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Author | SHA1 | Date | |
---|---|---|---|
14a980e54e | |||
cbc453c6d1 | |||
2fb065b9fb | |||
07f42e8057 | |||
71f59749dc | |||
3b0b9967f6 | |||
123b54a178 | |||
f5dd8dfc3e | |||
bcfed70888 | |||
503ef3bbc9 | |||
08f2c696b0 | |||
b75f1f4c17 | |||
95ed079761 | |||
4a082683df | |||
26be5e0733 | |||
bd5110a2fe | |||
fa8b9acdf6 | |||
2b74d1824b | |||
c77b00d3ac | |||
c77073efcc | |||
1537323eb9 | |||
a0a3b55700 | |||
214b51de87 | |||
95975944d7 | |||
7a2af06b1e | |||
cb0c3a5aad | |||
cbcf6c9ba3 | |||
bf742d81cf | |||
fc1df5793c | |||
953a82ca04 |
@ -29,7 +29,6 @@ use bumpalo::collections::CollectIn;
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use bumpalo::Bump;
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use dump::IndexMetadata;
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use meilisearch_types::batches::BatchId;
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use meilisearch_types::error::Code;
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use meilisearch_types::heed::{RoTxn, RwTxn};
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use meilisearch_types::milli::documents::{obkv_to_object, DocumentsBatchReader, PrimaryKey};
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use meilisearch_types::milli::heed::CompactionOption;
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@ -497,7 +496,6 @@ impl IndexScheduler {
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// 5. We make a batch from the unprioritised tasks. Start by taking the next enqueued task.
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let task_id = if let Some(task_id) = enqueued.min() { task_id } else { return Ok(None) };
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let mut task = self.get_task(rtxn, task_id)?.ok_or(Error::CorruptedTaskQueue)?;
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current_batch.processing(Some(&mut task));
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// If the task is not associated with any index, verify that it is an index swap and
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// create the batch directly. Otherwise, get the index name associated with the task
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@ -507,6 +505,7 @@ impl IndexScheduler {
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index_name
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} else {
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assert!(matches!(&task.kind, KindWithContent::IndexSwap { swaps } if swaps.is_empty()));
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current_batch.processing(Some(&mut task));
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return Ok(Some((Batch::IndexSwap { task }, current_batch)));
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};
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@ -689,7 +688,9 @@ impl IndexScheduler {
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let index = self.index_mapper.index(&rtxn, name)?;
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let dst = temp_snapshot_dir.path().join("indexes").join(uuid.to_string());
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fs::create_dir_all(&dst)?;
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index.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)?;
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index
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.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)
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.map_err(|e| Error::from_milli(e, Some(name.to_string())))?;
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}
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drop(rtxn);
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@ -791,16 +792,19 @@ impl IndexScheduler {
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let content_file = self.file_store.get_update(content_file)?;
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let reader = DocumentsBatchReader::from_reader(content_file)
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.map_err(milli::Error::from)?;
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.map_err(|e| Error::from_milli(e.into(), None))?;
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let (mut cursor, documents_batch_index) =
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reader.into_cursor_and_fields_index();
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while let Some(doc) =
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cursor.next_document().map_err(milli::Error::from)?
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while let Some(doc) = cursor
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.next_document()
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.map_err(|e| Error::from_milli(e.into(), None))?
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{
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dump_content_file
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.push_document(&obkv_to_object(doc, &documents_batch_index)?)?;
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dump_content_file.push_document(
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&obkv_to_object(doc, &documents_batch_index)
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.map_err(|e| Error::from_milli(e, None))?,
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)?;
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}
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dump_content_file.flush()?;
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}
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@ -814,27 +818,41 @@ impl IndexScheduler {
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let metadata = IndexMetadata {
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uid: uid.to_owned(),
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primary_key: index.primary_key(&rtxn)?.map(String::from),
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created_at: index.created_at(&rtxn)?,
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updated_at: index.updated_at(&rtxn)?,
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created_at: index
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.created_at(&rtxn)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
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updated_at: index
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.updated_at(&rtxn)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
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};
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let mut index_dumper = dump.create_index(uid, &metadata)?;
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let fields_ids_map = index.fields_ids_map(&rtxn)?;
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let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
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let embedding_configs = index.embedding_configs(&rtxn)?;
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let embedding_configs = index
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.embedding_configs(&rtxn)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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let documents = index
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.all_documents(&rtxn)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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// 3.1. Dump the documents
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for ret in index.all_documents(&rtxn)? {
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for ret in documents {
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if self.must_stop_processing.get() {
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return Err(Error::AbortedTask);
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}
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let (id, doc) = ret?;
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let (id, doc) =
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ret.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, doc)?;
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let mut document =
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milli::obkv_to_json(&all_fields, &fields_ids_map, doc)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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'inject_vectors: {
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let embeddings = index.embeddings(&rtxn, id)?;
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let embeddings = index
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.embeddings(&rtxn, id)
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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if embeddings.is_empty() {
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break 'inject_vectors;
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@ -845,7 +863,7 @@ impl IndexScheduler {
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.or_insert(serde_json::Value::Object(Default::default()));
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let serde_json::Value::Object(vectors) = vectors else {
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return Err(milli::Error::UserError(
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let user_err = milli::Error::UserError(
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milli::UserError::InvalidVectorsMapType {
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document_id: {
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if let Ok(Some(Ok(index))) = index
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@ -859,8 +877,9 @@ impl IndexScheduler {
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},
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value: vectors.clone(),
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},
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)
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.into());
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);
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return Err(Error::from_milli(user_err, Some(uid.to_string())));
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};
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for (embedder_name, embeddings) in embeddings {
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@ -890,7 +909,8 @@ impl IndexScheduler {
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index,
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&rtxn,
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||||
meilisearch_types::settings::SecretPolicy::RevealSecrets,
|
||||
)?;
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||||
)
|
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.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?;
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index_dumper.settings(&settings)?;
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Ok(())
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})?;
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@ -946,7 +966,8 @@ impl IndexScheduler {
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// the entire batch.
