Clément Renault 656a851830
Introduce the Transform struct transforming CSVs
This allows us to:
  - transform a CSV, a JSON or a JSON lines data type into the same
    Grenad x Obkv streamable data type and creates the new FieldsIdsMap.
  - Extract all the documents user ids in advance to be able to delete
    the existing documents before re-indexing them.
  - Keep the last documents with the same user id avoiding duplicates
    in the same request.
2020-10-24 13:37:38 +02:00

399 lines
14 KiB
Rust

use std::borrow::Cow;
use std::fs::File;
use std::io::{self, Read, Seek, SeekFrom};
use std::sync::mpsc::sync_channel;
use std::time::Instant;
use anyhow::Context;
use bstr::ByteSlice as _;
use flate2::read::GzDecoder;
use grenad::{Writer, Sorter, Merger, Reader, FileFuse, CompressionType};
use heed::types::ByteSlice;
use log::{debug, info, error};
use rayon::prelude::*;
use structopt::StructOpt;
use tempfile::tempfile;
use crate::Index;
use self::store::Store;
use self::merge_function::{
main_merge, word_docids_merge, words_pairs_proximities_docids_merge,
docid_word_positions_merge, documents_merge,
};
mod merge_function;
mod store;
mod transform;
#[derive(Debug, Clone, StructOpt)]
pub struct IndexerOpt {
/// The amount of documents to skip before printing
/// a log regarding the indexing advancement.
#[structopt(long, default_value = "1000000")] // 1m
log_every_n: usize,
/// MTBL max number of chunks in bytes.
#[structopt(long)]
max_nb_chunks: Option<usize>,
/// The maximum amount of memory to use for the MTBL buffer. It is recommended
/// to use something like 80%-90% of the available memory.
///
/// It is automatically split by the number of jobs e.g. if you use 7 jobs
/// and 7 GB of max memory, each thread will use a maximum of 1 GB.
#[structopt(long, default_value = "7516192768")] // 7 GB
max_memory: usize,
/// Size of the linked hash map cache when indexing.
/// The bigger it is, the faster the indexing is but the more memory it takes.
#[structopt(long, default_value = "500")]
linked_hash_map_size: usize,
/// The name of the compression algorithm to use when compressing intermediate
/// chunks during indexing documents.
///
/// Choosing a fast algorithm will make the indexing faster but may consume more memory.
#[structopt(long, default_value = "snappy", possible_values = &["snappy", "zlib", "lz4", "lz4hc", "zstd"])]
chunk_compression_type: CompressionType,
/// The level of compression of the chosen algorithm.
#[structopt(long, requires = "chunk-compression-type")]
chunk_compression_level: Option<u32>,
/// The number of bytes to remove from the begining of the chunks while reading/sorting
/// or merging them.
///
/// File fusing must only be enable on file systems that support the `FALLOC_FL_COLLAPSE_RANGE`,
/// (i.e. ext4 and XFS). File fusing will only work if the `enable-chunk-fusing` is set.
#[structopt(long, default_value = "4294967296")] // 4 GB
chunk_fusing_shrink_size: u64,
/// Enable the chunk fusing or not, this reduces the amount of disk used by a factor of 2.
#[structopt(long)]
enable_chunk_fusing: bool,
/// Number of parallel jobs for indexing, defaults to # of CPUs.
