mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-11-28 06:41:19 +08:00
732 lines
31 KiB
Rust
732 lines
31 KiB
Rust
use std::borrow::Cow;
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use std::collections::hash_map::Entry;
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use std::collections::{HashMap, HashSet};
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use std::fs::File;
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use std::io::{Read, Seek, SeekFrom};
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use fxhash::FxHashMap;
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use heed::RoTxn;
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use itertools::Itertools;
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use obkv::{KvReader, KvWriter};
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use roaring::RoaringBitmap;
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use serde_json::Value;
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use smartstring::SmartString;
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use super::helpers::{create_sorter, create_writer, keep_latest_obkv, merge_obkvs, MergeFn};
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use super::{IndexDocumentsMethod, IndexerConfig};
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use crate::documents::{DocumentsBatchIndex, EnrichedDocument, EnrichedDocumentsBatchReader};
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use crate::error::{Error, InternalError, UserError};
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use crate::index::db_name;
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use crate::update::{AvailableDocumentsIds, UpdateIndexingStep};
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use crate::{
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ExternalDocumentsIds, FieldDistribution, FieldId, FieldIdMapMissingEntry, FieldsIdsMap, Index,
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Result, BEU32,
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};
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pub struct TransformOutput {
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pub primary_key: String,
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pub fields_ids_map: FieldsIdsMap,
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pub field_distribution: FieldDistribution,
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pub external_documents_ids: ExternalDocumentsIds<'static>,
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pub new_documents_ids: RoaringBitmap,
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pub replaced_documents_ids: RoaringBitmap,
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pub documents_count: usize,
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pub original_documents: File,
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pub flattened_documents: File,
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}
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/// Extract the external ids, deduplicate and compute the new internal documents ids
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/// and fields ids, writing all the documents under their internal ids into a final file.
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///
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/// Outputs the new `FieldsIdsMap`, the new `UsersIdsDocumentsIds` map, the new documents ids,
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/// the replaced documents ids, the number of documents in this update and the file
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/// containing all those documents.
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pub struct Transform<'a, 'i> {
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pub index: &'i Index,
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fields_ids_map: FieldsIdsMap,
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indexer_settings: &'a IndexerConfig,
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pub autogenerate_docids: bool,
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pub index_documents_method: IndexDocumentsMethod,
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available_documents_ids: AvailableDocumentsIds,
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original_sorter: grenad::Sorter<MergeFn>,
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flattened_sorter: grenad::Sorter<MergeFn>,
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replaced_documents_ids: RoaringBitmap,
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new_documents_ids: RoaringBitmap,
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// To increase the cache locality and decrease the heap usage we use compact smartstring.
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new_external_documents_ids_builder: FxHashMap<SmartString<smartstring::Compact>, u64>,
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documents_count: usize,
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}
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/// Create a mapping between the field ids found in the document batch and the one that were
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/// already present in the index.
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///
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/// If new fields are present in the addition, they are added to the index field ids map.
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fn create_fields_mapping(
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index_field_map: &mut FieldsIdsMap,
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batch_field_map: &DocumentsBatchIndex,
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) -> Result<HashMap<FieldId, FieldId>> {
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batch_field_map
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.iter()
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// we sort by id here to ensure a deterministic mapping of the fields, that preserves
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// the original ordering.
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.sorted_by_key(|(&id, _)| id)
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.map(|(field, name)| match index_field_map.id(&name) {
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Some(id) => Ok((*field, id)),
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None => index_field_map
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.insert(&name)
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.ok_or(Error::UserError(UserError::AttributeLimitReached))
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.map(|id| (*field, id)),
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})
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.collect()
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}
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impl<'a, 'i> Transform<'a, 'i> {
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pub fn new(
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wtxn: &mut heed::RwTxn,
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index: &'i Index,
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indexer_settings: &'a IndexerConfig,
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index_documents_method: IndexDocumentsMethod,
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autogenerate_docids: bool,
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) -> Result<Self> {
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// We must choose the appropriate merge function for when two or more documents
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// with the same user id must be merged or fully replaced in the same batch.
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let merge_function = match index_documents_method {
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IndexDocumentsMethod::ReplaceDocuments => keep_latest_obkv,
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IndexDocumentsMethod::UpdateDocuments => merge_obkvs,
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};
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// We initialize the sorter with the user indexing settings.
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let original_sorter = create_sorter(
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merge_function,
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indexer_settings.chunk_compression_type,
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indexer_settings.chunk_compression_level,
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indexer_settings.max_nb_chunks,
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indexer_settings.max_memory.map(|mem| mem / 2),
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);
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// We initialize the sorter with the user indexing settings.
