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

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mod enrich;
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mod extract;
mod helpers;
mod transform;
mod typed_chunk;
use std::collections::{HashMap, HashSet};
use std::io::{Read, Seek};
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use std::iter::FromIterator;
use std::num::NonZeroU32;
use std::result::Result as StdResult;
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use crossbeam_channel::{Receiver, Sender};
use grenad::{Merger, MergerBuilder};
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use heed::types::Str;
use heed::Database;
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use rand::SeedableRng;
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use roaring::RoaringBitmap;
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use serde::{Deserialize, Serialize};
use slice_group_by::GroupBy;
use tracing::debug;
use typed_chunk::{write_typed_chunk_into_index, ChunkAccumulator, TypedChunk};
use self::enrich::enrich_documents_batch;
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pub use self::enrich::{extract_finite_float_from_value, DocumentId};
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pub use self::helpers::{
as_cloneable_grenad, create_sorter, create_writer, fst_stream_into_hashset,
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fst_stream_into_vec, merge_cbo_roaring_bitmaps, merge_deladd_cbo_roaring_bitmaps,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap, merge_roaring_bitmaps,
valid_lmdb_key, write_sorter_into_database, writer_into_reader, MergeFn,
};
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use self::helpers::{grenad_obkv_into_chunks, GrenadParameters};
pub use self::transform::{Transform, TransformOutput};
use crate::documents::{obkv_to_object, DocumentsBatchReader};
use crate::error::{Error, InternalError, UserError};
pub use crate::update::index_documents::helpers::CursorClonableMmap;
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use crate::update::{
IndexerConfig, UpdateIndexingStep, WordPrefixDocids, WordPrefixIntegerDocids, WordsPrefixesFst,
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};
use crate::vector::EmbeddingConfigs;
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use crate::{CboRoaringBitmapCodec, Index, Result};
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static MERGED_DATABASE_COUNT: usize = 7;
static PREFIX_DATABASE_COUNT: usize = 4;
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static TOTAL_POSTING_DATABASE_COUNT: usize = MERGED_DATABASE_COUNT + PREFIX_DATABASE_COUNT;
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
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pub struct DocumentAdditionResult {
/// The number of documents that were indexed during the update
pub indexed_documents: u64,
/// The total number of documents in the index after the update
pub number_of_documents: u64,
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}
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, Serialize, Deserialize)]
#[non_exhaustive]
pub enum IndexDocumentsMethod {
/// Replace the previous document with the new one,
/// removing all the already known attributes.
ReplaceDocuments,
/// Merge the previous version of the document with the new version,
/// replacing old attributes values with the new ones and add the new attributes.
UpdateDocuments,
}
impl Default for IndexDocumentsMethod {
fn default() -> Self {
Self::ReplaceDocuments
}
}
pub struct IndexDocuments<'t, 'i, 'a, FP, FA> {
wtxn: &'t mut heed::RwTxn<'i>,
index: &'i Index,
config: IndexDocumentsConfig,
indexer_config: &'a IndexerConfig,
transform: Option<Transform<'a, 'i>>,
progress: FP,
should_abort: FA,
added_documents: u64,
deleted_documents: u64,
embedders: EmbeddingConfigs,
}
#[derive(Default, Debug, Clone)]
pub struct IndexDocumentsConfig {
pub words_prefix_threshold: Option<u32>,
pub max_prefix_length: Option<usize>,
pub words_positions_level_group_size: Option<NonZeroU32>,
pub words_positions_min_level_size: Option<NonZeroU32>,
pub update_method: IndexDocumentsMethod,
pub autogenerate_docids: bool,
}
impl<'t, 'i, 'a, FP, FA> IndexDocuments<'t, 'i, 'a, FP, FA>
where
FP: Fn(UpdateIndexingStep) + Sync + Send,
FA: Fn() -> bool + Sync + Send,
{
pub fn new(
wtxn: &'t mut heed::RwTxn<'i>,
index: &'i Index,
indexer_config: &'a IndexerConfig,
config: IndexDocumentsConfig,
progress: FP,
should_abort: FA,
) -> Result<IndexDocuments<'t, 'i, 'a, FP, FA>> {
let transform = Some(Transform::new(
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wtxn,
index,
indexer_config,
config.update_method,
config.autogenerate_docids,
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)?);
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Ok(IndexDocuments {
transform,
config,
indexer_config,
progress,
should_abort,
wtxn,
index,
added_documents: 0,
deleted_documents: 0,
embedders: Default::default(),
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})
}
/// Adds a batch of documents to the current builder.
///
/// Since the documents are progressively added to the writer, a failure will cause only
/// return an error and not the `IndexDocuments` struct as it is invalid to use it afterward.
///
/// Returns the number of documents added to the builder.
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#[tracing::instrument(level = "trace", skip_all, target = "indexing::documents")]
pub fn add_documents<R: Read + Seek>(
mut self,
reader: DocumentsBatchReader<R>,
) -> Result<(Self, StdResult<u64, UserError>)> {
puffin::profile_function!();
// Early return when there is no document to add
if reader.is_empty() {
return Ok((self, Ok(0)));
}
// We check for user errors in this validator and if there is one, we can return
// the `IndexDocument` struct as it is valid to send more documents into it.
// However, if there is an internal error we throw it away!
let enriched_documents_reader = match enrich_documents_batch(
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self.wtxn,
self.index,
self.config.autogenerate_docids,
reader,
)? {
Ok(reader) => reader,
Err(user_error) => return Ok((self, Err(user_error))),
};
let indexed_documents =
self.transform.as_mut().expect("Invalid document addition state").read_documents(
enriched_documents_reader,
self.wtxn,
&self.progress,
&self.should_abort,
)? as u64;
self.added_documents += indexed_documents;
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Ok((self, Ok(indexed_documents)))
}
pub fn with_embedders(mut self, embedders: EmbeddingConfigs) -> Self {
self.embedders = embedders;
self
}
/// Remove a batch of documents from the current builder.
///
/// Returns the number of documents deleted from the builder.
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#[tracing::instrument(level = "trace", skip_all, target = "indexing::documents")]
pub fn remove_documents(
mut self,
to_delete: Vec<String>,
) -> Result<(Self, StdResult<u64, UserError>)> {
puffin::profile_function!();
// Early return when there is no document to add
if to_delete.is_empty() {
// Maintains Invariant: remove documents actually always returns Ok for the inner result
return Ok((self, Ok(0)));
}
let deleted_documents = self
.transform
.as_mut()
.expect("Invalid document deletion state")
.remove_documents(to_delete, self.wtxn, &self.should_abort)?
as u64;
self.deleted_documents += deleted_documents;
// Maintains Invariant: remove documents actually always returns Ok for the inner result
Ok((self, Ok(deleted_documents)))
}
/// Removes documents from db using their internal document ids.
///
/// # Warning
///
/// This function is dangerous and will only work correctly if:
///
/// - All the passed ids currently exist in the database
/// - No batching using the standards `remove_documents` and `add_documents` took place
///
/// TODO: make it impossible to call `remove_documents` or `add_documents` on an instance that calls this function.
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#[tracing::instrument(level = "trace", skip_all, target = "indexing::details")]
pub fn remove_documents_from_db_no_batch(
mut self,
to_delete: &RoaringBitmap,
) -> Result<(Self, u64)> {
puffin::profile_function!();
// Early return when there is no document to add
if to_delete.is_empty() {
return Ok((self, 0));
}
let deleted_documents = self
.transform
.as_mut()
.expect("Invalid document deletion state")
.remove_documents_from_db_no_batch(to_delete, self.wtxn, &self.should_abort)?
as u64;
self.deleted_documents += deleted_documents;
Ok((self, deleted_documents))
}
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#[tracing::instrument(
level = "trace"
skip_all,
target = "indexing::documents",
name = "index_documents"
)]
pub fn execute(mut self) -> Result<DocumentAdditionResult> {
puffin::profile_function!();
if self.added_documents == 0 && self.deleted_documents == 0 {
let number_of_documents = self.index.number_of_documents(self.wtxn)?;
return Ok(DocumentAdditionResult { indexed_documents: 0, number_of_documents });
}
let output = self
.transform
.take()
.expect("Invalid document addition state")
.output_from_sorter(self.wtxn, &self.progress)?;
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let new_facets = output.compute_real_facets(self.wtxn, self.index)?;
self.index.put_faceted_fields(self.wtxn, &new_facets)?;
// in case new fields were introduced we're going to recreate the searchable fields.
if let Some(faceted_fields) = self.index.user_defined_searchable_fields(self.wtxn)? {
// we can't keep references on the faceted fields while we update the index thus we need to own it.
let faceted_fields: Vec<String> =
faceted_fields.into_iter().map(str::to_string).collect();
self.index.put_all_searchable_fields_from_fields_ids_map(
self.wtxn,
&faceted_fields.iter().map(String::as_ref).collect::<Vec<_>>(),
&output.fields_ids_map,
)?;
}
let indexed_documents = output.documents_count as u64;
let number_of_documents = self.execute_raw(output)?;
Ok(DocumentAdditionResult { indexed_documents, number_of_documents })
}
/// Returns the total number of documents in the index after the update.
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#[tracing::instrument(
level = "trace",
skip_all,
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target = "indexing::details",
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name = "index_documents_raw"
)]
pub fn execute_raw(self, output: TransformOutput) -> Result<u64>
where
FP: Fn(UpdateIndexingStep) + Sync,
FA: Fn() -> bool + Sync,
{
puffin::profile_function!();
let TransformOutput {
primary_key,
fields_ids_map,
field_distribution,
documents_count,
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original_documents,
flattened_documents,
} = output;
// The fields_ids_map is put back to the store now so the rest of the transaction sees an
// up to date field map.
self.index.put_fields_ids_map(self.wtxn, &fields_ids_map)?;
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let backup_pool;
let pool = match self.indexer_config.thread_pool {
Some(ref pool) => pool,
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#[cfg(not(test))]
None => {
// We initialize a bakcup pool with the default
// settings if none have already been set.
backup_pool = rayon::ThreadPoolBuilder::new().build()?;
&backup_pool
}
#[cfg(test)]
None => {
// We initialize a bakcup pool with the default
// settings if none have already been set.
backup_pool = rayon::ThreadPoolBuilder::new().num_threads(1).build()?;
&backup_pool
}
};
// create LMDB writer channel
let (lmdb_writer_sx, lmdb_writer_rx): (
Sender<Result<TypedChunk>>,
Receiver<Result<TypedChunk>>,
) = crossbeam_channel::unbounded();
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// get the primary key field id
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let primary_key_id = fields_ids_map.id(&primary_key).unwrap();
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// get searchable fields for word databases
let searchable_fields =
self.index.searchable_fields_ids(self.wtxn)?.map(HashSet::from_iter);
// get filterable fields for facet databases
let faceted_fields = self.index.faceted_fields_ids(self.wtxn)?;
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// get the fid of the `_geo.lat` and `_geo.lng` fields.
let mut field_id_map = self.index.fields_ids_map(self.wtxn)?;
// self.index.fields_ids_map($a)? ==>> field_id_map
let geo_fields_ids = match field_id_map.id("_geo") {
Some(gfid) => {
let is_sortable = self.index.sortable_fields_ids(self.wtxn)?.contains(&gfid);
let is_filterable = self.index.filterable_fields_ids(self.wtxn)?.contains(&gfid);
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// if `_geo` is faceted then we get the `lat` and `lng`
if is_sortable || is_filterable {
let field_ids = field_id_map
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.insert("_geo.lat")
.zip(field_id_map.insert("_geo.lng"))
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.ok_or(UserError::AttributeLimitReached)?;
Some(field_ids)
} else {
None
}
}
None => None,
};
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let stop_words = self.index.stop_words(self.wtxn)?;
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let separators = self.index.allowed_separators(self.wtxn)?;
let dictionary = self.index.dictionary(self.wtxn)?;
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let exact_attributes = self.index.exact_attributes_ids(self.wtxn)?;
let proximity_precision = self.index.proximity_precision(self.wtxn)?.unwrap_or_default();
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let pool_params = GrenadParameters {
chunk_compression_type: self.indexer_config.chunk_compression_type,
chunk_compression_level: self.indexer_config.chunk_compression_level,
max_memory: self.indexer_config.max_memory,
max_nb_chunks: self.indexer_config.max_nb_chunks, // default value, may be chosen.
