meilisearch/milli/src/update/index_documents/transform.rs

675 lines
29 KiB
Rust

use std::borrow::Cow;
use std::collections::hash_map::Entry;
use std::collections::{HashMap, HashSet};
use std::fs::File;
use std::io::{Read, Seek, SeekFrom};
use fxhash::FxHashMap;
use heed::RoTxn;
use itertools::Itertools;
use obkv::{KvReader, KvWriter};
use roaring::RoaringBitmap;
use serde_json::Value;
use smartstring::SmartString;
use super::helpers::{create_sorter, create_writer, keep_latest_obkv, merge_obkvs, MergeFn};
use super::{IndexDocumentsMethod, IndexerConfig};
use crate::documents::{DocumentsBatchIndex, EnrichedDocument, EnrichedDocumentsBatchReader};
use crate::error::{Error, InternalError, UserError};
use crate::index::db_name;
use crate::update::{AvailableDocumentsIds, UpdateIndexingStep};
use crate::{
ExternalDocumentsIds, FieldDistribution, FieldId, FieldIdMapMissingEntry, FieldsIdsMap, Index,
Result, BEU32,
};
pub struct TransformOutput {
pub primary_key: String,
pub fields_ids_map: FieldsIdsMap,
pub field_distribution: FieldDistribution,
pub external_documents_ids: ExternalDocumentsIds<'static>,
pub new_documents_ids: RoaringBitmap,
pub replaced_documents_ids: RoaringBitmap,
pub documents_count: usize,
pub original_documents: File,
pub flattened_documents: File,
}
/// Extract the external ids, deduplicate and compute the new internal documents ids
/// and fields ids, writing all the documents under their internal ids into a final file.
///
/// Outputs the new `FieldsIdsMap`, the new `UsersIdsDocumentsIds` map, the new documents ids,
/// the replaced documents ids, the number of documents in this update and the file
/// containing all those documents.
pub struct Transform<'a, 'i> {
pub index: &'i Index,
fields_ids_map: FieldsIdsMap,
indexer_settings: &'a IndexerConfig,
pub autogenerate_docids: bool,
pub index_documents_method: IndexDocumentsMethod,
available_documents_ids: AvailableDocumentsIds,
original_sorter: grenad::Sorter<MergeFn>,
flattened_sorter: grenad::Sorter<MergeFn>,
replaced_documents_ids: RoaringBitmap,
new_documents_ids: RoaringBitmap,
// To increase the cache locality and decrease the heap usage we use compact smartstring.
new_external_documents_ids_builder: FxHashMap<SmartString<smartstring::Compact>, u64>,
documents_count: usize,
}
/// Create a mapping between the field ids found in the document batch and the one that were
/// already present in the index.
///
/// If new fields are present in the addition, they are added to the index field ids map.
fn create_fields_mapping(
index_field_map: &mut FieldsIdsMap,
batch_field_map: &DocumentsBatchIndex,
) -> Result<HashMap<FieldId, FieldId>> {
batch_field_map
.iter()
// we sort by id here to ensure a deterministic mapping of the fields, that preserves
// the original ordering.
.sorted_by_key(|(&id, _)| id)
.map(|(field, name)| match index_field_map.id(&name) {
Some(id) => Ok((*field, id)),
None => index_field_map
.insert(&name)
.ok_or(Error::UserError(UserError::AttributeLimitReached))
.map(|id| (*field, id)),
})
.collect()
}
impl<'a, 'i> Transform<'a, 'i> {
pub fn new(
wtxn: &mut heed::RwTxn,
index: &'i Index,
indexer_settings: &'a IndexerConfig,
index_documents_method: IndexDocumentsMethod,
autogenerate_docids: bool,
) -> Result<Self> {
// We must choose the appropriate merge function for when two or more documents
// with the same user id must be merged or fully replaced in the same batch.
let merge_function = match index_documents_method {
IndexDocumentsMethod::ReplaceDocuments => keep_latest_obkv,
IndexDocumentsMethod::UpdateDocuments => merge_obkvs,
};
// We initialize the sorter with the user indexing settings.