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let flattened_sorter = create_sorter(
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merge_function,
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indexer_settings.chunk_compression_type,
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indexer_settings.chunk_compression_level,
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indexer_settings.max_nb_chunks,
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indexer_settings.max_memory.map(|mem| mem / 2),
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);
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let documents_ids = index.documents_ids(wtxn)?;
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let soft_deleted_documents_ids = index.soft_deleted_documents_ids(wtxn)?;
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Ok(Transform {
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index,
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fields_ids_map: index.fields_ids_map(wtxn)?,
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indexer_settings,
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autogenerate_docids,
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available_documents_ids: AvailableDocumentsIds::from_documents_ids(
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&documents_ids,
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&soft_deleted_documents_ids,
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),
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original_sorter,
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flattened_sorter,
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index_documents_method,
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replaced_documents_ids: RoaringBitmap::new(),
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new_documents_ids: RoaringBitmap::new(),
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new_external_documents_ids_builder: FxHashMap::default(),
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documents_count: 0,
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})
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}
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pub fn read_documents<R, F>(
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&mut self,
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reader: EnrichedDocumentsBatchReader<R>,
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wtxn: &mut heed::RwTxn,
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progress_callback: F,
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) -> Result<usize>
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where
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R: Read + Seek,
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F: Fn(UpdateIndexingStep) + Sync,
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{
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let mut cursor = reader.into_cursor();
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let fields_index = cursor.documents_batch_index();
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let external_documents_ids = self.index.external_documents_ids(wtxn)?;
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let mapping = create_fields_mapping(&mut self.fields_ids_map, fields_index)?;
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let primary_key = cursor.primary_key().to_string();
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let primary_key_id_nested = primary_key.contains('.');
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let primary_key_id =
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self.fields_ids_map.insert(&primary_key).ok_or(UserError::AttributeLimitReached)?;
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let mut flattened_document = None;
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let mut obkv_buffer = Vec::new();
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let mut flattened_obkv_buffer = Vec::new();
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let mut documents_count = 0;
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let mut field_buffer: Vec<(u16, Cow<[u8]>)> = Vec::new();
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while let Some(enriched_document) = cursor.next_enriched_document()? {
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let EnrichedDocument { document, document_id } = enriched_document;
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let mut field_buffer_cache = drop_and_reuse(field_buffer);
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if self.indexer_settings.log_every_n.map_or(false, |len| documents_count % len == 0) {
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progress_callback(UpdateIndexingStep::RemapDocumentAddition {
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documents_seen: documents_count,
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});
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}
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// When the document id has been auto-generated by the `enrich_documents_batch`
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// we must insert this document id into the remaped document.
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let external_id = document_id.value();
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if document_id.is_generated() {
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let docid = serde_json::to_vec(external_id).map_err(InternalError::SerdeJson)?;
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field_buffer_cache.push((primary_key_id, Cow::from(docid)));
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}
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for (k, v) in document.iter() {
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let mapped_id =
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*mapping.get(&k).ok_or(InternalError::FieldIdMappingMissingEntry { key: k })?;
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field_buffer_cache.push((mapped_id, Cow::from(v)));
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}
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// We need to make sure that every document has a primary key. After we have remapped
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// all the fields in the document, we try to find the primary key value. If we can find
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// it, transform it into a string and validate it, and then update it in the
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// document. If none is found, and we were told to generate missing document ids, then
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// we create the missing field, and update the new document.
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if primary_key_id_nested {
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let mut field_buffer_cache = field_buffer_cache.clone();
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self.flatten_from_field_mapping(
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&mapping,
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&document,
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&mut flattened_obkv_buffer,
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&mut field_buffer_cache,
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)?;
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flattened_document = Some(&flattened_obkv_buffer);
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};
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// Insertion in a obkv need to be done with keys ordered. For now they are ordered
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// according to the document addition key order, so we sort it according to the
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// fieldids map keys order.
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field_buffer_cache.sort_unstable_by(|(f1, _), (f2, _)| f1.cmp(&f2));
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// Build the new obkv document.
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let mut writer = obkv::KvWriter::new(&mut obkv_buffer);
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for (k, v) in field_buffer_cache.iter() {
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writer.insert(*k, v)?;
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}
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let mut original_docid = None;
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let docid = match self.new_external_documents_ids_builder.entry(external_id.into()) {
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Entry::Occupied(entry) => *entry.get() as u32,
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Entry::Vacant(entry) => {
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// If the document was already in the db we mark it as a replaced document.