};
let documents_chunk_size = match self.indexer_config.documents_chunk_size {
Some(chunk_size) => chunk_size,
None => {
let default_chunk_size = 1024 * 1024 * 4; // 4MiB
let min_chunk_size = 1024 * 512; // 512KiB
// compute the chunk size from the number of available threads and the inputed data size.
let total_size = flattened_documents.metadata().map(|m| m.len());
let current_num_threads = pool.current_num_threads();
// if we have more than 2 thread, create a number of chunk equal to 3/4 threads count
let chunk_count = if current_num_threads > 2 {
(current_num_threads * 3 / 4).max(2)
} else {
current_num_threads
};
total_size
.map_or(default_chunk_size, |size| (size as usize) / chunk_count)
.max(min_chunk_size)
}
};
let original_documents = grenad::Reader::new(original_documents)?;
let flattened_documents = grenad::Reader::new(flattened_documents)?;
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let max_positions_per_attributes = self.indexer_config.max_positions_per_attributes;
let cloned_embedder = self.embedders.clone();
let mut final_documents_ids = RoaringBitmap::new();
let mut databases_seen = 0;
let mut word_position_docids = None;
let mut word_fid_docids = None;
let mut word_docids = None;
let mut exact_word_docids = None;
let mut chunk_accumulator = ChunkAccumulator::default();
let mut dimension = HashMap::new();
let stop_words = stop_words.map(|sw| sw.map_data(Vec::from).unwrap());
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let current_span = tracing::Span::current();
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// Run extraction pipeline in parallel.
pool.install(|| {
rayon::spawn(move || {
let child_span = tracing::trace_span!(target: "indexing::details", parent: &current_span, "extract_and_send_grenad_chunks");
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let _enter = child_span.enter();
puffin::profile_scope!("extract_and_send_grenad_chunks");
// split obkv file into several chunks
let original_chunk_iter =
grenad_obkv_into_chunks(original_documents, pool_params, documents_chunk_size);
// split obkv file into several chunks
let flattened_chunk_iter =
grenad_obkv_into_chunks(flattened_documents, pool_params, documents_chunk_size);
let separators: Option<Vec<_>> =
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
let dictionary: Option<Vec<_>> =
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
let result = original_chunk_iter.and_then(|original_chunk| {
let flattened_chunk = flattened_chunk_iter?;
// extract all databases from the chunked obkv douments
extract::data_from_obkv_documents(
original_chunk,
flattened_chunk,
pool_params,
lmdb_writer_sx.clone(),
searchable_fields,
faceted_fields,
primary_key_id,
geo_fields_ids,
field_id_map,
stop_words,
separators.as_deref(),
dictionary.as_deref(),
max_positions_per_attributes,
exact_attributes,
proximity_precision,
cloned_embedder,
)
});
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if let Err(e) = result {
let _ = lmdb_writer_sx.send(Err(e));
}
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// needs to be dropped to avoid channel waiting lock.
drop(lmdb_writer_sx);
});
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(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
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loop {
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
match lmdb_writer_rx.clone().recv_timeout(std::time::Duration::from_millis(500)) {
Err(status) => {
if let Some(typed_chunks) = chunk_accumulator.pop_longest() {
let (docids, is_merged_database) =
write_typed_chunk_into_index(typed_chunks, self.index, self.wtxn)?;
if !docids.is_empty() {
final_documents_ids |= docids;
let documents_seen_count = final_documents_ids.len();
(self.progress)(UpdateIndexingStep::IndexDocuments {
documents_seen: documents_seen_count as usize,
total_documents: documents_count,
});
debug!(documents = documents_seen_count, total = documents_count, "Seen");
}
if is_merged_database {
databases_seen += 1;
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
}
// If no more chunk remains in the chunk accumulator and the channel is disconected, break.
} else if status == crossbeam_channel::RecvTimeoutError::Disconnected {
break;
} else {
rayon::yield_now();
}
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}
Ok(result) => {
let typed_chunk = match result? {
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
} => {
let cloneable_chunk =
unsafe { as_cloneable_grenad(&word_docids_reader)? };
let word_docids = word_docids.get_or_insert_with(|| {
MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn)
});
word_docids.push(cloneable_chunk.into_cursor()?);
let cloneable_chunk =
unsafe { as_cloneable_grenad(&exact_word_docids_reader)? };
let exact_word_docids =
exact_word_docids.get_or_insert_with(|| {
MergerBuilder::new(
merge_deladd_cbo_roaring_bitmaps as MergeFn,
)
});
exact_word_docids.push(cloneable_chunk.into_cursor()?);
let cloneable_chunk =
unsafe { as_cloneable_grenad(&word_fid_docids_reader)? };
let word_fid_docids = word_fid_docids.get_or_insert_with(|| {
MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn)
});
word_fid_docids.push(cloneable_chunk.into_cursor()?);
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
}
}
TypedChunk::WordPositionDocids(chunk) => {
let cloneable_chunk = unsafe { as_cloneable_grenad(&chunk)? };
let word_position_docids =
word_position_docids.get_or_insert_with(|| {
MergerBuilder::new(
merge_deladd_cbo_roaring_bitmaps as MergeFn,
)
});
word_position_docids.push(cloneable_chunk.into_cursor()?);
TypedChunk::WordPositionDocids(chunk)
}
TypedChunk::VectorPoints {
expected_dimension,
remove_vectors,
embeddings,
manual_vectors,
embedder_name,
} => {
dimension.insert(embedder_name.clone(), expected_dimension);
TypedChunk::VectorPoints {
remove_vectors,
embeddings,
expected_dimension,
manual_vectors,
embedder_name,
}
}
otherwise => otherwise,
};
chunk_accumulator.insert(typed_chunk);
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}
}
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}
Ok(())
})?;
// We write the field distribution into the main database
self.index.put_field_distribution(self.wtxn, &field_distribution)?;
// We write the primary key field id into the main database
self.index.put_primary_key(self.wtxn, &primary_key)?;
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let number_of_documents = self.index.number_of_documents(self.wtxn)?;
let mut rng = rand::rngs::StdRng::seed_from_u64(42);
for (embedder_name, dimension) in dimension {
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let wtxn = &mut *self.wtxn;
let vector_arroy = self.index.vector_arroy;
let embedder_index = self.index.embedder_category_id.get(wtxn, &embedder_name)?.ok_or(
InternalError::DatabaseMissingEntry { db_name: "embedder_category_id", key: None },
)?;
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pool.install(|| {
let writer_index = (embedder_index as u16) << 8;
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for k in 0..=u8::MAX {
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let writer =
arroy::Writer::new(vector_arroy, writer_index | (k as u16), dimension)?;
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if writer.is_empty(wtxn)? {
break;
}
writer.build(wtxn, &mut rng, None)?;
}
Result::Ok(())
})?;
}
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self.execute_prefix_databases(
word_docids.map(MergerBuilder::build),
exact_word_docids.map(MergerBuilder::build),
word_position_docids.map(MergerBuilder::build),
word_fid_docids.map(MergerBuilder::build),
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)?;
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Ok(number_of_documents)
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}
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#[tracing::instrument(
level = "trace",
skip_all,
target = "indexing::prefix",
name = "index_documents_prefix_databases"
)]
pub fn execute_prefix_databases(
self,
word_docids: Option<Merger<CursorClonableMmap, MergeFn>>,
exact_word_docids: Option<Merger<CursorClonableMmap, MergeFn>>,
word_position_docids: Option<Merger<CursorClonableMmap, MergeFn>>,
word_fid_docids: Option<Merger<CursorClonableMmap, MergeFn>>,
) -> Result<()>
where
FP: Fn(UpdateIndexingStep) + Sync,
FA: Fn() -> bool + Sync,
{
puffin::profile_function!();
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// Merged databases are already been indexed, we start from this count;
let mut databases_seen = MERGED_DATABASE_COUNT;
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
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databases_seen += 1;
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
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total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
let previous_words_prefixes_fst =
self.index.words_prefixes_fst(self.wtxn)?.map_data(|cow| cow.into_owned())?;
// Run the words prefixes update operation.
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let mut builder = WordsPrefixesFst::new(self.wtxn, self.index);
if let Some(value) = self.config.words_prefix_threshold {
builder.threshold(value);
}
if let Some(value) = self.config.max_prefix_length {
builder.max_prefix_length(value);
}
builder.execute()?;
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
let current_prefix_fst;
let common_prefix_fst_words_tmp;
let common_prefix_fst_words: Vec<_>;
let new_prefix_fst_words;
let del_prefix_fst_words;
{
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let span = tracing::trace_span!(target: "indexing::details", "compute_prefix_diffs");
let _entered = span.enter();
puffin::profile_scope!("compute_prefix_diffs");
current_prefix_fst = self.index.words_prefixes_fst(self.wtxn)?;
// We retrieve the common words between the previous and new prefix word fst.
common_prefix_fst_words_tmp = fst_stream_into_vec(
previous_words_prefixes_fst.op().add(&current_prefix_fst).intersection(),
);
common_prefix_fst_words = common_prefix_fst_words_tmp
.as_slice()
.linear_group_by_key(|x| x.chars().next().unwrap())
.collect();
// We retrieve the newly added words between the previous and new prefix word fst.
new_prefix_fst_words = fst_stream_into_vec(
current_prefix_fst.op().add(&previous_words_prefixes_fst).difference(),
);
// We compute the set of prefixes that are no more part of the prefix fst.
del_prefix_fst_words = fst_stream_into_hashset(
previous_words_prefixes_fst.op().add(&current_prefix_fst).difference(),
);
}
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databases_seen += 1;
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
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total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
if let Some(word_docids) = word_docids {
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execute_word_prefix_docids(
self.wtxn,
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word_docids,
self.index.word_docids,
self.index.word_prefix_docids,
self.indexer_config,
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&new_prefix_fst_words,
&common_prefix_fst_words,
&del_prefix_fst_words,
)?;
}
if let Some(exact_word_docids) = exact_word_docids {
execute_word_prefix_docids(
self.wtxn,
exact_word_docids,
self.index.exact_word_docids,
self.index.exact_word_prefix_docids,
self.indexer_config,
&new_prefix_fst_words,
&common_prefix_fst_words,
&del_prefix_fst_words,
)?;
}
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
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databases_seen += 1;
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
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total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
if let Some(word_position_docids) = word_position_docids {
// Run the words prefix position docids update operation.
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let mut builder = WordPrefixIntegerDocids::new(
self.wtxn,
self.index.word_prefix_position_docids,
self.index.word_position_docids,
);
builder.chunk_compression_type = self.indexer_config.chunk_compression_type;
builder.chunk_compression_level = self.indexer_config.chunk_compression_level;
builder.max_nb_chunks = self.indexer_config.max_nb_chunks;
builder.max_memory = self.indexer_config.max_memory;
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builder.execute(
word_position_docids,
&new_prefix_fst_words,
&common_prefix_fst_words,
&del_prefix_fst_words,
)?;
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}
if let Some(word_fid_docids) = word_fid_docids {
// Run the words prefix fid docids update operation.
let mut builder = WordPrefixIntegerDocids::new(
self.wtxn,
self.index.word_prefix_fid_docids,
self.index.word_fid_docids,
);
builder.chunk_compression_type = self.indexer_config.chunk_compression_type;
builder.chunk_compression_level = self.indexer_config.chunk_compression_level;
builder.max_nb_chunks = self.indexer_config.max_nb_chunks;
builder.max_memory = self.indexer_config.max_memory;
builder.execute(
word_fid_docids,
&new_prefix_fst_words,
&common_prefix_fst_words,
&del_prefix_fst_words,
)?;
}
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
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databases_seen += 1;
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
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total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
Ok(())
}
}
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/// Run the word prefix docids update operation.