let original_sorter = create_sorter(
grenad::SortAlgorithm::Stable,
merge_function,
indexer_settings.chunk_compression_type,
indexer_settings.chunk_compression_level,
indexer_settings.max_nb_chunks,
indexer_settings.max_memory.map(|mem| mem / 2),
);
// We initialize the sorter with the user indexing settings.
let flattened_sorter = create_sorter(
grenad::SortAlgorithm::Stable,
merge_function,
indexer_settings.chunk_compression_type,
indexer_settings.chunk_compression_level,
indexer_settings.max_nb_chunks,
indexer_settings.max_memory.map(|mem| mem / 2),
);
let documents_ids = index.documents_ids(wtxn)?;
let soft_deleted_documents_ids = index.soft_deleted_documents_ids(wtxn)?;
Ok(Transform {
index,
fields_ids_map: index.fields_ids_map(wtxn)?,
indexer_settings,
autogenerate_docids,
available_documents_ids: AvailableDocumentsIds::from_documents_ids(
&documents_ids,
&soft_deleted_documents_ids,
),
original_sorter,
flattened_sorter,
index_documents_method,
replaced_documents_ids: RoaringBitmap::new(),
new_documents_ids: RoaringBitmap::new(),
new_external_documents_ids_builder: FxHashMap::default(),
documents_count: 0,
})
}
pub fn read_documents<R, F>(
&mut self,
reader: EnrichedDocumentsBatchReader<R>,
wtxn: &mut heed::RwTxn,
progress_callback: F,
) -> Result<usize>
where
R: Read + Seek,
F: Fn(UpdateIndexingStep) + Sync,
{
let (mut cursor, fields_index) = reader.into_cursor_and_fields_index();
let external_documents_ids = self.index.external_documents_ids(wtxn)?;
let mapping = create_fields_mapping(&mut self.fields_ids_map, &fields_index)?;
let primary_key = cursor.primary_key().to_string();
let primary_key_id =
self.fields_ids_map.insert(&primary_key).ok_or(UserError::AttributeLimitReached)?;
let mut obkv_buffer = Vec::new();
let mut documents_count = 0;
let mut docid_buffer: Vec<u8> = Vec::new();
let mut field_buffer: Vec<(u16, Cow<[u8]>)> = Vec::new();
while let Some(enriched_document) = cursor.next_enriched_document()? {
let EnrichedDocument { document, document_id } = enriched_document;
// drop_and_reuse is called instead of .clear() to communicate to the compiler that field_buffer
// does not keep references from the cursor between loop iterations
let mut field_buffer_cache = drop_and_reuse(field_buffer);
if self.indexer_settings.log_every_n.map_or(false, |len| documents_count % len == 0) {
progress_callback(UpdateIndexingStep::RemapDocumentAddition {
documents_seen: documents_count,
});
}
// When the document id has been auto-generated by the `enrich_documents_batch`
// we must insert this document id into the remaped document.
let external_id = document_id.value();
if document_id.is_generated() {
serde_json::to_writer(&mut docid_buffer, external_id)
.map_err(InternalError::SerdeJson)?;
field_buffer_cache.push((primary_key_id, Cow::from(&docid_buffer)));
}
for (k, v) in document.iter() {
let mapped_id =
*mapping.get(&k).ok_or(InternalError::FieldIdMappingMissingEntry { key: k })?;
field_buffer_cache.push((mapped_id, Cow::from(v)));
}
// Insertion in a obkv need to be done with keys ordered. For now they are ordered
// according to the document addition key order, so we sort it according to the
// fieldids map keys order.
field_buffer_cache.sort_unstable_by(|(f1, _), (f2, _)| f1.cmp(&f2));
// Build the new obkv document.
let mut writer = obkv::KvWriter::new(&mut obkv_buffer);
for (k, v) in field_buffer_cache.iter() {
writer.insert(*k, v)?;
}
let mut original_docid = None;
let docid =
match self.new_external_documents_ids_builder.entry(external_id.clone().into()) {
Entry::Occupied(entry) => *entry.get() as u32,
Entry::Vacant(entry) => {
// If the document was already in the db we mark it as a replaced document.
