mirror of
https://github.com/meilisearch/meilisearch.git
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214 lines
8.7 KiB
Rust
214 lines
8.7 KiB
Rust
use std::borrow::Cow;
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use std::convert::TryFrom;
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use fst::{IntoStreamer, Streamer};
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use roaring::RoaringBitmap;
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use crate::{Index, BEU32, SmallString32};
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use super::ClearDocuments;
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pub struct DeleteDocuments<'t, 'u, 'i> {
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wtxn: &'t mut heed::RwTxn<'i, 'u>,
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index: &'i Index,
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users_ids_documents_ids: fst::Map<Vec<u8>>,
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documents_ids: RoaringBitmap,
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}
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impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
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pub fn new(
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wtxn: &'t mut heed::RwTxn<'i, 'u>,
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index: &'i Index,
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) -> anyhow::Result<DeleteDocuments<'t, 'u, 'i>>
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{
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let users_ids_documents_ids = index
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.users_ids_documents_ids(wtxn)?
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.map_data(Cow::into_owned)?;
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Ok(DeleteDocuments {
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wtxn,
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index,
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users_ids_documents_ids,
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documents_ids: RoaringBitmap::new(),
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})
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}
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pub fn delete_document(&mut self, docid: u32) {
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self.documents_ids.insert(docid);
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}
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pub fn delete_documents(&mut self, docids: &RoaringBitmap) {
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self.documents_ids.union_with(docids);
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}
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pub fn delete_user_id(&mut self, user_id: &str) -> Option<u32> {
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let docid = self.users_ids_documents_ids.get(user_id).map(|id| u32::try_from(id).unwrap())?;
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self.delete_document(docid);
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Some(docid)
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}
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pub fn execute(self) -> anyhow::Result<usize> {
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// We retrieve the current documents ids that are in the database.
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let mut documents_ids = self.index.documents_ids(self.wtxn)?;
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// We can and must stop removing documents in a database that is empty.
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if documents_ids.is_empty() {
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return Ok(0);
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}
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// We remove the documents ids that we want to delete
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// from the documents in the database and write them back.
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let current_documents_ids_len = documents_ids.len();
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documents_ids.difference_with(&self.documents_ids);
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self.index.put_documents_ids(self.wtxn, &documents_ids)?;
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// We can execute a ClearDocuments operation when the number of documents
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// to delete is exactly the number of documents in the database.
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if current_documents_ids_len == self.documents_ids.len() {
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return ClearDocuments::new(self.wtxn, self.index).execute();
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}
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let fields_ids_map = self.index.fields_ids_map(self.wtxn)?;
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let id_field = fields_ids_map.id("id").expect(r#"the field "id" to be present"#);
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let Index {
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env: _env,
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main: _main,
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word_docids,
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docid_word_positions,
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word_pair_proximity_docids,
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facet_field_id_value_docids,
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documents,
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} = self.index;
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// Retrieve the words and the users ids contained in the documents.
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let mut words = Vec::new();
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let mut users_ids = Vec::new();
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for docid in &self.documents_ids {
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// We create an iterator to be able to get the content and delete the document
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// content itself. It's faster to acquire a cursor to get and delete,
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// as we avoid traversing the LMDB B-Tree two times but only once.
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let key = BEU32::new(docid);
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let mut iter = documents.range_mut(self.wtxn, &(key..=key))?;
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if let Some((_key, obkv)) = iter.next().transpose()? {
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if let Some(content) = obkv.get(id_field) {
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let user_id: SmallString32 = serde_json::from_slice(content).unwrap();
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users_ids.push(user_id);
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}
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iter.del_current()?;
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}
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drop(iter);
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// We iterate througt the words positions of the document id,
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// retrieve the word and delete the positions.
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let mut iter = docid_word_positions.prefix_iter_mut(self.wtxn, &(docid, ""))?;
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while let Some(result) = iter.next() {
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let ((_docid, word), _positions) = result?;
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// This boolean will indicate if we must remove this word from the words FST.