#[structopt(long)]
indexing_jobs: Option<usize>,
}
#[derive(Debug, Copy, Clone)]
enum WriteMethod {
Append,
GetMergePut,
}
type MergeFn = for<'a> fn(&[u8], &[Cow<'a, [u8]>]) -> anyhow::Result<Vec<u8>>;
fn create_writer(typ: CompressionType, level: Option<u32>, file: File) -> io::Result<Writer<File>> {
let mut builder = Writer::builder();
builder.compression_type(typ);
if let Some(level) = level {
builder.compression_level(level);
}
builder.build(file)
}
fn create_sorter(
merge: MergeFn,
chunk_compression_type: CompressionType,
chunk_compression_level: Option<u32>,
chunk_fusing_shrink_size: Option<u64>,
max_nb_chunks: Option<usize>,
max_memory: Option<usize>,
) -> Sorter<MergeFn>
{
let mut builder = Sorter::builder(merge);
if let Some(shrink_size) = chunk_fusing_shrink_size {
builder.file_fusing_shrink_size(shrink_size);
}
builder.chunk_compression_type(chunk_compression_type);
if let Some(level) = chunk_compression_level {
builder.chunk_compression_level(level);
}
if let Some(nb_chunks) = max_nb_chunks {
builder.max_nb_chunks(nb_chunks);
}
if let Some(memory) = max_memory {
builder.max_memory(memory);
}
builder.build()
}
fn writer_into_reader(writer: Writer<File>, shrink_size: Option<u64>) -> anyhow::Result<Reader<FileFuse>> {
let mut file = writer.into_inner()?;
file.seek(SeekFrom::Start(0))?;
let file = if let Some(shrink_size) = shrink_size {
FileFuse::builder().shrink_size(shrink_size).build(file)
} else {
FileFuse::new(file)
};
Reader::new(file).map_err(Into::into)
}
fn merge_readers(sources: Vec<Reader<FileFuse>>, merge: MergeFn) -> Merger<FileFuse, MergeFn> {
let mut builder = Merger::builder(merge);
builder.extend(sources);
builder.build()
}
fn merge_into_lmdb_database(
wtxn: &mut heed::RwTxn,
database: heed::PolyDatabase,
sources: Vec<Reader<FileFuse>>,
merge: MergeFn,
method: WriteMethod,
) -> anyhow::Result<()> {
debug!("Merging {} MTBL stores...", sources.len());
let before = Instant::now();
let merger = merge_readers(sources, merge);
let mut in_iter = merger.into_merge_iter()?;
match method {
WriteMethod::Append => {
let mut out_iter = database.iter_mut::<_, ByteSlice, ByteSlice>(wtxn)?;
while let Some((k, v)) = in_iter.next()? {
out_iter.append(k, v).with_context(|| format!("writing {:?} into LMDB", k.as_bstr()))?;
}
},
WriteMethod::GetMergePut => {
while let Some((k, v)) = in_iter.next()? {
match database.get::<_, ByteSlice, ByteSlice>(wtxn, k)? {
Some(old_val) => {
let vals = vec![Cow::Borrowed(old_val), Cow::Borrowed(v)];
let val = merge(k, &vals).expect("merge failed");
database.put::<_, ByteSlice, ByteSlice>(wtxn, k, &val)?
},
None => database.put::<_, ByteSlice, ByteSlice>(wtxn, k, v)?,
}
}
},
}
debug!("MTBL stores merged in {:.02?}!", before.elapsed());
Ok(())
}
fn write_into_lmdb_database(
wtxn: &mut heed::RwTxn,
database: heed::PolyDatabase,
mut reader: Reader<FileFuse>,
merge: MergeFn,
method: WriteMethod,
) -> anyhow::Result<()> {
debug!("Writing MTBL stores...");
let before = Instant::now();
match method {
WriteMethod::Append => {
let mut out_iter = database.iter_mut::<_, ByteSlice, ByteSlice>(wtxn)?;
while let Some((k, v)) = reader.next()? {
out_iter.append(k, v).with_context(|| format!("writing {:?} into LMDB", k.as_bstr()))?;
}
},
WriteMethod::GetMergePut => {
while let Some((k, v)) = reader.next()? {
match database.get::<_, ByteSlice, ByteSlice>(wtxn, k)? {
Some(old_val) => {
let vals = vec![Cow::Borrowed(old_val), Cow::Borrowed(v)];
let val = merge(k, &vals).expect("merge failed");
database.put::<_, ByteSlice, ByteSlice>(wtxn, k, &val)?
},
None => database.put::<_, ByteSlice, ByteSlice>(wtxn, k, v)?,
}
}
}
}
debug!("MTBL stores merged in {:.02?}!", before.elapsed());
Ok(())
}
fn csv_bytes_readers<'a>(
content: &'a [u8],
gzipped: bool,
count: usize,
) -> Vec<csv::Reader<Box<dyn Read + Send + 'a>>>
{
let mut readers = Vec::new();
for _ in 0..count {
let content = if gzipped {
Box::new(GzDecoder::new(content)) as Box<dyn Read + Send>
} else {
Box::new(content) as Box<dyn Read + Send>
};
let reader = csv::Reader::from_reader(content);
readers.push(reader);
}
readers
}
pub fn run<'a, F>(
env: &heed::Env,
index: &Index,
opt: &IndexerOpt,
content: &'a [u8],
gzipped: bool,
progress_callback: F,
) -> anyhow::Result<()>
where F: Fn(u32) + Sync + Send,
{
let jobs = opt.indexing_jobs.unwrap_or(0);
let pool = rayon::ThreadPoolBuilder::new().num_threads(jobs).build()?;
pool.install(|| run_intern(env, index, opt, content, gzipped, progress_callback))
}
fn run_intern<'a, F>(