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// It'll be deleted later. We keep its original docid to insert it in the grenad.
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if let Some(docid) = external_documents_ids.get(entry.key()) {
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self.replaced_documents_ids.insert(docid);
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original_docid = Some(docid);
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}
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let docid = self
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.available_documents_ids
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.next()
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.ok_or(UserError::DocumentLimitReached)?;
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entry.insert(docid as u64);
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docid
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}
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};
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if let Some(original_docid) = original_docid {
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let original_key = BEU32::new(original_docid);
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let base_obkv = self
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.index
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.documents
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.remap_data_type::<heed::types::ByteSlice>()
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.get(wtxn, &original_key)?
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.ok_or(InternalError::DatabaseMissingEntry {
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db_name: db_name::DOCUMENTS,
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key: None,
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})?;
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// we associate the base document with the new key, everything will get merged later.
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self.original_sorter.insert(&docid.to_be_bytes(), base_obkv)?;
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match self.flatten_from_fields_ids_map(KvReader::new(&base_obkv))? {
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Some(buffer) => self.flattened_sorter.insert(docid.to_be_bytes(), &buffer)?,
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None => self.flattened_sorter.insert(docid.to_be_bytes(), base_obkv)?,
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}
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} else {
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self.new_documents_ids.insert(docid);
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}
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// We use the extracted/generated user id as the key for this document.
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self.original_sorter.insert(&docid.to_be_bytes(), obkv_buffer.clone())?;
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documents_count += 1;
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if let Some(flatten) = flattened_document {
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self.flattened_sorter.insert(docid.to_be_bytes(), &flatten)?;
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} else {
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match self.flatten_from_fields_ids_map(KvReader::new(&obkv_buffer))? {
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Some(buffer) => self.flattened_sorter.insert(docid.to_be_bytes(), &buffer)?,
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None => {
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self.flattened_sorter.insert(docid.to_be_bytes(), obkv_buffer.clone())?
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}
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}
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}
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progress_callback(UpdateIndexingStep::RemapDocumentAddition {
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documents_seen: documents_count,
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});
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field_buffer = drop_and_reuse(field_buffer_cache);
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obkv_buffer.clear();
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}
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progress_callback(UpdateIndexingStep::RemapDocumentAddition {
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documents_seen: documents_count,
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});
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self.index.put_fields_ids_map(wtxn, &self.fields_ids_map)?;
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self.index.put_primary_key(wtxn, &primary_key)?;
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self.documents_count += documents_count;
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// Now that we have a valid sorter that contains the user id and the obkv we
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// give it to the last transforming function which returns the TransformOutput.
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Ok(documents_count)
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}
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// Flatten a document from the fields ids map contained in self and insert the new
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// created fields. Returns `None` if the document doesn't need to be flattened.
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fn flatten_from_fields_ids_map(&mut self, obkv: KvReader<FieldId>) -> Result<Option<Vec<u8>>> {
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if obkv
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.iter()
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.all(|(_, value)| !json_depth_checker::should_flatten_from_unchecked_slice(value))
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{
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return Ok(None);
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}
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// store the keys and values the original obkv + the flattened json
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// We first extract all the key+value out of the obkv. If a value is not nested
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// we keep a reference on its value. If the value is nested we'll get its value
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// as an owned `Vec<u8>` after flattening it.
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let mut key_value: Vec<(FieldId, Cow<[u8]>)> = Vec::new();
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// the object we're going to use to store the fields that need to be flattened.
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let mut doc = serde_json::Map::new();
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// we recreate a json containing only the fields that needs to be flattened.
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// all the raw values get inserted directly in the `key_value` vec.
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for (key, value) in obkv.iter() {
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if json_depth_checker::should_flatten_from_unchecked_slice(value) {
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let key = self.fields_ids_map.name(key).ok_or(FieldIdMapMissingEntry::FieldId {
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field_id: key,
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process: "Flatten from fields ids map.",
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})?;
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let value = serde_json::from_slice::<Value>(value)
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.map_err(crate::error::InternalError::SerdeJson)?;
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doc.insert(key.to_string(), value);
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} else {
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key_value.push((key, value.into()));
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}
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}
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let flattened = flatten_serde_json::flatten(&doc);
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// Once we have the flattened version we insert all the new generated fields_ids
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// (if any) in the fields ids map and serialize the value.