#[allow(clippy::too_many_arguments)]
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#[tracing::instrument(
level = "trace",
skip_all,
target = "indexing::prefix",
name = "index_documents_word_prefix_docids"
)]
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fn execute_word_prefix_docids(
txn: &mut heed::RwTxn,
merger: Merger<CursorClonableMmap, MergeFn>,
word_docids_db: Database<Str, CboRoaringBitmapCodec>,
word_prefix_docids_db: Database<Str, CboRoaringBitmapCodec>,
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indexer_config: &IndexerConfig,
new_prefix_fst_words: &[String],
common_prefix_fst_words: &[&[String]],
del_prefix_fst_words: &HashSet<Vec<u8>>,
) -> Result<()> {
puffin::profile_function!();
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let mut builder = WordPrefixDocids::new(txn, word_docids_db, word_prefix_docids_db);
builder.chunk_compression_type = indexer_config.chunk_compression_type;
builder.chunk_compression_level = indexer_config.chunk_compression_level;
builder.max_nb_chunks = indexer_config.max_nb_chunks;
builder.max_memory = indexer_config.max_memory;
builder.execute(merger, new_prefix_fst_words, common_prefix_fst_words, del_prefix_fst_words)?;
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Ok(())
}
#[cfg(test)]
mod tests {
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use std::collections::BTreeMap;
use big_s::S;
use fst::IntoStreamer;
use heed::RwTxn;
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use maplit::hashset;
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use super::*;
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use crate::documents::documents_batch_reader_from_objects;
use crate::index::tests::TempIndex;
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use crate::search::TermsMatchingStrategy;
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use crate::update::Setting;
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use crate::{db_snap, Filter, Search};
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#[test]
fn simple_document_replacement() {
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let index = TempIndex::new();
// First we send 3 documents with ids from 1 to 3.
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index
.add_documents(documents!([
{ "id": 1, "name": "kevin" },
{ "id": 2, "name": "kevina" },
{ "id": 3, "name": "benoit" }
]))
.unwrap();
// Check that there is 3 documents now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 3);
drop(rtxn);
// Second we send 1 document with id 1, to erase the previous ones.
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index.add_documents(documents!([ { "id": 1, "name": "updated kevin" } ])).unwrap();
// Check that there is **always** 3 documents.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 3);
drop(rtxn);
// Third we send 3 documents again to replace the existing ones.
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index
.add_documents(documents!([
{ "id": 1, "name": "updated second kevin" },
{ "id": 2, "name": "updated kevina" },
{ "id": 3, "name": "updated benoit" }
]))
.unwrap();
// Check that there is **always** 3 documents.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 3);
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let count = index.all_documents(&rtxn).unwrap().count();
assert_eq!(count, 3);
drop(rtxn);
}
#[test]
fn simple_document_merge() {
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let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::UpdateDocuments;
// First we send 3 documents with duplicate ids and
// change the index method to merge documents.
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index
.add_documents(documents!([
{ "id": 1, "name": "kevin" },
{ "id": 1, "name": "kevina" },
{ "id": 1, "name": "benoit" }
]))
.unwrap();
// Check that there is only 1 document now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 1);
// Check that we get only one document from the database.
let docs = index.documents(&rtxn, Some(0)).unwrap();
assert_eq!(docs.len(), 1);
let (id, doc) = docs[0];
assert_eq!(id, 0);
// Check that this document is equal to the last one sent.
let mut doc_iter = doc.iter();
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assert_eq!(doc_iter.next(), Some((0, &b"1"[..])));
assert_eq!(doc_iter.next(), Some((1, &br#""benoit""#[..])));
assert_eq!(doc_iter.next(), None);
drop(rtxn);
// Second we send 1 document with id 1, to force it to be merged with the previous one.
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index.add_documents(documents!([ { "id": 1, "age": 25 } ])).unwrap();
// Check that there is **always** 1 document.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 1);
// Check that we get only one document from the database.
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let docs = index.documents(&rtxn, Some(0)).unwrap();
assert_eq!(docs.len(), 1);
let (id, doc) = docs[0];
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assert_eq!(id, 0);
// Check that this document is equal to the last one sent.
let mut doc_iter = doc.iter();
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assert_eq!(doc_iter.next(), Some((0, &b"1"[..])));
assert_eq!(doc_iter.next(), Some((1, &br#""benoit""#[..])));
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assert_eq!(doc_iter.next(), Some((2, &b"25"[..])));
assert_eq!(doc_iter.next(), None);
drop(rtxn);
}
#[test]
fn not_auto_generated_documents_ids() {
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let index = TempIndex::new();
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let result = index.add_documents(documents!([
{ "name": "kevin" },
{ "name": "kevina" },
{ "name": "benoit" }
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]));
assert!(result.is_err());
// Check that there is no document.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 0);
drop(rtxn);
}
#[test]
fn simple_auto_generated_documents_ids() {
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let mut index = TempIndex::new();
index.index_documents_config.autogenerate_docids = true;
// First we send 3 documents with ids from 1 to 3.
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index
.add_documents(documents!([
{ "name": "kevin" },
{ "name": "kevina" },
{ "name": "benoit" }
]))
.unwrap();
// Check that there is 3 documents now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 3);
let docs = index.documents(&rtxn, vec![0, 1, 2]).unwrap();
let (_id, obkv) = docs.iter().find(|(_id, kv)| kv.get(0) == Some(br#""kevin""#)).unwrap();
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let kevin_uuid: String = serde_json::from_slice(obkv.get(1).unwrap()).unwrap();
drop(rtxn);
// Second we send 1 document with the generated uuid, to erase the previous ones.
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index.add_documents(documents!([ { "name": "updated kevin", "id": kevin_uuid } ])).unwrap();
// Check that there is **always** 3 documents.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 3);
// the document 0 has been deleted and reinserted with the id 3
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let docs = index.documents(&rtxn, vec![1, 2, 0]).unwrap();
let kevin_position =
docs.iter().position(|(_, d)| d.get(0).unwrap() == br#""updated kevin""#).unwrap();
assert_eq!(kevin_position, 2);
let (_, doc) = docs[kevin_position];
// Check that this document is equal to the last
// one sent and that an UUID has been generated.
assert_eq!(doc.get(0), Some(&br#""updated kevin""#[..]));
// This is an UUID, it must be 36 bytes long plus the 2 surrounding string quotes (").
assert_eq!(doc.get(1).unwrap().len(), 36 + 2);
drop(rtxn);
}
#[test]
fn reordered_auto_generated_documents_ids() {
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let mut index = TempIndex::new();
// First we send 3 documents with ids from 1 to 3.
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index
.add_documents(documents!([
{ "id": 1, "name": "kevin" },
{ "id": 2, "name": "kevina" },
{ "id": 3, "name": "benoit" }
]))
.unwrap();
// Check that there is 3 documents now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 3);
drop(rtxn);
// Second we send 1 document without specifying the id.
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index.index_documents_config.autogenerate_docids = true;
index.add_documents(documents!([ { "name": "new kevin" } ])).unwrap();
// Check that there is 4 documents now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 4);
drop(rtxn);
}
#[test]
fn empty_update() {
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let index = TempIndex::new();
// First we send 0 documents and only headers.
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index.add_documents(documents!([])).unwrap();
// Check that there is no documents.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 0);
drop(rtxn);
}
#[test]
fn invalid_documents_ids() {
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let index = TempIndex::new();
// First we send 1 document with an invalid id.
// There is a space in the document id.
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index.add_documents(documents!([ { "id": "brume bleue", "name": "kevin" } ])).unwrap_err();
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// Then we send 1 document with a valid id.
index.add_documents(documents!([ { "id": 32, "name": "kevin" } ])).unwrap();
// Check that there is 1 document now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 1);
drop(rtxn);
}
#[test]
fn complex_documents() {
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let index = TempIndex::new();
// First we send 3 documents with an id for only one of them.
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index
.add_documents(documents!([
{ "id": 0, "name": "kevin", "object": { "key1": "value1", "key2": "value2" } },
{ "id": 1, "name": "kevina", "array": ["I", "am", "fine"] },
{ "id": 2, "name": "benoit", "array_of_object": [{ "wow": "amazing" }] }
]))
.unwrap();
// Check that there is 1 documents now.
let rtxn = index.read_txn().unwrap();
// Search for a sub object value
let result = index.search(&rtxn).query(r#""value2""#).execute().unwrap();
assert_eq!(result.documents_ids, vec![0]);
// Search for a sub array value
let result = index.search(&rtxn).query(r#""fine""#).execute().unwrap();
assert_eq!(result.documents_ids, vec![1]);
// Search for a sub array sub object key
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let result = index.search(&rtxn).query(r#""amazing""#).execute().unwrap();
assert_eq!(result.documents_ids, vec![2]);
drop(rtxn);
}
#[test]
fn simple_documents_replace() {
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let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::ReplaceDocuments;
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index.add_documents(documents!([
{ "id": 2, "title": "Pride and Prejudice", "author": "Jane Austin", "genre": "romance", "price": 3.5, "_geo": { "lat": 12, "lng": 42 } },
{ "id": 456, "title": "Le Petit Prince", "author": "Antoine de Saint-Exupéry", "genre": "adventure" , "price": 10.0 },
{ "id": 1, "title": "Alice In Wonderland", "author": "Lewis Carroll", "genre": "fantasy", "price": 25.99 },
{ "id": 1344, "title": "The Hobbit", "author": "J. R. R. Tolkien", "genre": "fantasy" },
{ "id": 4, "title": "Harry Potter and the Half-Blood Prince", "author": "J. K. Rowling", "genre": "fantasy" },
{ "id": 42, "title": "The Hitchhiker's Guide to the Galaxy", "author": "Douglas Adams", "_geo": { "lat": 35, "lng": 23 } }
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])).unwrap();
db_snap!(index, word_docids, "initial");
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index.index_documents_config.update_method = IndexDocumentsMethod::UpdateDocuments;
index
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.add_documents(documents!([
{"id":4,"title":"Harry Potter and the Half-Blood Princess"},
{"id":456,"title":"The Little Prince"}
]))
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.unwrap();
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index
.add_documents(documents!([
{ "id": 2, "author": "J. Austen", "date": "1813" }
]))
.unwrap();
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// Check that there is **always** 6 documents.
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let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 6);
let count = index.all_documents(&rtxn).unwrap().count();
assert_eq!(count, 6);
db_snap!(index, word_docids, "updated");
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drop(rtxn);
}
#[test]
fn mixed_geo_documents() {
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let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::ReplaceDocuments;
// We send 6 documents and mix the ones that have _geo and those that don't have it.
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index
.add_documents(documents!([
{ "id": 2, "price": 3.5, "_geo": { "lat": 12, "lng": 42 } },
{ "id": 456 },
{ "id": 1 },
{ "id": 1344 },
{ "id": 4 },
{ "id": 42, "_geo": { "lat": 35, "lng": 23 } }
]))
.unwrap();
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index
.update_settings(|settings| {
settings.set_filterable_fields(hashset!(S("_geo")));
})
.unwrap();
}
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#[test]
fn geo_error() {
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let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::ReplaceDocuments;
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index
.update_settings(|settings| {
settings.set_filterable_fields(hashset!(S("_geo")));
})
.unwrap();
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let error = index
.add_documents(documents!([
{ "id": 0, "_geo": { "lng": 42 } }
]))
.unwrap_err();
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assert_eq!(
&error.to_string(),
r#"Could not find latitude in the document with the id: `0`. Was expecting a `_geo.lat` field."#
);
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let error = index
.add_documents(documents!([
{ "id": 0, "_geo": { "lat": 42 } }
]))
.unwrap_err();
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assert_eq!(
&error.to_string(),
r#"Could not find longitude in the document with the id: `0`. Was expecting a `_geo.lng` field."#
);
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let error = index
.add_documents(documents!([
{ "id": 0, "_geo": { "lat": "lol", "lng": 42 } }
]))
.unwrap_err();
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assert_eq!(
&error.to_string(),
r#"Could not parse latitude in the document with the id: `0`. Was expecting a finite number but instead got `"lol"`."#
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);
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let error = index
.add_documents(documents!([
{ "id": 0, "_geo": { "lat": [12, 13], "lng": 42 } }
]))
.unwrap_err();
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assert_eq!(
&error.to_string(),
r#"Could not parse latitude in the document with the id: `0`. Was expecting a finite number but instead got `[12,13]`."#
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);
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let error = index
.add_documents(documents!([
{ "id": 0, "_geo": { "lat": 12, "lng": "hello" } }
]))
.unwrap_err();
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assert_eq!(
&error.to_string(),
r#"Could not parse longitude in the document with the id: `0`. Was expecting a finite number but instead got `"hello"`."#
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);
}
#[test]
fn delete_documents_then_insert() {
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let index = TempIndex::new();
index
.add_documents(documents!([
{ "objectId": 123, "title": "Pride and Prejudice", "comment": "A great book" },
{ "objectId": 456, "title": "Le Petit Prince", "comment": "A french book" },
{ "objectId": 1, "title": "Alice In Wonderland", "comment": "A weird book" },
{ "objectId": 30, "title": "Hamlet", "_geo": { "lat": 12, "lng": 89 } }
]))
.unwrap();
// Delete not all of the documents but some of them.