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words.push((SmallString32::from(word), false));
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iter.del_current()?;
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}
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}
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// We create the FST map of the users ids that we must delete.
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users_ids.sort_unstable();
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let users_ids_to_delete = fst::Set::from_iter(users_ids.iter().map(AsRef::as_ref))?;
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let users_ids_to_delete = fst::Map::from(users_ids_to_delete.into_fst());
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let new_users_ids_documents_ids = {
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// We acquire the current users ids documents ids map and create
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// a difference operation between the current and to-delete users ids.
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let users_ids_documents_ids = self.index.users_ids_documents_ids(self.wtxn)?;
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let difference = users_ids_documents_ids.op().add(&users_ids_to_delete).difference();
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// We stream the new users ids that does no more contains the to-delete users ids.
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let mut iter = difference.into_stream();
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let mut new_users_ids_documents_ids_builder = fst::MapBuilder::memory();
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while let Some((userid, docids)) = iter.next() {
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new_users_ids_documents_ids_builder.insert(userid, docids[0].value)?;
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}
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// We create an FST map from the above builder.
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new_users_ids_documents_ids_builder.into_map()
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};
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// We write the new users ids into the main database.
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self.index.put_users_ids_documents_ids(self.wtxn, &new_users_ids_documents_ids)?;
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// Maybe we can improve the get performance of the words
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// if we sort the words first, keeping the LMDB pages in cache.
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words.sort_unstable();
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// We iterate over the words and delete the documents ids
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// from the word docids database.
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for (word, must_remove) in &mut words {
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// We create an iterator to be able to get the content and delete the word docids.
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// It's faster to acquire a cursor to get and delete or put, as we avoid traversing
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// the LMDB B-Tree two times but only once.
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let mut iter = word_docids.prefix_iter_mut(self.wtxn, &word)?;
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if let Some((key, mut docids)) = iter.next().transpose()? {
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if key == word.as_ref() {
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docids.difference_with(&self.documents_ids);
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if docids.is_empty() {
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iter.del_current()?;
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*must_remove = true;
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} else {
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iter.put_current(key, &docids)?;
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}
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}
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}
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}
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// We construct an FST set that contains the words to delete from the words FST.
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let words_to_delete = words.iter().filter_map(|(word, must_remove)| {
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if *must_remove { Some(word.as_ref()) } else { None }
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});
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let words_to_delete = fst::Set::from_iter(words_to_delete)?;
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let new_words_fst = {
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// We retrieve the current words FST from the database.
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let words_fst = self.index.words_fst(self.wtxn)?;
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let difference = words_fst.op().add(&words_to_delete).difference();
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// We stream the new users ids that does no more contains the to-delete users ids.
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let mut new_words_fst_builder = fst::SetBuilder::memory();
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new_words_fst_builder.extend_stream(difference.into_stream())?;
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// We create an words FST set from the above builder.
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new_words_fst_builder.into_set()
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};
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// We write the new words FST into the main database.
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self.index.put_words_fst(self.wtxn, &new_words_fst)?;
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// We delete the documents ids that are under the pairs of words,
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// it is faster and use no memory to iterate over all the words pairs than
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// to compute the cartesian product of every words of the deleted documents.
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let mut iter = word_pair_proximity_docids.iter_mut(self.wtxn)?;
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while let Some(result) = iter.next() {
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let ((w1, w2, prox), mut docids) = result?;
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docids.difference_with(&self.documents_ids);
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if docids.is_empty() {
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iter.del_current()?;
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} else {
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iter.put_current(&(w1, w2, prox), &docids)?;
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}
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}
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drop(iter);
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// We delete the documents ids that are under the facet field id values.
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let mut iter = facet_field_id_value_docids.iter_mut(self.wtxn)?;
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while let Some(result) = iter.next() {
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let (bytes, mut docids) = result?;
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docids.difference_with(&self.documents_ids);
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if docids.is_empty() {
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iter.del_current()?;
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} else {
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iter.put_current(bytes, &docids)?;
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}
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}
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Ok(self.documents_ids.len() as usize)
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}
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}
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