Finalize the LMDB indexing design

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Kerollmops 2020-07-01 22:45:43 +02:00
parent 2ae3f40971
commit 7e7440c431
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@ -2,22 +2,25 @@ use std::collections::hash_map::Entry;
use std::collections::{HashMap, BTreeSet}; use std::collections::{HashMap, BTreeSet};
use std::convert::{TryFrom, TryInto}; use std::convert::{TryFrom, TryInto};
use std::hash::{Hash, BuildHasher}; use std::hash::{Hash, BuildHasher};
use std::io; use std::{cmp, io};
use std::path::PathBuf; use std::iter::FromIterator;
use std::sync::atomic::{AtomicUsize, Ordering}; use std::path::{Path, PathBuf};
use std::time::Instant;
use anyhow::Context; use anyhow::{ensure, Context};
use cow_utils::CowUtils; use fst::{Streamer, set::OpBuilder};
use fst::Streamer;
use heed::EnvOpenOptions;
use heed::types::*; use heed::types::*;
use heed::{Env, EnvOpenOptions};
use rayon::prelude::*;
use roaring::RoaringBitmap; use roaring::RoaringBitmap;
use slice_group_by::StrGroupBy; use slice_group_by::StrGroupBy;
use structopt::StructOpt; use structopt::StructOpt;
use tempfile::TempDir;
use mega_mini_indexer::cache::ArcCache; use mega_mini_indexer::cache::ArcCache;
use mega_mini_indexer::{BEU32, Index, DocumentId, FastMap4}; use mega_mini_indexer::{BEU32, Index, DocumentId, FastMap4};
const ONE_MILLION: u32 = 1_000_000;
const MAX_POSITION: usize = 1000; const MAX_POSITION: usize = 1000;
const MAX_ATTRIBUTES: usize = u32::max_value() as usize / MAX_POSITION; const MAX_ATTRIBUTES: usize = u32::max_value() as usize / MAX_POSITION;
@ -25,8 +28,6 @@ const MAX_ATTRIBUTES: usize = u32::max_value() as usize / MAX_POSITION;
#[global_allocator] #[global_allocator]
static ALLOC: jemallocator::Jemalloc = jemallocator::Jemalloc; static ALLOC: jemallocator::Jemalloc = jemallocator::Jemalloc;
static ID_GENERATOR: AtomicUsize = AtomicUsize::new(0); // AtomicU32 ?
pub fn simple_alphanumeric_tokens(string: &str) -> impl Iterator<Item = &str> { pub fn simple_alphanumeric_tokens(string: &str) -> impl Iterator<Item = &str> {
let is_alphanumeric = |s: &&str| s.chars().next().map_or(false, char::is_alphanumeric); let is_alphanumeric = |s: &&str| s.chars().next().map_or(false, char::is_alphanumeric);
string.linear_group_by_key(|c| c.is_alphanumeric()).filter(is_alphanumeric) string.linear_group_by_key(|c| c.is_alphanumeric()).filter(is_alphanumeric)
@ -95,12 +96,19 @@ fn index_csv<R: io::Read>(
writer.write_byte_record(headers.as_byte_record())?; writer.write_byte_record(headers.as_byte_record())?;
let headers = writer.into_inner()?; let headers = writer.into_inner()?;
let mut document_id = 0usize;
let mut before = Instant::now();
let mut document = csv::StringRecord::new(); let mut document = csv::StringRecord::new();
while rdr.read_record(&mut document)? { while rdr.read_record(&mut document)? {
let document_id = ID_GENERATOR.fetch_add(1, Ordering::SeqCst); document_id = document_id + 1;
let document_id = DocumentId::try_from(document_id).context("Generated id is too big")?; let document_id = DocumentId::try_from(document_id).context("Generated id is too big")?;
if thread_index == 0 && document_id % ONE_MILLION == 0 {
eprintln!("Document {}m just processed ({:.02?} elapsed).", document_id / ONE_MILLION, before.elapsed());
before = Instant::now();
}
for (attr, content) in document.iter().enumerate().take(MAX_ATTRIBUTES) { for (attr, content) in document.iter().enumerate().take(MAX_ATTRIBUTES) {
for (pos, word) in simple_alphanumeric_tokens(&content).enumerate().take(MAX_POSITION) { for (pos, word) in simple_alphanumeric_tokens(&content).enumerate().take(MAX_POSITION) {
if !word.is_empty() && word.len() < 500 { // LMDB limits if !word.is_empty() && word.len() < 500 { // LMDB limits
@ -142,12 +150,14 @@ fn index_csv<R: io::Read>(
} }
} }
if thread_index == 0 {
// We write the document in the database. // We write the document in the database.
