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

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(
            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(
            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.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
                }
            };

            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 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)?,
                }
            } else {
                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)?;
            documents_count += 1;

            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)?,
            }

            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())
    }
}