Introduce an infos binary to fetch stats

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Kerollmops 2020-08-17 15:15:37 +02:00 committed by Clément Renault
parent 8806fcd545
commit 962bad3cea
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src/bin/infos.rs Normal file
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use std::path::PathBuf;
use std::{str, io};
use heed::EnvOpenOptions;
use milli::Index;
use structopt::StructOpt;
#[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,
}
}
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, opt.database)?;
let rtxn = env.read_txn()?;
match opt.command {
Command::MostCommonWords { limit } => most_common_words(&index, &rtxn, limit),
}
}
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 (bytes, postings) = result?;
let (word, _position) = bytes.split_at(bytes.len() - 4);
let word = str::from_utf8(word)?;
match prev.as_mut() {
Some((prev_word, freq, docids)) if prev_word == word => {
*freq += docids.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()?)
}