index.delete_document("30");
let txn = index.read_txn().unwrap();
assert_eq!(index.primary_key(&txn).unwrap(), Some("objectId"));
let external_documents_ids = index.external_documents_ids();
assert!(external_documents_ids.get(&txn, "30").unwrap().is_none());
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index
.add_documents(documents!([
{ "objectId": 30, "title": "Hamlet", "_geo": { "lat": 12, "lng": 89 } }
]))
.unwrap();
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let wtxn = index.write_txn().unwrap();
let external_documents_ids = index.external_documents_ids();
assert!(external_documents_ids.get(&wtxn, "30").unwrap().is_some());
wtxn.commit().unwrap();
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index
.add_documents(documents!([
{ "objectId": 30, "title": "Hamlet", "_geo": { "lat": 12, "lng": 89 } }
]))
.unwrap();
}
#[test]
fn index_more_than_256_fields() {
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let index = TempIndex::new();
let mut big_object = serde_json::Map::new();
big_object.insert(S("id"), serde_json::Value::from("wow"));
for i in 0..1000 {
let key = i.to_string();
big_object.insert(key, serde_json::Value::from("I am a text!"));
}
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let documents = documents_batch_reader_from_objects([big_object]);
index.add_documents(documents).unwrap();
}
#[test]
fn index_more_than_1000_positions_in_a_field() {
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let index = TempIndex::new_with_map_size(4096 * 100_000); // 400 MB
let mut content = String::with_capacity(382101);
for i in 0..=u16::MAX {
content.push_str(&format!("{i} "));
}
index
.add_documents(documents!({
"id": "wow",
"content": content
}))
.unwrap();
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let rtxn = index.read_txn().unwrap();
assert!(index.word_docids.get(&rtxn, "0").unwrap().is_some());
assert!(index.word_docids.get(&rtxn, "64").unwrap().is_some());
assert!(index.word_docids.get(&rtxn, "256").unwrap().is_some());
assert!(index.word_docids.get(&rtxn, "1024").unwrap().is_some());
assert!(index.word_docids.get(&rtxn, "32768").unwrap().is_some());
assert!(index.word_docids.get(&rtxn, "65535").unwrap().is_some());
}
#[test]
fn index_documents_with_zeroes() {
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let index = TempIndex::new();
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index
.add_documents(documents!([
{
"id": 2,
"title": "Prideand Prejudice",
"au{hor": "Jane Austin",
"genre": "romance",
"price$": "3.5$",
},
{
"id": 456,
"title": "Le Petit Prince",
"au{hor": "Antoine de Saint-Exupéry",
"genre": "adventure",
"price$": "10.0$",
},
{
"id": 1,
"title": "Wonderland",
"au{hor": "Lewis Carroll",
"genre": "fantasy",
"price$": "25.99$",
},
{
"id": 4,
"title": "Harry Potter ing fantasy\0lood Prince",
"au{hor": "J. K. Rowling",
"genre": "fantasy\0",
},
]))
.unwrap();
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}
#[test]
fn index_documents_with_nested_fields() {
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let index = TempIndex::new();
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index
.add_documents(documents!([
{
"id": 0,
"title": "The zeroth document",
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},
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{
"id": 1,
"title": "The first document",
"nested": {
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"object": "field",
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"machin": "bidule",
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},
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},
{
"id": 2,
"title": "The second document",
"nested": [
"array",
{
"object": "field",
},
{
"prout": "truc",
"machin": "lol",
},
],
},
{
"id": 3,
"title": "The third document",
"nested": "I lied",
},
]))
.unwrap();
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index
.update_settings(|settings| {
let searchable_fields = vec![S("title"), S("nested.object"), S("nested.machin")];
settings.set_searchable_fields(searchable_fields);
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let faceted_fields = hashset!(S("title"), S("nested.object"), S("nested.machin"));
settings.set_filterable_fields(faceted_fields);
})
.unwrap();
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let rtxn = index.read_txn().unwrap();
let facets = index.faceted_fields(&rtxn).unwrap();
assert_eq!(facets, hashset!(S("title"), S("nested.object"), S("nested.machin")));
// testing the simple query search
let mut search = crate::Search::new(&rtxn, &index);
search.query("document");
search.terms_matching_strategy(TermsMatchingStrategy::default());
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// all documents should be returned
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids.len(), 4);
search.query("zeroth");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![0]);
search.query("first");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![1]);
search.query("second");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![2]);
search.query("third");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![3]);
search.query("field");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![1, 2]);
search.query("lol");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![2]);
search.query("object");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert!(documents_ids.is_empty());
search.query("array");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert!(documents_ids.is_empty()); // nested is not searchable
search.query("lied");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert!(documents_ids.is_empty()); // nested is not searchable
// testing the filters
let mut search = crate::Search::new(&rtxn, &index);
search.filter(crate::Filter::from_str(r#"title = "The first document""#).unwrap().unwrap());
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![1]);
search.filter(crate::Filter::from_str(r#"nested.object = field"#).unwrap().unwrap());
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![1, 2]);
search.filter(crate::Filter::from_str(r#"nested.machin = bidule"#).unwrap().unwrap());
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![1]);
search.filter(crate::Filter::from_str(r#"nested = array"#).unwrap().unwrap());
let error = search.execute().map(|_| unreachable!()).unwrap_err(); // nested is not filterable
assert!(matches!(error, crate::Error::UserError(crate::UserError::InvalidFilter(_))));
search.filter(crate::Filter::from_str(r#"nested = "I lied""#).unwrap().unwrap());
let error = search.execute().map(|_| unreachable!()).unwrap_err(); // nested is not filterable
assert!(matches!(error, crate::Error::UserError(crate::UserError::InvalidFilter(_))));
}
#[test]
fn index_documents_with_nested_primary_key() {
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let index = TempIndex::new();
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index
.update_settings(|settings| {
settings.set_primary_key("complex.nested.id".to_owned());
})
.unwrap();
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index
.add_documents(documents!([
{
"complex": {
"nested": {
"id": 0,
},
},
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"title": "The zeroth document",
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},
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{
"complex.nested": {
"id": 1,
},
"title": "The first document",
},
{
"complex": {
"nested.id": 2,
},
"title": "The second document",
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},
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{
"complex.nested.id": 3,
"title": "The third document",
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},
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]))
.unwrap();
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let rtxn = index.read_txn().unwrap();
// testing the simple query search
let mut search = crate::Search::new(&rtxn, &index);
search.query("document");
search.terms_matching_strategy(TermsMatchingStrategy::default());
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// all documents should be returned
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids.len(), 4);
search.query("zeroth");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![0]);
search.query("first");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![1]);
search.query("second");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![2]);
search.query("third");
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![3]);
}
#[test]
fn retrieve_a_b_nested_document_id() {
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let index = TempIndex::new();
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index
.update_settings(|settings| {
settings.set_primary_key("a.b".to_owned());
})
.unwrap();
// There must be an issue with the primary key no present in the given document
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index.add_documents(documents!({ "a" : { "b" : { "c" : 1 }}})).unwrap_err();
}
#[test]
fn retrieve_a_b_c_nested_document_id() {
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let index = TempIndex::new();
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index
.update_settings(|settings| {
settings.set_primary_key("a.b.c".to_owned());
})
.unwrap();
index.add_documents(documents!({ "a" : { "b" : { "c" : 1 }}})).unwrap();
let rtxn = index.read_txn().unwrap();
let all_documents_count = index.all_documents(&rtxn).unwrap().count();
assert_eq!(all_documents_count, 1);
let external_documents_ids = index.external_documents_ids();
assert!(external_documents_ids.get(&rtxn, "1").unwrap().is_some());
}
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#[test]
fn test_facets_generation() {
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let index = TempIndex::new();
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index
.add_documents(documents!([
{
"id": 0,
"dog": {
"race": {
"bernese mountain": "zeroth",
},
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},
},
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{
"id": 1,
"dog.race": {
"bernese mountain": "first",
},
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},
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{
"id": 2,
"dog.race.bernese mountain": "second",
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},
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{
"id": 3,
"dog": {
"race.bernese mountain": "third"
},
},
]))
.unwrap();
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index
.update_settings(|settings| {
settings.set_filterable_fields(hashset!(String::from("dog")));
})
.unwrap();
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db_snap!(index, facet_id_string_docids, @r###"
3 0 first 1 [1, ]
3 0 second 1 [2, ]
3 0 third 1 [3, ]
3 0 zeroth 1 [0, ]
"###);
db_snap!(index, field_id_docid_facet_strings, @r###"
3 0 zeroth zeroth
3 1 first first
3 2 second second
3 3 third third
"###);
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let rtxn = index.read_txn().unwrap();
let hidden = index.faceted_fields(&rtxn).unwrap();
assert_eq!(hidden, hashset!(S("dog"), S("dog.race"), S("dog.race.bernese mountain")));
for (s, i) in [("zeroth", 0), ("first", 1), ("second", 2), ("third", 3)] {
let mut search = crate::Search::new(&rtxn, &index);
let filter = format!(r#""dog.race.bernese mountain" = {s}"#);
search.filter(crate::Filter::from_str(&filter).unwrap().unwrap());
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![i]);
}
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// Reset the settings
index
.update_settings(|settings| {
settings.reset_filterable_fields();
})
.unwrap();
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db_snap!(index, facet_id_string_docids, @"");
db_snap!(index, field_id_docid_facet_strings, @"");
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let rtxn = index.read_txn().unwrap();
let facets = index.faceted_fields(&rtxn).unwrap();
assert_eq!(facets, hashset!());
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// update the settings to test the sortable
index
.update_settings(|settings| {
settings.set_sortable_fields(hashset!(S("dog.race")));
})
.unwrap();
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db_snap!(index, facet_id_string_docids, @r###"
3 0 first 1 [1, ]
3 0 second 1 [2, ]
3 0 third 1 [3, ]
3 0 zeroth 1 [0, ]
"###);
db_snap!(index, field_id_docid_facet_strings, @r###"
3 0 zeroth zeroth
3 1 first first
3 2 second second
3 3 third third
"###);
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let rtxn = index.read_txn().unwrap();
let facets = index.faceted_fields(&rtxn).unwrap();
assert_eq!(facets, hashset!(S("dog.race"), S("dog.race.bernese mountain")));
let mut search = crate::Search::new(&rtxn, &index);
search.sort_criteria(vec![crate::AscDesc::Asc(crate::Member::Field(S(
"dog.race.bernese mountain",
)))]);
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids, vec![1, 2, 3, 0]);
}
#[test]
fn index_2_times_documents_split_by_zero_document_indexation() {
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let index = TempIndex::new();
index
.add_documents(documents!([
{"id": 0, "name": "Kerollmops", "score": 78},
{"id": 1, "name": "ManyTheFish", "score": 75},
{"id": 2, "name": "Ferdi", "score": 39},
{"id": 3, "name": "Tommy", "score": 33}
]))
.unwrap();
// Check that there is 4 document now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 4);
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index.add_documents(documents!([])).unwrap();
// Check that there is 4 document now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 4);
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index
.add_documents(documents!([
{"id": 0, "name": "Kerollmops", "score": 78},
{"id": 1, "name": "ManyTheFish", "score": 75},
{"id": 2, "name": "Ferdi", "score": 39},
{"id": 3, "name": "Tommy", "score": 33}
]))
.unwrap();
// Check that there is 4 document now.
let rtxn = index.read_txn().unwrap();
let count = index.number_of_documents(&rtxn).unwrap();
assert_eq!(count, 4);
}
#[cfg(feature = "chinese")]
#[test]
fn test_meilisearch_1714() {
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let index = TempIndex::new();
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index
.add_documents(documents!([
{"id": "123", "title": "小化妆包" },
{"id": "456", "title": "Ipad 包" }
]))
.unwrap();
let rtxn = index.read_txn().unwrap();
// Only the first document should match.