// It'll be deleted later. We keep its original docid to insert it in the grenad.
if let Some(docid) = external_documents_ids.get(entry.key()) {
self.replaced_documents_ids.insert(docid);
original_docid = Some(docid);
}
let docid = self
.available_documents_ids
.next()
.ok_or(UserError::DocumentLimitReached)?;
entry.insert(docid as u64);
docid
}
};
let mut skip_insertion = false;
if let Some(original_docid) = original_docid {
let original_key = BEU32::new(original_docid);
let base_obkv = self
.index
.documents
.remap_data_type::<heed::types::ByteSlice>()
.get(wtxn, &original_key)?
.ok_or(InternalError::DatabaseMissingEntry {
db_name: db_name::DOCUMENTS,
key: None,
})?;
// we check if the two documents are exactly equal. If it's the case we can skip this document entirely
if base_obkv == obkv_buffer {
// we're not replacing anything
self.replaced_documents_ids.remove(original_docid);
// and we need to put back the original id as it was before
self.new_external_documents_ids_builder.remove(&*external_id);
skip_insertion = true;
} else {
// we associate the base document with the new key, everything will get merged later.
self.original_sorter.insert(&docid.to_be_bytes(), base_obkv)?;
match self.flatten_from_fields_ids_map(KvReader::new(&base_obkv))? {
Some(buffer) => {
self.flattened_sorter.insert(docid.to_be_bytes(), &buffer)?
}
None => self.flattened_sorter.insert(docid.to_be_bytes(), base_obkv)?,
}
}
}
if !skip_insertion {
self.new_documents_ids.insert(docid);
// We use the extracted/generated user id as the key for this document.
self.original_sorter.insert(&docid.to_be_bytes(), obkv_buffer.clone())?;
match self.flatten_from_fields_ids_map(KvReader::new(&obkv_buffer))? {
Some(buffer) => self.flattened_sorter.insert(docid.to_be_bytes(), &buffer)?,
None => {
self.flattened_sorter.insert(docid.to_be_bytes(), obkv_buffer.clone())?
}
}
}
documents_count += 1;
progress_callback(UpdateIndexingStep::RemapDocumentAddition {
documents_seen: documents_count,
});
field_buffer = drop_and_reuse(field_buffer_cache);
docid_buffer.clear();
obkv_buffer.clear();
}
progress_callback(UpdateIndexingStep::RemapDocumentAddition {
documents_seen: documents_count,
});
self.index.put_fields_ids_map(wtxn, &self.fields_ids_map)?;
self.index.put_primary_key(wtxn, &primary_key)?;
self.documents_count += documents_count;
// Now that we have a valid sorter that contains the user id and the obkv we
// give it to the last transforming function which returns the TransformOutput.
Ok(documents_count)
}
// Flatten a document from the fields ids map contained in self and insert the new
// created fields. Returns `None` if the document doesn't need to be flattened.
fn flatten_from_fields_ids_map(&mut self, obkv: KvReader<FieldId>) -> Result<Option<Vec<u8>>> {
if obkv
.iter()
.all(|(_, value)| !json_depth_checker::should_flatten_from_unchecked_slice(value))
{
return Ok(None);
}
// store the keys and values the original obkv + the flattened json
// We first extract all the key+value out of the obkv. If a value is not nested
// we keep a reference on its value. If the value is nested we'll get its value
// as an owned `Vec<u8>` after flattening it.
let mut key_value: Vec<(FieldId, Cow<[u8]>)> = Vec::new();
// the object we're going to use to store the fields that need to be flattened.
let mut doc = serde_json::Map::new();
// we recreate a json containing only the fields that needs to be flattened.
// all the raw values get inserted directly in the `key_value` vec.
for (key, value) in obkv.iter() {
if json_depth_checker::should_flatten_from_unchecked_slice(value) {
let key = self.fields_ids_map.name(key).ok_or(FieldIdMapMissingEntry::FieldId {
field_id: key,
process: "Flatten from fields ids map.",
})?;
let value = serde_json::from_slice::<Value>(value)
.map_err(crate::error::InternalError::SerdeJson)?;
doc.insert(key.to_string(), value);
} else {
key_value.push((key, value.into()));
}
}
let flattened = flatten_serde_json::flatten(&doc);
// Once we have the flattened version we insert all the new generated fields_ids
// (if any) in the fields ids map and serialize the value.