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for (key, value) in flattened.into_iter() {
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let fid = self.fields_ids_map.insert(&key).ok_or(UserError::AttributeLimitReached)?;
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let value = serde_json::to_vec(&value).map_err(InternalError::SerdeJson)?;
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key_value.push((fid, value.into()));
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}
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// we sort the key. If there was a conflict between the obkv and the new generated value the
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// keys will be consecutive.
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key_value.sort_unstable_by_key(|(key, _)| *key);
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let mut buffer = Vec::new();
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Self::create_obkv_from_key_value(&mut key_value, &mut buffer)?;
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Ok(Some(buffer))
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}
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// Flatten a document from a field mapping generated by [create_fields_mapping]
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fn flatten_from_field_mapping(
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&mut self,
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mapping: &HashMap<FieldId, FieldId>,
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obkv: &KvReader<FieldId>,
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output_buffer: &mut Vec<u8>,
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field_buffer_cache: &mut Vec<(u16, Cow<[u8]>)>,
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) -> Result<()> {
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// store the keys and values of the json + the original obkv
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let mut key_value: Vec<(FieldId, Cow<[u8]>)> = Vec::new();
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// if the primary_key is nested we need to flatten the document before being able to do anything
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let mut doc = serde_json::Map::new();
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// we recreate a json containing only the fields that needs to be flattened.
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// all the raw values get inserted directly in the `key_value` vec.
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for (key, value) in obkv.iter() {
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if json_depth_checker::should_flatten_from_unchecked_slice(value) {
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let key =
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mapping.get(&key).ok_or(InternalError::FieldIdMappingMissingEntry { key })?;
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let key =
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self.fields_ids_map.name(*key).ok_or(FieldIdMapMissingEntry::FieldId {
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field_id: *key,
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process: "Flatten from field mapping.",
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})?;
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let value = serde_json::from_slice::<serde_json::Value>(value)
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.map_err(InternalError::SerdeJson)?;
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doc.insert(key.to_string(), value);
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} else {
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key_value.push((key, value.into()));
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}
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}
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let flattened = flatten_serde_json::flatten(&doc);
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// Once we have the flattened version we insert all the new generated fields_ids
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// (if any) in the fields ids map and serialize the value.
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for (key, value) in flattened.into_iter() {
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let fid = self.fields_ids_map.insert(&key).ok_or(UserError::AttributeLimitReached)?;
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let value = serde_json::to_vec(&value).map_err(InternalError::SerdeJson)?;
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key_value.push((fid, value.clone().into()));
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if field_buffer_cache.iter().find(|(id, _)| *id == fid).is_none() {
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field_buffer_cache.push((fid, value.into()));
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}
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}
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// we sort the key. If there was a conflict between the obkv and the new generated value the
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// keys will be consecutive.
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key_value.sort_unstable_by_key(|(key, _)| *key);
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Self::create_obkv_from_key_value(&mut key_value, output_buffer)?;
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Ok(())
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}
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/// Generate an obkv from a slice of key / value sorted by key.
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fn create_obkv_from_key_value(
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key_value: &mut [(FieldId, Cow<[u8]>)],
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output_buffer: &mut Vec<u8>,
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) -> Result<()> {
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debug_assert!(
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key_value.windows(2).all(|vec| vec[0].0 <= vec[1].0),
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"The slice of key / value pair must be sorted."
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);
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output_buffer.clear();
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let mut writer = KvWriter::new(output_buffer);
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let mut skip_next_value = false;
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for things in key_value.windows(2) {
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if skip_next_value {
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skip_next_value = false;
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continue;
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}
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let (key1, value1) = &things[0];
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let (key2, value2) = &things[1];
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// now we're going to look for conflicts between the keys. For example the following documents would cause a conflict:
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// { "doggo.name": "jean", "doggo": { "name": "paul" } }
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// we should find a first "doggo.name" from the obkv and a second one from the flattening.
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// but we must generate the following document:
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// { "doggo.name": ["jean", "paul"] }
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// thus we're going to merge the value from the obkv and the flattened document in a single array and skip the next
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// iteration.
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if key1 == key2 {
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skip_next_value = true;
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let value1 = serde_json::from_slice(value1)
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.map_err(crate::error::InternalError::SerdeJson)?;
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let value2 = serde_json::from_slice(value2)
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.map_err(crate::error::InternalError::SerdeJson)?;
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let value = match (value1, value2) {
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(Value::Array(mut left), Value::Array(mut right)) => {
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left.append(&mut right);
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Value::Array(left)
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}
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(Value::Array(mut array), value) | (value, Value::Array(mut array)) => {
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array.push(value);
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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())
|
|
}
|
|
}
|