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let count = index.word_docids.get(&rtxn, "huàzhuāngbāo").unwrap().unwrap().len();
assert_eq!(count, 1);
// Only the second document should match.
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let count = index.word_docids.get(&rtxn, "bāo").unwrap().unwrap().len();
assert_eq!(count, 1);
let mut search = crate::Search::new(&rtxn, &index);
search.query("化妆包");
search.terms_matching_strategy(TermsMatchingStrategy::default());
// only 1 document should be returned
let crate::SearchResult { documents_ids, .. } = search.execute().unwrap();
assert_eq!(documents_ids.len(), 1);
}
/// We try to index documents with words that are too long here,
/// it should not return any error.
#[test]
fn text_with_too_long_words() {
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let index = TempIndex::new();
index
.add_documents(documents!([
{"id": 1, "title": "a".repeat(256) },
{"id": 2, "title": "b".repeat(512) },
{"id": 3, "title": format!("{} {}", "c".repeat(250), "d".repeat(250)) },
]))
.unwrap();
}
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#[test]
fn text_with_too_long_keys() {
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let index = TempIndex::new();
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let script = "https://bug.example.com/meilisearch/milli.saml2?ROLE=Programmer-1337&SAMLRequest=Cy1ytcZT1Po%2L2IY2y9Unru8rgnW4qWfPiI0EpT7P8xjJV8PeQikRL%2E8D9A4pj9tmbymbQCQwGmGjPMK7qwXFPX4DH52JO2b7n6TXjuR7zkIFuYdzdY2rwRNBPgCL7ihclEm9zyIjKZQ%2JTqiwfXxWjnI0KEYQYHdwd6Q%2Fx%28BDLNsvmL54CCY2F4RWeRs4eqWfn%2EHqxlhreFzax4AiQ2tgOtV5thOaaWqrhZD%2Py70nuyZWNTKwciGI43AoHg6PThANsQ5rAY5amzN%2ufbs1swETUXlLZuOut5YGpYPZfY6STJWNp4QYSUOUXBZpdElYsH7UHZ7VhJycgyt%28aTK0GW6GbKne2tJM0hgSczOqndg6RFa9WsnSBi4zMcaEfYur4WlSsHDYInF9ROousKqVMZ6H8%2gbUissaLh1eXRGo8KEJbyEHbhVVKGD%28kx4cfKjx9fT3pkeDTdvDrVn25jIzi9wHyt9l1lWc8ICnCvXCVUPP%2BjBG4wILR29gMV9Ux2QOieQm2%2Fycybhr8sBGCl30mHC7blvWt%2T3mrCHQoS3VK49PZNPqBZO9C7vOjOWoszNkJx4QckWV%2FZFvbpzUUkiBiehr9F%2FvQSxz9lzv68GwbTu9fr638p%2FQM%3D&RelayState=https%3A%2F%example.bug.com%2Fde&SigAlg=http%3A%2F%2Fwww.w3.org%2F2000%2F09%2Fxmldsig%23rsa-sha1&Signature=AZFpkhFFII7PodiewTovaGnLQKUVZp0qOCCcBIUkJ6P5by3lE3Lldj9pKaFu4wz4j%2B015HEhDvF0LlAmwwES85vdGh%2FpD%2cIQPRUEjdCbQkQDd3dy1mMXbpXxSe4QYcv9Ni7tqNTQxekpO1gE7rtg6zC66EU55uM9aj9abGQ034Vly%2F6IJ08bvAq%2B%2FB9KruLstuiNWnlXTfNGsOxGLK7%2BXr94LTkat8m%2FMan6Qr95%2KeR5TmmqaQIE4N9H6o4TopT7mXr5CF2Z3";
// Create 200 documents with a long text
let content = {
let documents_iter = (0..200i32)
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.map(|i| serde_json::json!({ "id": i, "script": script }))
.filter_map(|json| match json {
serde_json::Value::Object(object) => Some(object),
_ => None,
});
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documents_batch_reader_from_objects(documents_iter)
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};
// Index those 200 long documents
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index.add_documents(content).unwrap();
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// Index one long document
index
.add_documents(documents!([
{"id": 400, "script": script },
]))
.unwrap();
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}
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#[test]
fn index_documents_in_multiple_transforms() {
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let index = TempIndex::new();
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let doc1 = documents! {[{
"id": 228142,
"title": "asdsad",
"state": "automated",
"priority": "normal",
"public_uid": "37ccf021",
"project_id": 78207,
"branch_id_number": 0
}]};
let doc2 = documents! {[{
"id": 228143,
"title": "something",
"state": "automated",
"priority": "normal",
"public_uid": "39c6499b",
"project_id": 78207,
"branch_id_number": 0
}]};
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{
let mut wtxn = index.write_txn().unwrap();
index.put_primary_key(&mut wtxn, "id").unwrap();
wtxn.commit().unwrap();
}
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index.add_documents(doc1).unwrap();
index.add_documents(doc2).unwrap();
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let wtxn = index.read_txn().unwrap();
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let map = index.external_documents_ids().to_hash_map(&wtxn).unwrap();
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let ids = map.values().collect::<HashSet<_>>();
assert_eq!(ids.len(), map.len());
}
#[test]
fn index_documents_check_exists_database() {
let content = || {
documents!([
{
"id": 0,
"colour": 0,
},
{
"id": 1,
"colour": []
},
{
"id": 2,
"colour": {}
},
{
"id": 3,
"colour": null
},
{
"id": 4,
"colour": [1]
},
{
"id": 5
},
{
"id": 6,
"colour": {
"green": 1
}
},
{
"id": 7,
"colour": {
"green": {
"blue": []
}
}
}
])
};
let check_ok = |index: &Index| {
let rtxn = index.read_txn().unwrap();
let facets = index.faceted_fields(&rtxn).unwrap();
assert_eq!(facets, hashset!(S("colour"), S("colour.green"), S("colour.green.blue")));
let colour_id = index.fields_ids_map(&rtxn).unwrap().id("colour").unwrap();
let colour_green_id = index.fields_ids_map(&rtxn).unwrap().id("colour.green").unwrap();
let bitmap_colour =
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index.facet_id_exists_docids.get(&rtxn, &colour_id).unwrap().unwrap();
assert_eq!(bitmap_colour.into_iter().collect::<Vec<_>>(), vec![0, 1, 2, 3, 4, 6, 7]);
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let bitmap_colour_green =
index.facet_id_exists_docids.get(&rtxn, &colour_green_id).unwrap().unwrap();
assert_eq!(bitmap_colour_green.into_iter().collect::<Vec<_>>(), vec![6, 7]);
};
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let faceted_fields = hashset!(S("colour"));
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let index = TempIndex::new();
index.add_documents(content()).unwrap();
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index
.update_settings(|settings| {
settings.set_filterable_fields(faceted_fields.clone());
})
.unwrap();
check_ok(&index);
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let index = TempIndex::new();
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index
.update_settings(|settings| {
settings.set_filterable_fields(faceted_fields.clone());
})
.unwrap();
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index.add_documents(content()).unwrap();
check_ok(&index);
}
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#[test]
fn index_documents_check_is_null_database() {
let content = || {
documents!([
{
"id": 0,
"colour": null,
},
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{
"id": 1,
"colour": [null], // must not be returned
},
{
"id": 6,
"colour": {
"green": null
}
},
{
"id": 7,
"colour": {
"green": {
"blue": null
}
}
},
{
"id": 8,
"colour": 0,
},
{
"id": 9,
"colour": []
},
{
"id": 10,
"colour": {}
},
{
"id": 12,
"colour": [1]
},
{
"id": 13
},
{
"id": 14,
"colour": {
"green": 1
}
},
{
"id": 15,
"colour": {
"green": {
"blue": []
}
}
}
])
};
let check_ok = |index: &Index| {
let rtxn = index.read_txn().unwrap();
let facets = index.faceted_fields(&rtxn).unwrap();
assert_eq!(facets, hashset!(S("colour"), S("colour.green"), S("colour.green.blue")));
let colour_id = index.fields_ids_map(&rtxn).unwrap().id("colour").unwrap();
let colour_green_id = index.fields_ids_map(&rtxn).unwrap().id("colour.green").unwrap();
let colour_blue_id =
index.fields_ids_map(&rtxn).unwrap().id("colour.green.blue").unwrap();
let bitmap_null_colour =
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index.facet_id_is_null_docids.get(&rtxn, &colour_id).unwrap().unwrap();
assert_eq!(bitmap_null_colour.into_iter().collect::<Vec<_>>(), vec![0]);
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let bitmap_colour_green =
index.facet_id_is_null_docids.get(&rtxn, &colour_green_id).unwrap().unwrap();
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assert_eq!(bitmap_colour_green.into_iter().collect::<Vec<_>>(), vec![2]);
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let bitmap_colour_blue =
index.facet_id_is_null_docids.get(&rtxn, &colour_blue_id).unwrap().unwrap();
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assert_eq!(bitmap_colour_blue.into_iter().collect::<Vec<_>>(), vec![3]);
};
let faceted_fields = hashset!(S("colour"));
let index = TempIndex::new();
index.add_documents(content()).unwrap();
index
.update_settings(|settings| {
settings.set_filterable_fields(faceted_fields.clone());
})
.unwrap();
check_ok(&index);
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let index = TempIndex::new();
index
.update_settings(|settings| {
settings.set_filterable_fields(faceted_fields.clone());
})
.unwrap();
index.add_documents(content()).unwrap();
check_ok(&index);
}
#[test]
fn index_documents_check_is_empty_database() {
let content = || {
documents!([
{"id": 0, "tags": null },
{"id": 1, "tags": [null] },
{"id": 2, "tags": [] },
{"id": 3, "tags": ["hello","world"] },
{"id": 4, "tags": [""] },
{"id": 5 },
{"id": 6, "tags": {} },
{"id": 7, "tags": {"green": "cool"} },
{"id": 8, "tags": {"green": ""} },
{"id": 9, "tags": "" },
{"id": 10, "tags": { "green": null } },
{"id": 11, "tags": { "green": { "blue": null } } },
{"id": 12, "tags": { "green": { "blue": [] } } }
])
};
let check_ok = |index: &Index| {
let rtxn = index.read_txn().unwrap();
let facets = index.faceted_fields(&rtxn).unwrap();
assert_eq!(facets, hashset!(S("tags"), S("tags.green"), S("tags.green.blue")));
let tags_id = index.fields_ids_map(&rtxn).unwrap().id("tags").unwrap();
let tags_green_id = index.fields_ids_map(&rtxn).unwrap().id("tags.green").unwrap();
let tags_blue_id = index.fields_ids_map(&rtxn).unwrap().id("tags.green.blue").unwrap();
let bitmap_empty_tags =
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index.facet_id_is_empty_docids.get(&rtxn, &tags_id).unwrap().unwrap();
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assert_eq!(bitmap_empty_tags.into_iter().collect::<Vec<_>>(), vec![2, 6, 9]);
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let bitmap_tags_green =
index.facet_id_is_empty_docids.get(&rtxn, &tags_green_id).unwrap().unwrap();
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assert_eq!(bitmap_tags_green.into_iter().collect::<Vec<_>>(), vec![8]);
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let bitmap_tags_blue =
index.facet_id_is_empty_docids.get(&rtxn, &tags_blue_id).unwrap().unwrap();
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assert_eq!(bitmap_tags_blue.into_iter().collect::<Vec<_>>(), vec![12]);
};
let faceted_fields = hashset!(S("tags"));
let index = TempIndex::new();
index.add_documents(content()).unwrap();
index
.update_settings(|settings| {
settings.set_filterable_fields(faceted_fields.clone());
})
.unwrap();
check_ok(&index);
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let index = TempIndex::new();
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index
.update_settings(|settings| {
settings.set_filterable_fields(faceted_fields.clone());
})
.unwrap();
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index.add_documents(content()).unwrap();
check_ok(&index);
}
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#[test]
fn primary_key_must_not_contain_floats() {
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let index = TempIndex::new_with_map_size(4096 * 100);
let doc1 = documents! {[{
"id": -228142,
"title": "asdsad",