for (key, value) in flattened.into_iter() {
let fid = self.fields_ids_map.insert(&key).ok_or(UserError::AttributeLimitReached)?;
let value = serde_json::to_vec(&value).map_err(InternalError::SerdeJson)?;
key_value.push((fid, value.into()));
}
// we sort the key. If there was a conflict between the obkv and the new generated value the
// keys will be consecutive.
key_value.sort_unstable_by_key(|(key, _)| *key);
let mut buffer = Vec::new();
Self::create_obkv_from_key_value(&mut key_value, &mut buffer)?;
Ok(Some(buffer))
}
/// Generate an obkv from a slice of key / value sorted by key.
fn create_obkv_from_key_value(
key_value: &mut [(FieldId, Cow<[u8]>)],
output_buffer: &mut Vec<u8>,
) -> Result<()> {
debug_assert!(
key_value.windows(2).all(|vec| vec[0].0 <= vec[1].0),
"The slice of key / value pair must be sorted."
);
output_buffer.clear();
let mut writer = KvWriter::new(output_buffer);
let mut skip_next_value = false;
for things in key_value.windows(2) {
if skip_next_value {
skip_next_value = false;
continue;
}
let (key1, value1) = &things[0];
let (key2, value2) = &things[1];
// now we're going to look for conflicts between the keys. For example the following documents would cause a conflict:
// { "doggo.name": "jean", "doggo": { "name": "paul" } }
// we should find a first "doggo.name" from the obkv and a second one from the flattening.
// but we must generate the following document:
// { "doggo.name": ["jean", "paul"] }
// thus we're going to merge the value from the obkv and the flattened document in a single array and skip the next
// iteration.
if key1 == key2 {
skip_next_value = true;
let value1 = serde_json::from_slice(value1)
.map_err(crate::error::InternalError::SerdeJson)?;
let value2 = serde_json::from_slice(value2)
.map_err(crate::error::InternalError::SerdeJson)?;
let value = match (value1, value2) {
(Value::Array(mut left), Value::Array(mut right)) => {
left.append(&mut right);
Value::Array(left)
}
(Value::Array(mut array), value) | (value, Value::Array(mut array)) => {
array.push(value);
Value::Array(array)
}
(left, right) => Value::Array(vec![left, right]),
};
let value = serde_json::to_vec(&value).map_err(InternalError::SerdeJson)?;
writer.insert(*key1, value)?;
} else {
writer.insert(*key1, value1)?;
}
}
if !skip_next_value {
// the unwrap is safe here, we know there was at least one value in the document
let (key, value) = key_value.last().unwrap();
writer.insert(*key, value)?;
}
Ok(())
}
fn remove_deleted_documents_from_field_distribution(
&self,
rtxn: &RoTxn,
field_distribution: &mut FieldDistribution,
) -> Result<()> {
for deleted_docid in self.replaced_documents_ids.iter() {
let obkv = self.index.documents.get(rtxn, &BEU32::new(deleted_docid))?.ok_or(
InternalError::DatabaseMissingEntry { db_name: db_name::DOCUMENTS, key: None },
)?;
for (key, _) in obkv.iter() {
let name =
self.fields_ids_map.name(key).ok_or(FieldIdMapMissingEntry::FieldId {
field_id: key,
process: "Computing field distribution in transform.",
})?;
// We checked that the document was in the db earlier. If we can't find it it means
// there is an inconsistency between the field distribution and the field id map.
let field =
field_distribution.get_mut(name).ok_or(FieldIdMapMissingEntry::FieldId {
field_id: key,
process: "Accessing field distribution in transform.",
})?;
*field -= 1;
if *field == 0 {
// since we were able to get the field right before it's safe to unwrap here
field_distribution.remove(name).unwrap();
}
}
}
Ok(())
}
/// Generate the `TransformOutput` based on the given sorter that can be generated from any
/// format like CSV, JSON or JSON stream. This sorter must contain a key that is the document
/// id for the user side and the value must be an obkv where keys are valid fields ids.
pub(crate) fn output_from_sorter<F>(
self,
wtxn: &mut heed::RwTxn,
progress_callback: F,
) -> Result<TransformOutput>
where
F: Fn(UpdateIndexingStep) + Sync,
{
let primary_key = self
.index
.primary_key(&wtxn)?