env: &heed::Env,
index: &Index,
opt: &IndexerOpt,
content: &'a [u8],
gzipped: bool,
progress_callback: F,
) -> anyhow::Result<()>
where F: Fn(u32) + Sync + Send,
{
let before_indexing = Instant::now();
let num_threads = rayon::current_num_threads();
let linked_hash_map_size = opt.linked_hash_map_size;
let max_nb_chunks = opt.max_nb_chunks;
let max_memory_by_job = opt.max_memory / num_threads;
let chunk_compression_type = opt.chunk_compression_type;
let chunk_compression_level = opt.chunk_compression_level;
let log_every_n = opt.log_every_n;
let chunk_fusing_shrink_size = if opt.enable_chunk_fusing {
Some(opt.chunk_fusing_shrink_size)
} else {
None
};
let rtxn = env.read_txn()?;
let number_of_documents = index.number_of_documents(&rtxn)?;
drop(rtxn);
let readers = csv_bytes_readers(content, gzipped, num_threads)
.into_par_iter()
.enumerate()
.map(|(i, rdr)| {
let store = Store::new(
linked_hash_map_size,
max_nb_chunks,
Some(max_memory_by_job),
chunk_compression_type,
chunk_compression_level,
chunk_fusing_shrink_size,
)?;
let base_document_id = number_of_documents;
store.index_csv(rdr, base_document_id, i, num_threads, log_every_n, &progress_callback)
})
.collect::<Result<Vec<_>, _>>()?;
let mut main_readers = Vec::with_capacity(readers.len());
let mut word_docids_readers = Vec::with_capacity(readers.len());
let mut docid_word_positions_readers = Vec::with_capacity(readers.len());
let mut words_pairs_proximities_docids_readers = Vec::with_capacity(readers.len());
let mut documents_readers = Vec::with_capacity(readers.len());
readers.into_iter().for_each(|readers| {
main_readers.push(readers.main);
word_docids_readers.push(readers.word_docids);
docid_word_positions_readers.push(readers.docid_word_positions);
words_pairs_proximities_docids_readers.push(readers.words_pairs_proximities_docids);
documents_readers.push(readers.documents);
});
// This is the function that merge the readers
// by using the given merge function.
let merge_readers = move |readers, merge| {
let mut writer = tempfile().and_then(|f| {
create_writer(chunk_compression_type, chunk_compression_level, f)
})?;
let merger = merge_readers(readers, merge);
merger.write_into(&mut writer)?;
writer_into_reader(writer, chunk_fusing_shrink_size)
};
// The enum and the channel which is used to transfert
// the readers merges potentially done on another thread.
enum DatabaseType { Main, WordDocids, WordsPairsProximitiesDocids };
let (sender, receiver) = sync_channel(3);
debug!("Merging the main, word docids and words pairs proximity docids in parallel...");
rayon::spawn(move || {
vec![
(DatabaseType::Main, main_readers, main_merge as MergeFn),
(DatabaseType::WordDocids, word_docids_readers, word_docids_merge),
(
DatabaseType::WordsPairsProximitiesDocids,
words_pairs_proximities_docids_readers,
words_pairs_proximities_docids_merge,
),
]
.into_par_iter()
.for_each(|(dbtype, readers, merge)| {
let result = merge_readers(readers, merge);
if let Err(e) = sender.send((dbtype, result)) {
error!("sender error: {}", e);
}
});
});
let mut wtxn = env.write_txn()?;
let contains_documents = number_of_documents != 0;
let write_method = if contains_documents { WriteMethod::GetMergePut } else { WriteMethod::Append };
debug!("Writing the docid word positions into LMDB on disk...");
merge_into_lmdb_database(
&mut wtxn,
*index.docid_word_positions.as_polymorph(),
docid_word_positions_readers,
docid_word_positions_merge,
write_method
)?;
debug!("Writing the documents into LMDB on disk...");
merge_into_lmdb_database(
&mut wtxn,
*index.documents.as_polymorph(),
documents_readers,
documents_merge,
write_method
)?;
for (db_type, result) in receiver {
let content = result?;
match db_type {
DatabaseType::Main => {
debug!("Writing the main elements into LMDB on disk...");
write_into_lmdb_database(&mut wtxn, index.main, content, main_merge, write_method)?;
},
DatabaseType::WordDocids => {
debug!("Writing the words docids into LMDB on disk...");
let db = *index.word_docids.as_polymorph();
write_into_lmdb_database(&mut wtxn, db, content, word_docids_merge, write_method)?;
},
DatabaseType::WordsPairsProximitiesDocids => {
debug!("Writing the words pairs proximities docids into LMDB on disk...");
let db = *index.word_pair_proximity_docids.as_polymorph();
write_into_lmdb_database(
&mut wtxn,
db,
content,
words_pairs_proximities_docids_merge,
write_method,
)?;
},
}
}
wtxn.commit()?;
info!("Update processed in {:.02?}", before_indexing.elapsed());
Ok(())
}