}]};
let doc2 = documents! {[{
"id": 228143.56,
"title": "something",
}]};
let doc3 = documents! {[{
"id": -228143.56,
"title": "something",
}]};
let doc4 = documents! {[{
"id": 2.0,
"title": "something",
}]};
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index.add_documents(doc1).unwrap();
index.add_documents(doc2).unwrap_err();
index.add_documents(doc3).unwrap_err();
index.add_documents(doc4).unwrap_err();
}
#[test]
fn primary_key_must_not_contain_whitespace() {
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let index = TempIndex::new();
let doc1 = documents! {[{
"id": " 1",
"title": "asdsad",
}]};
let doc2 = documents! {[{
"id": "\t2",
"title": "something",
}]};
let doc3 = documents! {[{
"id": "\r3",
"title": "something",
}]};
let doc4 = documents! {[{
"id": "\n4",
"title": "something",
}]};
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index.add_documents(doc1).unwrap_err();
index.add_documents(doc2).unwrap_err();
index.add_documents(doc3).unwrap_err();
index.add_documents(doc4).unwrap_err();
}
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#[test]
fn primary_key_inference() {
let index = TempIndex::new();
let doc_no_id = documents! {[{
"title": "asdsad",
"state": "automated",
"priority": "normal",
"branch_id_number": 0
}]};
assert!(matches!(
index.add_documents(doc_no_id),
Err(Error::UserError(UserError::NoPrimaryKeyCandidateFound))
));
let doc_multiple_ids = documents! {[{
"id": 228143,
"title": "something",
"state": "automated",
"priority": "normal",
"public_uid": "39c6499b",
"project_id": 78207,
"branch_id_number": 0
}]};
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let Err(Error::UserError(UserError::MultiplePrimaryKeyCandidatesFound { candidates })) =
index.add_documents(doc_multiple_ids)
else {
panic!("Expected Error::UserError(MultiplePrimaryKeyCandidatesFound)")
};
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assert_eq!(candidates, vec![S("id"), S("project_id"), S("public_uid"),]);
let doc_inferable = documents! {[{
"video": "test.mp4",
"id": 228143,
"title": "something",
"state": "automated",
"priority": "normal",
"public_uid_": "39c6499b",
"project_id_": 78207,
"branch_id_number": 0
}]};
index.add_documents(doc_inferable).unwrap();
let txn = index.read_txn().unwrap();
assert_eq!(index.primary_key(&txn).unwrap().unwrap(), "id");
}
#[test]
fn long_words_must_be_skipped() {
let index = TempIndex::new();
// this is obviousy too long
let long_word = "lol".repeat(1000);
let doc1 = documents! {[{
"id": "1",
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"title": long_word,
}]};
index.add_documents(doc1).unwrap();
let rtxn = index.read_txn().unwrap();
let words_fst = index.words_fst(&rtxn).unwrap();
assert!(!words_fst.contains(&long_word));
}
#[test]
fn long_facet_values_must_not_crash() {
let index = TempIndex::new();
// this is obviousy too long
let long_word = "lol".repeat(1000);
let doc1 = documents! {[{
"id": "1",
"title": long_word,
}]};
index
.update_settings(|settings| {
settings.set_filterable_fields(hashset! { S("title") });
})
.unwrap();
index.add_documents(doc1).unwrap();
}
#[cfg(feature = "default")]
#[test]
fn store_detected_script_and_language_per_document_during_indexing() {
use charabia::{Language, Script};
let index = TempIndex::new();
index
.add_documents(documents!([
{ "id": 1, "title": "The quick (\"brown\") fox can't jump 32.3 feet, right? Brr, it's 29.3°F!" },
{ "id": 2, "title": "人人生而自由﹐在尊嚴和權利上一律平等。他們賦有理性和良心﹐並應以兄弟關係的精神互相對待。" },
{ "id": 3, "title": "הַשּׁוּעָל הַמָּהִיר (״הַחוּם״) לֹא יָכוֹל לִקְפֹּץ 9.94 מֶטְרִים, נָכוֹן? ברר, 1.5°C- בַּחוּץ!" },
{ "id": 4, "title": "関西国際空港限定トートバッグ すもももももももものうち" },
{ "id": 5, "title": "ภาษาไทยง่ายนิดเดียว" },
{ "id": 6, "title": "The quick 在尊嚴和權利上一律平等。" },
]))
.unwrap();
let rtxn = index.read_txn().unwrap();
let key_jpn = (Script::Cj, Language::Jpn);
let key_cmn = (Script::Cj, Language::Cmn);
let cj_jpn_docs = index.script_language_documents_ids(&rtxn, &key_jpn).unwrap().unwrap();
let cj_cmn_docs = index.script_language_documents_ids(&rtxn, &key_cmn).unwrap().unwrap();
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let expected_cj_jpn_docids = [3].iter().collect();
assert_eq!(cj_jpn_docs, expected_cj_jpn_docids);
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let expected_cj_cmn_docids = [1, 5].iter().collect();
assert_eq!(cj_cmn_docs, expected_cj_cmn_docids);
}
#[test]
fn add_and_delete_documents_in_single_transform() {
let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::UpdateDocuments;
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let documents = documents!([
{ "id": 1, "doggo": "kevin" },
{ "id": 2, "doggo": { "name": "bob", "age": 20 } },
{ "id": 3, "name": "jean", "age": 25 },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"3");
let (builder, removed) = builder.remove_documents(vec![S("2")]).unwrap();
insta::assert_display_snapshot!(removed.unwrap(), @"1");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 3,
number_of_documents: 2,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":1,"doggo":"kevin"}
{"id":3,"name":"jean","age":25}
"###);
}
#[test]
fn add_update_and_delete_documents_in_single_transform() {
let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::UpdateDocuments;
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let documents = documents!([
{ "id": 1, "doggo": "kevin" },
{ "id": 2, "doggo": { "name": "bob", "age": 20 } },
{ "id": 3, "name": "jean", "age": 25 },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"3");
let documents = documents!([
{ "id": 2, "catto": "jorts" },
{ "id": 3, "legs": 4 },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"2");
let (builder, removed) = builder.remove_documents(vec![S("1"), S("2")]).unwrap();
insta::assert_display_snapshot!(removed.unwrap(), @"2");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 5,
number_of_documents: 1,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":3,"name":"jean","age":25,"legs":4}
"###);
}
#[test]
fn add_document_and_in_another_transform_update_and_delete_documents() {
let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::UpdateDocuments;
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let documents = documents!([
{ "id": 1, "doggo": "kevin" },
{ "id": 2, "doggo": { "name": "bob", "age": 20 } },
{ "id": 3, "name": "jean", "age": 25 },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"3");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 3,
number_of_documents: 3,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":1,"doggo":"kevin"}
{"id":2,"doggo":{"name":"bob","age":20}}
{"id":3,"name":"jean","age":25}
"###);
// A first batch of documents has been inserted
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let documents = documents!([
{ "id": 2, "catto": "jorts" },
{ "id": 3, "legs": 4 },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"2");
let (builder, removed) = builder.remove_documents(vec![S("1"), S("2")]).unwrap();
insta::assert_display_snapshot!(removed.unwrap(), @"2");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 2,
number_of_documents: 1,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":3,"name":"jean","age":25,"legs":4}
"###);
}
#[test]
fn delete_document_and_then_add_documents_in_the_same_transform() {
let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::UpdateDocuments;
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let (builder, removed) = builder.remove_documents(vec![S("1"), S("2")]).unwrap();
insta::assert_display_snapshot!(removed.unwrap(), @"0");
let documents = documents!([
{ "id": 2, "doggo": { "name": "jean", "age": 20 } },
{ "id": 3, "name": "bob", "age": 25 },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"2");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 2,
number_of_documents: 2,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":2,"doggo":{"name":"jean","age":20}}
{"id":3,"name":"bob","age":25}
"###);
}
#[test]
fn delete_the_same_document_multiple_time() {
let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::UpdateDocuments;
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let (builder, removed) =
builder.remove_documents(vec![S("1"), S("2"), S("1"), S("2")]).unwrap();
insta::assert_display_snapshot!(removed.unwrap(), @"0");
let documents = documents!([
{ "id": 1, "doggo": "kevin" },
{ "id": 2, "doggo": { "name": "jean", "age": 20 } },
{ "id": 3, "name": "bob", "age": 25 },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"3");
let (builder, removed) =
builder.remove_documents(vec![S("1"), S("2"), S("1"), S("2")]).unwrap();
insta::assert_display_snapshot!(removed.unwrap(), @"2");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 3,
number_of_documents: 1,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":3,"name":"bob","age":25}
"###);
}
#[test]
fn add_document_and_in_another_transform_delete_the_document_then_add_it_again() {
let mut index = TempIndex::new();
index.index_documents_config.update_method = IndexDocumentsMethod::UpdateDocuments;
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let documents = documents!([
{ "id": 1, "doggo": "kevin" },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"1");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 1,
number_of_documents: 1,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":1,"doggo":"kevin"}
"###);
// A first batch of documents has been inserted
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let (builder, removed) = builder.remove_documents(vec![S("1")]).unwrap();
insta::assert_display_snapshot!(removed.unwrap(), @"1");
let documents = documents!([
{ "id": 1, "catto": "jorts" },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"1");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 1,
number_of_documents: 1,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":1,"catto":"jorts"}
"###);
}
#[test]
fn test_word_fid_position() {
let index = TempIndex::new();
index
.add_documents(documents!([
{"id": 0, "text": "sun flowers are looking at the sun" },
{"id": 1, "text": "sun flowers are looking at the sun" },
{"id": 2, "text": "the sun is shining today" },
{
"id": 3,
"text": "a a a a a a a a a a a a a a a a a
a a a a a a a a a a a a a a a a a a a a a a a a a a
a a a a a a a a a a a a a a a a a a a a a a a a a a
a a a a a a a a a a a a a a a a a a a a a a a a a a
a a a a a a a a a a a a a a a a a a a a a a a a a a
a a a a a a a a a a a a a a a a a a a a a a a a a a
a a a a a a a a a a a a a a a a a a a a a "
}
]))
.unwrap();
db_snap!(index, word_fid_docids, 1, @"bf3355e493330de036c8823ddd1dbbd9");
db_snap!(index, word_position_docids, 1, @"896d54b29ed79c4c6f14084f326dcf6f");
index
.add_documents(documents!([
{"id": 4, "text": "sun flowers are looking at the sun" },
{"id": 5, "text2": "sun flowers are looking at the sun" },
{"id": 6, "text": "b b b" },
{
"id": 7,
"text2": "a a a a"
}
]))
.unwrap();
db_snap!(index, word_fid_docids, 2, @"a48d3f88db33f94bc23110a673ea49e4");
db_snap!(index, word_position_docids, 2, @"3c9e66c6768ae2cf42b46b2c46e46a83");
// Delete not all of the documents but some of them.
index.delete_documents(vec!["0".into(), "3".into()]);
db_snap!(index, word_fid_docids, 3, @"4c2e2a1832e5802796edc1638136d933");
db_snap!(index, word_position_docids, 3, @"74f556b91d161d997a89468b4da1cb8f");
}
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/// Index multiple different number of vectors in documents.
/// Vectors must be of the same length.
