String, u64, RoaringBitmap)>; for result in index.word_position_docids.iter(rtxn)? { if limit == 0 { break } let ((word, _position), postings) = result?; match prev.as_mut() { Some((prev_word, freq, docids)) if prev_word == word => { *freq += postings.len(); docids.union_with(&postings); }, Some((prev_word, freq, docids)) => { heap.push(Reverse((docids.len(), *freq, prev_word.to_string()))); if heap.len() > limit { heap.pop(); } prev = Some((word.to_string(), postings.len(), postings)) }, None => prev = Some((word.to_string(), postings.len(), postings)), } } if let Some((prev_word, freq, docids)) = prev { heap.push(Reverse((docids.len(), freq, prev_word.to_string()))); if heap.len() > limit { heap.pop(); } } let stdout = io::stdout(); let mut wtr = csv::Writer::from_writer(stdout.lock()); wtr.write_record(&["word", "document_frequency", "frequency"])?; for Reverse((document_frequency, frequency, word)) in heap.into_sorted_vec() { wtr.write_record(&[word, document_frequency.to_string(), frequency.to_string()])?; } Ok(wtr.flush()?) } fn words_frequencies(index: &Index, rtxn: &heed::RoTxn, words: Vec) -> anyhow::Result<()> { use heed::BytesDecode; use heed::types::ByteSlice; use milli::heed_codec::{RoaringBitmapCodec, StrBEU32Codec}; use roaring::RoaringBitmap; let stdout = io::stdout(); let mut wtr = csv::Writer::from_writer(stdout.lock()); wtr.write_record(&["word", "document_frequency", "frequency"])?; for word in words { let mut document_frequency = RoaringBitmap::new(); let mut frequency = 0; let db = index.word_position_docids.as_polymorph(); for result in db.prefix_iter::<_, ByteSlice, RoaringBitmapCodec>(rtxn, word.as_bytes())? { let (bytes, postings) = result?; let (w, _position) = StrBEU32Codec::bytes_decode(bytes).unwrap(); // if the word is not exactly the word we requested then it means // we found a word that *starts with* the requested word and we must stop. if word != w { break } document_frequency.union_with(&postings); frequency += postings.len(); } wtr.write_record(&[word, document_frequency.len().to_string(), frequency.to_string()])?; } Ok(wtr.flush()?) } fn biggest_value_sizes(index: &Index, rtxn: &heed::RoTxn, limit: usize) -> anyhow::Result<()> { use std::cmp::Reverse; use std::collections::BinaryHeap; use heed::BytesDecode; use heed::types::{Str, ByteSlice}; use milli::heed_codec::StrBEU32Codec; let main_name = "main"; let word_positions_name = "word_positions"; let word_position_docids_name = "word_position_docids"; let word_four_positions_docids_name = "word_four_positions_docids"; let word_attribute_docids_name = "word_attribute_docids"; let mut heap = BinaryHeap::with_capacity(limit + 1); if limit > 0 { if let Some(fst) = index.fst(rtxn)? { heap.push(Reverse((fst.as_fst().as_bytes().len(), format!("words-fst"), main_name))); if heap.len() > limit { heap.pop(); } } if let Some(documents) = index.main.get::<_, Str, ByteSlice>(rtxn, "documents")? { heap.push(Reverse((documents.len(), format!("documents"), main_name))); if heap.len() > limit { heap.pop(); } } if let Some(documents_ids) = index.main.get::<_, Str, ByteSlice>(rtxn, "documents-ids")? { heap.push(Reverse((documents_ids.len(), format!("documents-ids"), main_name))); if heap.len() > limit { heap.pop(); } } for result in index.word_positions.as_polymorph().iter::<_, Str, ByteSlice>(rtxn)? { let (word, value) = result?; heap.push(Reverse((value.len(), word.to_string(), word_positions_name))); if heap.len() > limit { heap.pop(); } } for result in index.word_position_docids.as_polymorph().iter::<_, ByteSlice, ByteSlice>(rtxn)? { let (key_bytes, value) = result?; let (word, position) = StrBEU32Codec::bytes_decode(key_bytes).unwrap(); let key = format!("{} {}", word, position); heap.push(Reverse((value.len(), key, word_position_docids_name))); if heap.len() > limit { heap.pop(); } } for result in index.word_four_positions_docids.as_polymorph().iter::<_, ByteSlice, ByteSlice>(rtxn)? { let (key_bytes, value) = result?; let (word, lower_position) = StrBEU32Codec::bytes_decode(key_bytes).unwrap(); let key = format!("{} {}..{}", word, lower_position, lower_position + 4); heap.push(Reverse((value.len(), key, word_four_positions_docids_name))); if heap.len() > limit { heap.pop(); } } for result in index.word_attribute_docids.as_polymorph().iter::<_, ByteSlice, ByteSlice>(rtxn)? { let (key_bytes, value) = result?; let (word, attribute) = StrBEU32Codec::bytes_decode(key_bytes).unwrap(); let key = format!("{} {}", word, attribute); heap.push(Reverse((value.len(), key, word_attribute_docids_name))); if heap.len() > limit { heap.pop(); } } } let stdout = io::stdout(); let mut wtr = csv::Writer::from_writer(stdout.lock()); wtr.write_record(&["database_name", "key_name", "size"])?; for Reverse((size, key_name, database_name)) in heap.into_sorted_vec() { wtr.write_record(&[database_name.to_string(), key_name, size.to_string()])?; } Ok(wtr.flush()?) } fn word_position_doc_ids(index: &Index, rtxn: &heed::RoTxn, debug: bool, words: Vec) -> anyhow::Result<()> { use heed::BytesDecode; use heed::types::ByteSlice; use milli::heed_codec::{RoaringBitmapCodec, StrBEU32Codec}; let stdout = io::stdout(); let mut wtr = csv::Writer::from_writer(stdout.lock()); wtr.write_record(&["word", "position", "document_ids"])?; let mut non_debug = Vec::new(); for word in words { let db = index.word_position_docids.as_polymorph(); for result in db.prefix_iter::<_, ByteSlice, RoaringBitmapCodec>(rtxn, word.as_bytes())? { let (bytes, postings) = result?; let (w, position) = StrBEU32Codec::bytes_decode(bytes).unwrap(); // if the word is not exactly the word we requested then it means // we found a word that *starts with* the requested word and we must stop. if word != w { break } let postings_string = if debug { format!("{:?}", postings) } else { non_debug.clear(); non_debug.extend(postings); format!("{:?}", non_debug) }; wtr.write_record(&[&word, &position.to_string(), &postings_string])?; } } Ok(wtr.flush()?) } fn word_positions(index: &Index, rtxn: &heed::RoTxn, debug: bool, words: Vec) -> anyhow::Result<()> { let stdout = io::stdout(); let mut wtr = csv::Writer::from_writer(stdout.lock()); wtr.write_record(&["word", "positions"])?; let mut non_debug = Vec::new(); for word in words { let postings = index.word_positions.get(rtxn, &word)? .with_context(|| format!("could not find word {:?}", &word))?; let postings_string = if debug { format!("{:?}", postings) } else { non_debug.clear(); non_debug.extend(postings); format!("{:?}", non_debug) }; wtr.write_record(&[word, postings_string])?; } Ok(wtr.flush()?) }