.ok_or(Error::UserError(UserError::MissingPrimaryKey))?
.to_string();
let mut external_documents_ids = self.index.external_documents_ids(wtxn)?;
// We create a final writer to write the new documents in order from the sorter.
let mut writer = create_writer(
self.indexer_settings.chunk_compression_type,
self.indexer_settings.chunk_compression_level,
tempfile::tempfile()?,
);
// To compute the field distribution we need to;
// 1. Remove all the deleted documents from the field distribution
// 2. Add all the new documents to the field distribution
let mut field_distribution = self.index.field_distribution(wtxn)?;
self.remove_deleted_documents_from_field_distribution(wtxn, &mut field_distribution)?;
// Here we are going to do the document count + field distribution + `write_into_stream_writer`
let mut iter = self.original_sorter.into_stream_merger_iter()?;
// used only for the callback
let mut documents_count = 0;
while let Some((key, val)) = iter.next()? {
// send a callback to show at which step we are
documents_count += 1;
progress_callback(UpdateIndexingStep::ComputeIdsAndMergeDocuments {
documents_seen: documents_count,
total_documents: self.documents_count,
});
// We increment all the field of the current document in the field distribution.
let obkv = KvReader::new(val);
for (key, _) in obkv.iter() {
let name =
self.fields_ids_map.name(key).ok_or(FieldIdMapMissingEntry::FieldId {
field_id: key,
process: "Computing field distribution in transform.",
})?;
*field_distribution.entry(name.to_string()).or_insert(0) += 1;
}
writer.insert(key, val)?;
}
let mut original_documents = writer.into_inner()?;
// We then extract the file and reset the seek to be able to read it again.
original_documents.seek(SeekFrom::Start(0))?;
// We create a final writer to write the new documents in order from the sorter.
let mut writer = create_writer(
self.indexer_settings.chunk_compression_type,
self.indexer_settings.chunk_compression_level,
tempfile::tempfile()?,
);
// Once we have written all the documents into the final sorter, we write the documents
// into this writer, extract the file and reset the seek to be able to read it again.
self.flattened_sorter.write_into_stream_writer(&mut writer)?;
let mut flattened_documents = writer.into_inner()?;
flattened_documents.seek(SeekFrom::Start(0))?;
let mut new_external_documents_ids_builder: Vec<_> =
self.new_external_documents_ids_builder.into_iter().collect();
new_external_documents_ids_builder
.sort_unstable_by(|(left, _), (right, _)| left.cmp(&right));
let mut fst_new_external_documents_ids_builder = fst::MapBuilder::memory();
new_external_documents_ids_builder.into_iter().try_for_each(|(key, value)| {
fst_new_external_documents_ids_builder.insert(key, value)
})?;
let new_external_documents_ids = fst_new_external_documents_ids_builder.into_map();
external_documents_ids.insert_ids(&new_external_documents_ids)?;
Ok(TransformOutput {
primary_key,
fields_ids_map: self.fields_ids_map,
field_distribution,
external_documents_ids: external_documents_ids.into_static(),
new_documents_ids: self.new_documents_ids,
replaced_documents_ids: self.replaced_documents_ids,
documents_count: self.documents_count,
original_documents,
flattened_documents,
})
}
/// Returns a `TransformOutput` with a file that contains the documents of the index
/// with the attributes reordered accordingly to the `FieldsIdsMap` given as argument.
// TODO this can be done in parallel by using the rayon `ThreadPool`.
pub fn remap_index_documents(
self,
wtxn: &mut heed::RwTxn,
old_fields_ids_map: FieldsIdsMap,
mut new_fields_ids_map: FieldsIdsMap,
) -> Result<TransformOutput> {
// There already has been a document addition, the primary key should be set by now.
let primary_key =
self.index.primary_key(wtxn)?.ok_or(UserError::MissingPrimaryKey)?.to_string();
let field_distribution = self.index.field_distribution(wtxn)?;
let external_documents_ids = self.index.external_documents_ids(wtxn)?;
let documents_ids = self.index.documents_ids(wtxn)?;
let documents_count = documents_ids.len() as usize;
// We create a final writer to write the new documents in order from the sorter.