#[test]
fn test_multiple_vectors() {
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use crate::vector::settings::EmbeddingSettings;
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let index = TempIndex::new();
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index
.update_settings(|settings| {
let mut embedders = BTreeMap::default();
embedders.insert(
"manual".to_string(),
Setting::Set(EmbeddingSettings {
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source: Setting::Set(crate::vector::settings::EmbedderSource::UserProvided),
model: Setting::NotSet,
revision: Setting::NotSet,
api_key: Setting::NotSet,
dimensions: Setting::Set(3),
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document_template: Setting::NotSet,
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url: Setting::NotSet,
query: Setting::NotSet,
input_field: Setting::NotSet,
path_to_embeddings: Setting::NotSet,
embedding_object: Setting::NotSet,
input_type: Setting::NotSet,
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}),
);
settings.set_embedder_settings(embedders);
})
.unwrap();
index
.add_documents(
documents!([{"id": 0, "_vectors": { "manual": [[0, 1, 2], [3, 4, 5]] } }]),
)
.unwrap();
index.add_documents(documents!([{"id": 1, "_vectors": { "manual": [6, 7, 8] }}])).unwrap();
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index
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.add_documents(
documents!([{"id": 2, "_vectors": { "manual": [[9, 10, 11], [12, 13, 14], [15, 16, 17]] }}]),
)
.unwrap();
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let rtxn = index.read_txn().unwrap();
let res = index.search(&rtxn).vector([0.0, 1.0, 2.0].to_vec()).execute().unwrap();
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assert_eq!(res.documents_ids.len(), 3);
}
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#[test]
fn reproduce_the_bug() {
/*
[milli/examples/fuzz.rs:69] &batches = [
Batch(
[
AddDoc(
{ "id": 1, "doggo": "bernese" }, => internal 0
),
],
),
Batch(
[
DeleteDoc(
1, => delete internal 0
),
AddDoc(
{ "id": 0, "catto": "jorts" }, => internal 1
),
],
),
Batch(
[
AddDoc(
{ "id": 1, "catto": "jorts" }, => internal 2
),
],
),
]
*/
let index = TempIndex::new();
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// START OF BATCH
println!("--- ENTERING BATCH 1");
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
// OP
let documents = documents!([
{ "id": 1, "doggo": "bernese" },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"1");
// FINISHING
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 1,
number_of_documents: 1,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":1,"doggo":"bernese"}
"###);
db_snap!(index, external_documents_ids, @r###"
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docids:
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1 0
"###);
// A first batch of documents has been inserted
// BATCH 2
println!("--- ENTERING BATCH 2");
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let (builder, removed) = builder.remove_documents(vec![S("1")]).unwrap();
insta::assert_display_snapshot!(removed.unwrap(), @"1");
let documents = documents!([
{ "id": 0, "catto": "jorts" },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"1");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 1,
number_of_documents: 1,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":0,"catto":"jorts"}
"###);
db_snap!(index, external_documents_ids, @r###"
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docids:
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0 1
"###);
// BATCH 3
println!("--- ENTERING BATCH 3");
let mut wtxn = index.write_txn().unwrap();
let builder = IndexDocuments::new(
&mut wtxn,
&index,
&index.indexer_config,
index.index_documents_config.clone(),
|_| (),
|| false,
)
.unwrap();
let documents = documents!([
{ "id": 1, "catto": "jorts" },
]);
let (builder, added) = builder.add_documents(documents).unwrap();
insta::assert_display_snapshot!(added.unwrap(), @"1");
let addition = builder.execute().unwrap();
insta::assert_debug_snapshot!(addition, @r###"
DocumentAdditionResult {
indexed_documents: 1,
number_of_documents: 2,
}
"###);
wtxn.commit().unwrap();
db_snap!(index, documents, @r###"
{"id":1,"catto":"jorts"}
{"id":0,"catto":"jorts"}
"###);
// Ensuring all the returned IDs actually exists
let rtxn = index.read_txn().unwrap();
let res = index.search(&rtxn).execute().unwrap();
index.documents(&rtxn, res.documents_ids).unwrap();
}
fn delete_documents<'t>(
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wtxn: &mut RwTxn<'t>,
index: &'t TempIndex,
external_ids: &[&str],
) -> Vec<u32> {
let external_document_ids = index.external_documents_ids();
let ids_to_delete: Vec<u32> = external_ids
.iter()
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.map(|id| external_document_ids.get(wtxn, id).unwrap().unwrap())
.collect();
// Delete some documents.
index.delete_documents_using_wtxn(
wtxn,
external_ids.iter().map(ToString::to_string).collect(),
);
ids_to_delete
}
#[test]
fn delete_documents_with_numbers_as_primary_key() {
let index = TempIndex::new();
let mut wtxn = index.write_txn().unwrap();
index
.add_documents_using_wtxn(
&mut wtxn,
documents!([
{ "id": 0, "name": "kevin", "object": { "key1": "value1", "key2": "value2" } },
{ "id": 1, "name": "kevina", "array": ["I", "am", "fine"] },
{ "id": 2, "name": "benoit", "array_of_object": [{ "wow": "amazing" }] }
]),
)
.unwrap();
// delete those documents, ids are synchronous therefore 0, 1, and 2.
index.delete_documents_using_wtxn(&mut wtxn, vec![S("0"), S("1"), S("2")]);
wtxn.commit().unwrap();
// All these snapshots should be empty since the database was cleared
db_snap!(index, documents_ids);
db_snap!(index, word_docids);
db_snap!(index, word_pair_proximity_docids);
db_snap!(index, facet_id_exists_docids);
let rtxn = index.read_txn().unwrap();
assert!(index.field_distribution(&rtxn).unwrap().is_empty());
}
#[test]
fn delete_documents_with_strange_primary_key() {
let index = TempIndex::new();
index
.update_settings(|settings| settings.set_searchable_fields(vec!["name".to_string()]))
.unwrap();
let mut wtxn = index.write_txn().unwrap();
index
.add_documents_using_wtxn(
&mut wtxn,
documents!([
{ "mysuperid": 0, "name": "kevin" },
{ "mysuperid": 1, "name": "kevina" },
{ "mysuperid": 2, "name": "benoit" }
]),
)
.unwrap();
wtxn.commit().unwrap();
let mut wtxn = index.write_txn().unwrap();
// Delete not all of the documents but some of them.
index.delete_documents_using_wtxn(&mut wtxn, vec![S("0"), S("1")]);
wtxn.commit().unwrap();
db_snap!(index, documents_ids);
db_snap!(index, word_docids);
db_snap!(index, word_pair_proximity_docids);
}
#[test]
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fn filtered_placeholder_search_should_not_return_deleted_documents() {
let index = TempIndex::new();
let mut wtxn = index.write_txn().unwrap();
index
.update_settings_using_wtxn(&mut wtxn, |settings| {
settings.set_primary_key(S("docid"));
settings.set_filterable_fields(hashset! { S("label"), S("label2") });
})
.unwrap();
index
.add_documents_using_wtxn(
&mut wtxn,
documents!([
{ "docid": "1_4", "label": ["sign"] },
{ "docid": "1_5", "label": ["letter"] },
{ "docid": "1_7", "label": ["abstract","cartoon","design","pattern"] },
{ "docid": "1_36", "label": ["drawing","painting","pattern"] },
{ "docid": "1_37", "label": ["art","drawing","outdoor"] },
{ "docid": "1_38", "label": ["aquarium","art","drawing"] },
{ "docid": "1_39", "label": ["abstract"] },
{ "docid": "1_40", "label": ["cartoon"] },
{ "docid": "1_41", "label": ["art","drawing"] },
{ "docid": "1_42", "label": ["art","pattern"] },
{ "docid": "1_43", "label": ["abstract","art","drawing","pattern"] },
{ "docid": "1_44", "label": ["drawing"] },
{ "docid": "1_45", "label": ["art"] },
{ "docid": "1_46", "label": ["abstract","colorfulness","pattern"] },
{ "docid": "1_47", "label": ["abstract","pattern"] },
{ "docid": "1_52", "label": ["abstract","cartoon"] },
{ "docid": "1_57", "label": ["abstract","drawing","pattern"] },
{ "docid": "1_58", "label": ["abstract","art","cartoon"] },
{ "docid": "1_68", "label": ["design"] },
{ "docid": "1_69", "label": ["geometry"] },
{ "docid": "1_70", "label2": ["geometry", 1.2] },
{ "docid": "1_71", "label2": ["design", 2.2] },
{ "docid": "1_72", "label2": ["geometry", 1.2] }
]),
)
.unwrap();
delete_documents(&mut wtxn, &index, &["1_4", "1_70", "1_72"]);
// Placeholder search with filter
let filter = Filter::from_str("label = sign").unwrap().unwrap();
let results = index.search(&wtxn).filter(filter).execute().unwrap();
assert!(results.documents_ids.is_empty());
wtxn.commit().unwrap();
db_snap!(index, word_docids);
db_snap!(index, facet_id_f64_docids);
db_snap!(index, word_pair_proximity_docids);
db_snap!(index, facet_id_exists_docids);
db_snap!(index, facet_id_string_docids);
}
#[test]
fn placeholder_search_should_not_return_deleted_documents() {
let index = TempIndex::new();
let mut wtxn = index.write_txn().unwrap();
index
.update_settings_using_wtxn(&mut wtxn, |settings| {
settings.set_primary_key(S("docid"));
})
.unwrap();
index
.add_documents_using_wtxn(
&mut wtxn,
documents!([
{ "docid": "1_4", "label": ["sign"] },
{ "docid": "1_5", "label": ["letter"] },
{ "docid": "1_7", "label": ["abstract","cartoon","design","pattern"] },
{ "docid": "1_36", "label": ["drawing","painting","pattern"] },
{ "docid": "1_37", "label": ["art","drawing","outdoor"] },
{ "docid": "1_38", "label": ["aquarium","art","drawing"] },
{ "docid": "1_39", "label": ["abstract"] },
{ "docid": "1_40", "label": ["cartoon"] },
{ "docid": "1_41", "label": ["art","drawing"] },
{ "docid": "1_42", "label": ["art","pattern"] },
{ "docid": "1_43", "label": ["abstract","art","drawing","pattern"] },
{ "docid": "1_44", "label": ["drawing"] },
{ "docid": "1_45", "label": ["art"] },
{ "docid": "1_46", "label": ["abstract","colorfulness","pattern"] },
{ "docid": "1_47", "label": ["abstract","pattern"] },
{ "docid": "1_52", "label": ["abstract","cartoon"] },
{ "docid": "1_57", "label": ["abstract","drawing","pattern"] },
{ "docid": "1_58", "label": ["abstract","art","cartoon"] },
{ "docid": "1_68", "label": ["design"] },
{ "docid": "1_69", "label": ["geometry"] },
{ "docid": "1_70", "label2": ["geometry", 1.2] },
{ "docid": "1_71", "label2": ["design", 2.2] },
{ "docid": "1_72", "label2": ["geometry", 1.2] }
]),
)
.unwrap();
let deleted_internal_ids = delete_documents(&mut wtxn, &index, &["1_4"]);
// Placeholder search
let results = index.search(&wtxn).execute().unwrap();
assert!(!results.documents_ids.is_empty());
for id in results.documents_ids.iter() {
assert!(
!deleted_internal_ids.contains(id),
"The document {} was supposed to be deleted",
id
);
}
wtxn.commit().unwrap();
}
#[test]
fn search_should_not_return_deleted_documents() {
let index = TempIndex::new();
let mut wtxn = index.write_txn().unwrap();
index
.update_settings_using_wtxn(&mut wtxn, |settings| {
settings.set_primary_key(S("docid"));
})
.unwrap();
index
.add_documents_using_wtxn(
&mut wtxn,
documents!([
{ "docid": "1_4", "label": ["sign"] },
{ "docid": "1_5", "label": ["letter"] },
