use std::borrow::Cow; use std::convert::TryFrom; use fst::{IntoStreamer, Streamer}; use roaring::RoaringBitmap; use crate::{Index, BEU32, SmallString32}; use super::ClearDocuments; pub struct DeleteDocuments<'t, 'u, 'i> { wtxn: &'t mut heed::RwTxn<'i, 'u>, index: &'i Index, users_ids_documents_ids: fst::Map>, documents_ids: RoaringBitmap, } impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> { pub fn new( wtxn: &'t mut heed::RwTxn<'i, 'u>, index: &'i Index, ) -> anyhow::Result> { let users_ids_documents_ids = index .users_ids_documents_ids(wtxn)? .map_data(Cow::into_owned)?; Ok(DeleteDocuments { wtxn, index, users_ids_documents_ids, documents_ids: RoaringBitmap::new(), }) } pub fn delete_document(&mut self, docid: u32) { self.documents_ids.insert(docid); } pub fn delete_documents(&mut self, docids: &RoaringBitmap) { self.documents_ids.union_with(docids); } pub fn delete_user_id(&mut self, user_id: &str) -> Option { let docid = self.users_ids_documents_ids.get(user_id).map(|id| u32::try_from(id).unwrap())?; self.delete_document(docid); Some(docid) } pub fn execute(self) -> anyhow::Result { // We retrieve the current documents ids that are in the database. let mut documents_ids = self.index.documents_ids(self.wtxn)?; // We can and must stop removing documents in a database that is empty. if documents_ids.is_empty() { return Ok(0); } // We remove the documents ids that we want to delete // from the documents in the database and write them back. let current_documents_ids_len = documents_ids.len(); documents_ids.difference_with(&self.documents_ids); self.index.put_documents_ids(self.wtxn, &documents_ids)?; // We can execute a ClearDocuments operation when the number of documents // to delete is exactly the number of documents in the database. if current_documents_ids_len == self.documents_ids.len() { return ClearDocuments::new(self.wtxn, self.index).execute(); } let fields_ids_map = self.index.fields_ids_map(self.wtxn)?; let id_field = fields_ids_map.id("id").expect(r#"the field "id" to be present"#); let Index { env: _env, main: _main, word_docids, docid_word_positions, word_pair_proximity_docids, facet_field_id_value_docids, documents, } = self.index; // Retrieve the words and the users ids contained in the documents. let mut words = Vec::new(); let mut users_ids = Vec::new(); for docid in &self.documents_ids { // We create an iterator to be able to get the content and delete the document // content itself. It's faster to acquire a cursor to get and delete, // as we avoid traversing the LMDB B-Tree two times but only once. let key = BEU32::new(docid); let mut iter = documents.range_mut(self.wtxn, &(key..=key))?; if let Some((_key, obkv)) = iter.next().transpose()? { if let Some(content) = obkv.get(id_field) { let user_id: SmallString32 = serde_json::from_slice(content).unwrap(); users_ids.push(user_id); } iter.del_current()?; } drop(iter); // We iterate througt the words positions of the document id, // retrieve the word and delete the positions. let mut iter = docid_word_positions.prefix_iter_mut(self.wtxn, &(docid, ""))?; while let Some(result) = iter.next() { let ((_docid, word), _positions) = result?; // This boolean will indicate if we must remove this word from the words FST. words.push((SmallString32::from(word), false)); iter.del_current()?; } } // We create the FST map of the users ids that we must delete. users_ids.sort_unstable(); let users_ids_to_delete = fst::Set::from_iter(users_ids.iter().map(AsRef::as_ref))?; let users_ids_to_delete = fst::Map::from(users_ids_to_delete.into_fst()); let new_users_ids_documents_ids = { // We acquire the current users ids documents ids map and create // a difference operation between the current and to-delete users ids. let users_ids_documents_ids = self.index.users_ids_documents_ids(self.wtxn)?; let difference = users_ids_documents_ids.op().add(&users_ids_to_delete).difference(); // We stream the new users ids that does no more contains the to-delete users ids. let mut iter = difference.into_stream(); let mut new_users_ids_documents_ids_builder = fst::MapBuilder::memory(); while let Some((userid, docids)) = iter.next() { new_users_ids_documents_ids_builder.insert(userid, docids[0].value)?; } // We create an FST map from the above builder. new_users_ids_documents_ids_builder.into_map() }; // We write the new users ids into the main database. self.index.put_users_ids_documents_ids(self.wtxn, &new_users_ids_documents_ids)?; // Maybe we can improve the get performance of the words // if we sort the words first, keeping the LMDB pages in cache. words.sort_unstable(); // We iterate over the words and delete the documents ids // from the word docids database. for (word, must_remove) in &mut words { // We create an iterator to be able to get the content and delete the word docids. // It's faster to acquire a cursor to get and delete or put, as we avoid traversing // the LMDB B-Tree two times but only once. let mut iter = word_docids.prefix_iter_mut(self.wtxn, &word)?; if let Some((key, mut docids)) = iter.next().transpose()? { if key == word.as_ref() { docids.difference_with(&self.documents_ids); if docids.is_empty() { iter.del_current()?; *must_remove = true; } else { iter.put_current(key, &docids)?; } } } } // We construct an FST set that contains the words to delete from the words FST. let words_to_delete = words.iter().filter_map(|(word, must_remove)| { if *must_remove { Some(word.as_ref()) } else { None } }); let words_to_delete = fst::Set::from_iter(words_to_delete)?; let new_words_fst = { // We retrieve the current words FST from the database. let words_fst = self.index.words_fst(self.wtxn)?; let difference = words_fst.op().add(&words_to_delete).difference(); // We stream the new users ids that does no more contains the to-delete users ids. let mut new_words_fst_builder = fst::SetBuilder::memory(); new_words_fst_builder.extend_stream(difference.into_stream())?; // We create an words FST set from the above builder. new_words_fst_builder.into_set() }; // We write the new words FST into the main database. self.index.put_words_fst(self.wtxn, &new_words_fst)?; // We delete the documents ids that are under the pairs of words, // it is faster and use no memory to iterate over all the words pairs than // to compute the cartesian product of every words of the deleted documents. let mut iter = word_pair_proximity_docids.iter_mut(self.wtxn)?; while let Some(result) = iter.next() { let ((w1, w2, prox), mut docids) = result?; docids.difference_with(&self.documents_ids); if docids.is_empty() { iter.del_current()?; } else { iter.put_current(&(w1, w2, prox), &docids)?; } } drop(iter); // We delete the documents ids that are under the facet field id values. let mut iter = facet_field_id_value_docids.iter_mut(self.wtxn)?; while let Some(result) = iter.next() { let (bytes, mut docids) = result?; docids.difference_with(&self.documents_ids); if docids.is_empty() { iter.del_current()?; } else { iter.put_current(bytes, &docids)?; } } Ok(self.documents_ids.len() as usize) } }