let mut original_writer = create_writer(
self.indexer_settings.chunk_compression_type,
self.indexer_settings.chunk_compression_level,
tempfile::tempfile()?,
);
// We create a final writer to write the new documents in order from the sorter.
let mut flattened_writer = create_writer(
self.indexer_settings.chunk_compression_type,
self.indexer_settings.chunk_compression_level,
tempfile::tempfile()?,
);
let mut obkv_buffer = Vec::new();
for result in self.index.documents.iter(wtxn)? {
let (docid, obkv) = result?;
let docid = docid.get();
obkv_buffer.clear();
let mut obkv_writer = obkv::KvWriter::<_, FieldId>::new(&mut obkv_buffer);
// We iterate over the new `FieldsIdsMap` ids in order and construct the new obkv.
for (id, name) in new_fields_ids_map.iter() {
if let Some(val) = old_fields_ids_map.id(name).and_then(|id| obkv.get(id)) {
obkv_writer.insert(id, val)?;
}
}
let buffer = obkv_writer.into_inner()?;
original_writer.insert(docid.to_be_bytes(), &buffer)?;
// Once we have the document. We're going to flatten it
// and insert it in the flattened sorter.
let mut doc = serde_json::Map::new();
let reader = obkv::KvReader::new(buffer);
for (k, v) in reader.iter() {
let key = new_fields_ids_map.name(k).ok_or(FieldIdMapMissingEntry::FieldId {
field_id: k,
process: "Accessing field distribution in transform.",
})?;
let value = serde_json::from_slice::<serde_json::Value>(v)
.map_err(InternalError::SerdeJson)?;
doc.insert(key.to_string(), value);
}
let flattened = flatten_serde_json::flatten(&doc);
// Once we have the flattened version we can convert it back to obkv and
// insert all the new generated fields_ids (if any) in the fields ids map.
let mut buffer: Vec<u8> = Vec::new();
let mut writer = KvWriter::new(&mut buffer);
let mut flattened: Vec<_> = flattened.into_iter().collect();
// we reorder the field to get all the known field first
flattened.sort_unstable_by_key(|(key, _)| {
new_fields_ids_map.id(&key).unwrap_or(FieldId::MAX)
});
for (key, value) in flattened {
let fid =
new_fields_ids_map.insert(&key).ok_or(UserError::AttributeLimitReached)?;
let value = serde_json::to_vec(&value).map_err(InternalError::SerdeJson)?;
writer.insert(fid, &value)?;
}
flattened_writer.insert(docid.to_be_bytes(), &buffer)?;
}
// Once we have written all the documents, we extract
// the file and reset the seek to be able to read it again.
let mut original_documents = original_writer.into_inner()?;
original_documents.seek(SeekFrom::Start(0))?;
let mut flattened_documents = flattened_writer.into_inner()?;
flattened_documents.seek(SeekFrom::Start(0))?;
Ok(TransformOutput {
primary_key,
fields_ids_map: new_fields_ids_map,
field_distribution,
external_documents_ids: external_documents_ids.into_static(),
new_documents_ids: documents_ids,
replaced_documents_ids: RoaringBitmap::default(),
documents_count,
original_documents,
flattened_documents,
})
}
}
/// Drops all the value of type `U` in vec, and reuses the allocation to create a `Vec<T>`.
///
/// The size and alignment of T and U must match.
fn drop_and_reuse<U, T>(mut vec: Vec<U>) -> Vec<T> {
debug_assert_eq!(std::mem::align_of::<U>(), std::mem::align_of::<T>());
debug_assert_eq!(std::mem::size_of::<U>(), std::mem::size_of::<T>());
vec.clear();
debug_assert!(vec.is_empty());
vec.into_iter().map(|_| unreachable!()).collect()
}
impl TransformOutput {
// find and insert the new field ids
pub fn compute_real_facets(&self, rtxn: &RoTxn, index: &Index) -> Result<HashSet<String>> {
let user_defined_facets = index.user_defined_faceted_fields(rtxn)?;
Ok(self
.fields_ids_map
.names()
.filter(|&field| crate::is_faceted(field, &user_defined_facets))
.map(|field| field.to_string())
.collect())
}
}