{ "docid": "1_7", "label": ["abstract","cartoon","design","pattern"] },
{ "docid": "1_36", "label": ["drawing","painting","pattern"] },
{ "docid": "1_37", "label": ["art","drawing","outdoor"] },
{ "docid": "1_38", "label": ["aquarium","art","drawing"] },
{ "docid": "1_39", "label": ["abstract"] },
{ "docid": "1_40", "label": ["cartoon"] },
{ "docid": "1_41", "label": ["art","drawing"] },
{ "docid": "1_42", "label": ["art","pattern"] },
{ "docid": "1_43", "label": ["abstract","art","drawing","pattern"] },
{ "docid": "1_44", "label": ["drawing"] },
{ "docid": "1_45", "label": ["art"] },
{ "docid": "1_46", "label": ["abstract","colorfulness","pattern"] },
{ "docid": "1_47", "label": ["abstract","pattern"] },
{ "docid": "1_52", "label": ["abstract","cartoon"] },
{ "docid": "1_57", "label": ["abstract","drawing","pattern"] },
{ "docid": "1_58", "label": ["abstract","art","cartoon"] },
{ "docid": "1_68", "label": ["design"] },
{ "docid": "1_69", "label": ["geometry"] },
{ "docid": "1_70", "label2": ["geometry", 1.2] },
{ "docid": "1_71", "label2": ["design", 2.2] },
{ "docid": "1_72", "label2": ["geometry", 1.2] }
]),
)
.unwrap();
let deleted_internal_ids = delete_documents(&mut wtxn, &index, &["1_7", "1_52"]);
// search for abstract
let results = index.search(&wtxn).query("abstract").execute().unwrap();
assert!(!results.documents_ids.is_empty());
for id in results.documents_ids.iter() {
assert!(
!deleted_internal_ids.contains(id),
"The document {} was supposed to be deleted",
id
);
}
wtxn.commit().unwrap();
}
#[test]
fn geo_filtered_placeholder_search_should_not_return_deleted_documents() {
let index = TempIndex::new();
let mut wtxn = index.write_txn().unwrap();
index
.update_settings_using_wtxn(&mut wtxn, |settings| {
settings.set_primary_key(S("id"));
settings.set_filterable_fields(hashset!(S("_geo")));
settings.set_sortable_fields(hashset!(S("_geo")));
})
.unwrap();
index.add_documents_using_wtxn(&mut wtxn, documents!([
{ "id": "1", "city": "Lille", "_geo": { "lat": 50.6299, "lng": 3.0569 } },
{ "id": "2", "city": "Mons-en-Barœul", "_geo": { "lat": 50.6415, "lng": 3.1106 } },
{ "id": "3", "city": "Hellemmes", "_geo": { "lat": 50.6312, "lng": 3.1106 } },
{ "id": "4", "city": "Villeneuve-d'Ascq", "_geo": { "lat": 50.6224, "lng": 3.1476 } },
{ "id": "5", "city": "Hem", "_geo": { "lat": 50.6552, "lng": 3.1897 } },
{ "id": "6", "city": "Roubaix", "_geo": { "lat": 50.6924, "lng": 3.1763 } },
{ "id": "7", "city": "Tourcoing", "_geo": { "lat": 50.7263, "lng": 3.1541 } },
{ "id": "8", "city": "Mouscron", "_geo": { "lat": 50.7453, "lng": 3.2206 } },
{ "id": "9", "city": "Tournai", "_geo": { "lat": 50.6053, "lng": 3.3758 } },
{ "id": "10", "city": "Ghent", "_geo": { "lat": 51.0537, "lng": 3.6957 } },
{ "id": "11", "city": "Brussels", "_geo": { "lat": 50.8466, "lng": 4.3370 } },
{ "id": "12", "city": "Charleroi", "_geo": { "lat": 50.4095, "lng": 4.4347 } },
{ "id": "13", "city": "Mons", "_geo": { "lat": 50.4502, "lng": 3.9623 } },
{ "id": "14", "city": "Valenciennes", "_geo": { "lat": 50.3518, "lng": 3.5326 } },
{ "id": "15", "city": "Arras", "_geo": { "lat": 50.2844, "lng": 2.7637 } },
{ "id": "16", "city": "Cambrai", "_geo": { "lat": 50.1793, "lng": 3.2189 } },
{ "id": "17", "city": "Bapaume", "_geo": { "lat": 50.1112, "lng": 2.8547 } },
{ "id": "18", "city": "Amiens", "_geo": { "lat": 49.9314, "lng": 2.2710 } },
{ "id": "19", "city": "Compiègne", "_geo": { "lat": 49.4449, "lng": 2.7913 } },
{ "id": "20", "city": "Paris", "_geo": { "lat": 48.9021, "lng": 2.3708 } }
])).unwrap();
let external_ids_to_delete = ["5", "6", "7", "12", "17", "19"];
let deleted_internal_ids = delete_documents(&mut wtxn, &index, &external_ids_to_delete);
// Placeholder search with geo filter
let filter = Filter::from_str("_geoRadius(50.6924, 3.1763, 20000)").unwrap().unwrap();
let results = index.search(&wtxn).filter(filter).execute().unwrap();
assert!(!results.documents_ids.is_empty());
for id in results.documents_ids.iter() {
assert!(
!deleted_internal_ids.contains(id),
"The document {} was supposed to be deleted",
id
);
}
wtxn.commit().unwrap();
db_snap!(index, facet_id_f64_docids);
db_snap!(index, facet_id_string_docids);
}
#[test]
fn get_documents_should_not_return_deleted_documents() {
let index = TempIndex::new();
let mut wtxn = index.write_txn().unwrap();
index
.update_settings_using_wtxn(&mut wtxn, |settings| {
settings.set_primary_key(S("docid"));
})
.unwrap();
index
.add_documents_using_wtxn(
&mut wtxn,
documents!([
{ "docid": "1_4", "label": ["sign"] },
{ "docid": "1_5", "label": ["letter"] },
{ "docid": "1_7", "label": ["abstract","cartoon","design","pattern"] },
{ "docid": "1_36", "label": ["drawing","painting","pattern"] },
{ "docid": "1_37", "label": ["art","drawing","outdoor"] },
{ "docid": "1_38", "label": ["aquarium","art","drawing"] },
{ "docid": "1_39", "label": ["abstract"] },
{ "docid": "1_40", "label": ["cartoon"] },
{ "docid": "1_41", "label": ["art","drawing"] },
{ "docid": "1_42", "label": ["art","pattern"] },
{ "docid": "1_43", "label": ["abstract","art","drawing","pattern"] },
{ "docid": "1_44", "label": ["drawing"] },
{ "docid": "1_45", "label": ["art"] },
{ "docid": "1_46", "label": ["abstract","colorfulness","pattern"] },
{ "docid": "1_47", "label": ["abstract","pattern"] },
{ "docid": "1_52", "label": ["abstract","cartoon"] },
{ "docid": "1_57", "label": ["abstract","drawing","pattern"] },
{ "docid": "1_58", "label": ["abstract","art","cartoon"] },
{ "docid": "1_68", "label": ["design"] },
{ "docid": "1_69", "label": ["geometry"] },
{ "docid": "1_70", "label2": ["geometry", 1.2] },
{ "docid": "1_71", "label2": ["design", 2.2] },
{ "docid": "1_72", "label2": ["geometry", 1.2] }
]),
)
.unwrap();
let deleted_external_ids = ["1_7", "1_52"];
let deleted_internal_ids = delete_documents(&mut wtxn, &index, &deleted_external_ids);
// list all documents
let results = index.all_documents(&wtxn).unwrap();
for result in results {
let (id, _) = result.unwrap();
assert!(
!deleted_internal_ids.contains(&id),
"The document {} was supposed to be deleted",
id
);
}
// list internal document ids
let results = index.documents_ids(&wtxn).unwrap();
for id in results {
assert!(
!deleted_internal_ids.contains(&id),
"The document {} was supposed to be deleted",
id
);
}
wtxn.commit().unwrap();
let rtxn = index.read_txn().unwrap();
// get internal docids from deleted external document ids
let results = index.external_documents_ids();
for id in deleted_external_ids {
assert!(
results.get(&rtxn, id).unwrap().is_none(),
"The document {} was supposed to be deleted",
id
);
}
drop(rtxn);
}
#[test]
fn stats_should_not_return_deleted_documents() {
let index = TempIndex::new();
let mut wtxn = index.write_txn().unwrap();
index
.update_settings_using_wtxn(&mut wtxn, |settings| {
settings.set_primary_key(S("docid"));
})
.unwrap();
index.add_documents_using_wtxn(&mut wtxn, documents!([
{ "docid": "1_4", "label": ["sign"]},
{ "docid": "1_5", "label": ["letter"]},
{ "docid": "1_7", "label": ["abstract","cartoon","design","pattern"], "title": "Mickey Mouse"},
{ "docid": "1_36", "label": ["drawing","painting","pattern"]},
{ "docid": "1_37", "label": ["art","drawing","outdoor"]},
{ "docid": "1_38", "label": ["aquarium","art","drawing"], "title": "Nemo"},
{ "docid": "1_39", "label": ["abstract"]},
{ "docid": "1_40", "label": ["cartoon"]},
{ "docid": "1_41", "label": ["art","drawing"]},
{ "docid": "1_42", "label": ["art","pattern"]},
{ "docid": "1_43", "label": ["abstract","art","drawing","pattern"], "number": 32i32},
{ "docid": "1_44", "label": ["drawing"], "number": 44i32},
{ "docid": "1_45", "label": ["art"]},
{ "docid": "1_46", "label": ["abstract","colorfulness","pattern"]},
{ "docid": "1_47", "label": ["abstract","pattern"]},
{ "docid": "1_52", "label": ["abstract","cartoon"]},
{ "docid": "1_57", "label": ["abstract","drawing","pattern"]},
{ "docid": "1_58", "label": ["abstract","art","cartoon"]},
{ "docid": "1_68", "label": ["design"]},
{ "docid": "1_69", "label": ["geometry"]}
])).unwrap();
delete_documents(&mut wtxn, &index, &["1_7", "1_52"]);
// count internal documents
let results = index.number_of_documents(&wtxn).unwrap();
assert_eq!(18, results);
// count field distribution
let results = index.field_distribution(&wtxn).unwrap();
assert_eq!(Some(&18), results.get("label"));
assert_eq!(Some(&1), results.get("title"));
assert_eq!(Some(&2), results.get("number"));
wtxn.commit().unwrap();
}
#[test]
fn stored_detected_script_and_language_should_not_return_deleted_documents() {
use charabia::{Language, Script};
let index = TempIndex::new();
let mut wtxn = index.write_txn().unwrap();
index
.add_documents_using_wtxn(
&mut wtxn,
documents!([
{ "id": "0", "title": "The quick (\"brown\") fox can't jump 32.3 feet, right? Brr, it's 29.3°F!" },
{ "id": "1", "title": "人人生而自由﹐在尊嚴和權利上一律平等。他們賦有理性和良心﹐並應以兄弟關係的精神互相對待。" },
{ "id": "2", "title": "הַשּׁוּעָל הַמָּהִיר (״הַחוּם״) לֹא יָכוֹל לִקְפֹּץ 9.94 מֶטְרִים, נָכוֹן? ברר, 1.5°C- בַּחוּץ!" },
{ "id": "3", "title": "関西国際空港限定トートバッグ すもももももももものうち" },
{ "id": "4", "title": "ภาษาไทยง่ายนิดเดียว" },
{ "id": "5", "title": "The quick 在尊嚴和權利上一律平等。" },
]))
.unwrap();
let key_cmn = (Script::Cj, Language::Cmn);
let cj_cmn_docs =
index.script_language_documents_ids(&wtxn, &key_cmn).unwrap().unwrap_or_default();
let mut expected_cj_cmn_docids = RoaringBitmap::new();
expected_cj_cmn_docids.push(1);
expected_cj_cmn_docids.push(5);
assert_eq!(cj_cmn_docs, expected_cj_cmn_docids);
delete_documents(&mut wtxn, &index, &["1"]);
wtxn.commit().unwrap();
let rtxn = index.read_txn().unwrap();
let cj_cmn_docs =
index.script_language_documents_ids(&rtxn, &key_cmn).unwrap().unwrap_or_default();
let mut expected_cj_cmn_docids = RoaringBitmap::new();
expected_cj_cmn_docids.push(5);
assert_eq!(cj_cmn_docs, expected_cj_cmn_docids);
}
#[test]
fn delete_words_exact_attributes() {
let index = TempIndex::new();
index
.update_settings(|settings| {
settings.set_primary_key(S("id"));
settings.set_searchable_fields(vec![S("text"), S("exact")]);
settings.set_exact_attributes(vec![S("exact")].into_iter().collect());
})
.unwrap();
index
.add_documents(documents!([
{ "id": 0, "text": "hello" },
{ "id": 1, "exact": "hello"}
]))
.unwrap();
db_snap!(index, word_docids, 1, @r###"
hello [0, ]
"###);
db_snap!(index, exact_word_docids, 1, @r###"
hello [1, ]
"###);
db_snap!(index, words_fst, 1, @"300000000000000001084cfcfc2ce1000000016000000090ea47f");
let mut wtxn = index.write_txn().unwrap();
let deleted_internal_ids = delete_documents(&mut wtxn, &index, &["1"]);
wtxn.commit().unwrap();
db_snap!(index, word_docids, 2, @r###"
hello [0, ]
"###);
db_snap!(index, exact_word_docids, 2, @"");
db_snap!(index, words_fst, 2, @"300000000000000001084cfcfc2ce1000000016000000090ea47f");
insta::assert_snapshot!(format!("{deleted_internal_ids:?}"), @"[1]");
let txn = index.read_txn().unwrap();
let words = index.words_fst(&txn).unwrap().into_stream().into_strs().unwrap();
insta::assert_snapshot!(format!("{words:?}"), @r###"["hello"]"###);
let mut s = Search::new(&txn, &index);
s.query("hello");
let crate::SearchResult { documents_ids, .. } = s.execute().unwrap();
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[0]");
}
}