let mut writer = csv::WriterBuilder::new().has_headers(false).from_writer(Vec::new()); let mut writer = csv::WriterBuilder::new().has_headers(false).from_writer(Vec::new());
writer.write_byte_record(document.as_byte_record())?; writer.write_byte_record(document.as_byte_record())?;
let document = writer.into_inner()?; let document = writer.into_inner()?;
index.documents.put(wtxn, &BEU32::new(document_id), &document)?; index.documents.put(wtxn, &BEU32::new(document_id), &document)?;
} }
}
put_evicted_into_heed(wtxn, index, words_cache)?; put_evicted_into_heed(wtxn, index, words_cache)?;
@ -207,37 +217,134 @@ fn compute_words_attributes_docids(wtxn: &mut heed::RwTxn, index: &Index) -> any
Ok(()) Ok(())
} }
fn main() -> anyhow::Result<()> { fn merge_databases(
let opt = Opt::from_args(); others: Vec<(usize, Option<TempDir>, Env, Index)>,
wtxn: &mut heed::RwTxn,
index: &Index,
) -> anyhow::Result<()>
{
eprintln!("Merging the temporary databases...");
std::fs::create_dir_all(&opt.database)?; let mut fsts = Vec::new();
for (_i, _dir, env, oindex) in others {
let rtxn = env.read_txn()?;
// merge and check the headers are equal
let headers = oindex.headers(&rtxn)?.context("A database is missing the headers")?;
match index.headers(wtxn)? {
Some(h) => ensure!(h == headers, "headers are not equal"),
None => index.put_headers(wtxn, &headers)?,
};
// retrieve the FSTs to merge them together in one run.
let fst = oindex.fst(&rtxn)?.context("A database is missing its FST")?;
let fst = fst.map_data(|s| s.to_vec())?;
fsts.push(fst);
// merge the words positions
for result in oindex.word_positions.iter(&rtxn)? {
let (word, pos) = result?;
index.word_positions.put(wtxn, word, &pos)?;
}
// merge the documents ids by word and position
for result in oindex.word_position_docids.iter(&rtxn)? {
let (key, docids) = result?;
index.word_position_docids.put(wtxn, key, &docids)?;
}
// merge the documents ids by word and attribute
for result in oindex.word_attribute_docids.iter(&rtxn)? {
let (key, docids) = result?;
index.word_attribute_docids.put(wtxn, key, &docids)?;
}
for result in oindex.documents.iter(&rtxn)? {
let (id, content) = result?;
index.documents.put(wtxn, &id, &content)?;
}
}
// Merge all the FSTs to create a final one and write it in the final database.
if let Some(fst) = index.fst(wtxn)? {
let fst = fst.map_data(|s| s.to_vec())?;
fsts.push(fst);
}
let builder = OpBuilder::from_iter(&fsts);
let op = builder.r#union();
let mut builder = fst::set::SetBuilder::memory();
builder.extend_stream(op)?;
let fst = builder.into_set();
index.put_fst(wtxn, &fst)?;
Ok(())
}
fn open_env_index(path: impl AsRef<Path>) -> anyhow::Result<(Env, Index)> {
let env = EnvOpenOptions::new() let env = EnvOpenOptions::new()
.map_size(100 * 1024 * 1024 * 1024) // 100 GB .map_size(100 * 1024 * 1024 * 1024) // 100 GB
.max_readers(10) .max_readers(10)
.max_dbs(10) .max_dbs(10)
.open(opt.database)?; .open(path)?;
let index = Index::new(&env)?; let index = Index::new(&env)?;
let mut wtxn = env.write_txn()?; Ok((env, index))
}
match opt.csv_file { fn main() -> anyhow::Result<()> {
let opt = Opt::from_args();
std::fs::create_dir_all(&opt.database)?;
match &opt.csv_file {
Some(path) => { Some(path) => {
let rdr = csv::Reader::from_path(path)?; let num_threads = rayon::current_num_threads();
index_csv(&mut wtxn, rdr, &index, 1, 0)?;
}, let result: Result<Vec<_>, anyhow::Error> =
None => { (0..num_threads).into_par_iter().map(|i| {
let rdr = csv::Reader::from_reader(io::stdin()); let (dir, env, index) = if i == 0 {
index_csv(&mut wtxn, rdr, &index, 1, 0)?; let (env, index) = open_env_index(&opt.database)?;
} (None, env, index)
} else {
let dir = tempfile::tempdir()?;
let (env, index) = open_env_index(&dir)?;
(Some(dir), env, index)
}; };
let mut wtxn = env.write_txn()?;
let rdr = csv::Reader::from_path(path)?;
index_csv(&mut wtxn, rdr, &index, num_threads, i)?;
wtxn.commit()?;
Ok((i, dir, env, index))
})
.collect();
let mut parts = result?;
parts.sort_unstable_by_key(|&(i, ..)| cmp::Reverse(i));
let (_, _, env, index) = parts.pop().context("missing base database")?;
// TODO we can merge databases that are ready to be merged
// into the final one, without having to wait for all of them.
// TODO we can reuse an already existing database instead of creating a new one
// it would be even better to use the first one as it contains the documents.
let mut wtxn = env.write_txn()?;
merge_databases(parts, &mut wtxn, &index)?;
compute_words_attributes_docids(&mut wtxn, &index)?; compute_words_attributes_docids(&mut wtxn, &index)?;
let count = index.documents.len(&wtxn)?; let count = index.documents.len(&wtxn)?;
wtxn.commit()?; wtxn.commit()?;
eprintln!("Wrote {} documents into LMDB", count); eprintln!("Wrote {} documents into LMDB", count);
},
None => todo!("support for stdin CSV while indexing in parallel"),
};
Ok(()) Ok(())
} }