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let res = || -> Result<()> {
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let index_rtxn = index.read_txn()?;
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let stats = crate::index_mapper::IndexStats::new(&index, &index_rtxn)?;
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let stats = crate::index_mapper::IndexStats::new(&index, &index_rtxn)
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.map_err(|e| Error::from_milli(e, Some(index_uid.to_string())))?;
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let mut wtxn = self.env.write_txn()?;
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self.index_mapper.store_stats_of(&mut wtxn, &index_uid, &stats)?;
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wtxn.commit()?;
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@ -988,10 +1009,12 @@ impl IndexScheduler {
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);
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builder.set_primary_key(primary_key);
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let must_stop_processing = self.must_stop_processing.clone();
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builder.execute(
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|indexing_step| tracing::debug!(update = ?indexing_step),
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|| must_stop_processing.get(),
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)?;
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builder
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.execute(
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|indexing_step| tracing::debug!(update = ?indexing_step),
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|| must_stop_processing.get(),
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)
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.map_err(|e| Error::from_milli(e, Some(index_uid.to_string())))?;
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index_wtxn.commit()?;
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}
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@ -1008,7 +1031,8 @@ impl IndexScheduler {
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let res = || -> Result<()> {
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let mut wtxn = self.env.write_txn()?;
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let index_rtxn = index.read_txn()?;
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let stats = crate::index_mapper::IndexStats::new(&index, &index_rtxn)?;
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let stats = crate::index_mapper::IndexStats::new(&index, &index_rtxn)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
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self.index_mapper.store_stats_of(&mut wtxn, &index_uid, &stats)?;
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wtxn.commit()?;
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Ok(())
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@ -1031,7 +1055,9 @@ impl IndexScheduler {
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let number_of_documents = || -> Result<u64> {
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let index = self.index_mapper.index(&wtxn, &index_uid)?;
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let index_rtxn = index.read_txn()?;
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Ok(index.number_of_documents(&index_rtxn)?)
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index
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.number_of_documents(&index_rtxn)
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.map_err(|e| Error::from_milli(e, Some(index_uid.to_string())))
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}()
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.unwrap_or_default();
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@ -1188,8 +1214,10 @@ impl IndexScheduler {
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};
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match operation {
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IndexOperation::DocumentClear { mut tasks, .. } => {
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let count = milli::update::ClearDocuments::new(index_wtxn, index).execute()?;
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IndexOperation::DocumentClear { index_uid, mut tasks } => {
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let count = milli::update::ClearDocuments::new(index_wtxn, index)
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.execute()
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.map_err(|e| Error::from_milli(e, Some(index_uid)))?;
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let mut first_clear_found = false;
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for task in &mut tasks {
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@ -1209,7 +1237,7 @@ impl IndexScheduler {
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Ok(tasks)
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}
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IndexOperation::DocumentOperation {
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index_uid: _,
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index_uid,
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primary_key,
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method,
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operations,
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@ -1235,13 +1263,17 @@ impl IndexScheduler {
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let mut content_files_iter = content_files.iter();
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let mut indexer = indexer::DocumentOperation::new(method);
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let embedders = index.embedding_configs(index_wtxn)?;
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let embedders = self.embedders(embedders)?;
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let embedders = index
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.embedding_configs(index_wtxn)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
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let embedders = self.embedders(index_uid.clone(), embedders)?;
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for operation in operations {
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match operation {
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DocumentOperation::Add(_content_uuid) => {
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let mmap = content_files_iter.next().unwrap();
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indexer.add_documents(mmap)?;
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indexer
|
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.add_documents(mmap)
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.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
|
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}
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DocumentOperation::Delete(document_ids) => {
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let document_ids: bumpalo::collections::vec::Vec<_> = document_ids
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@ -1266,15 +1298,17 @@ impl IndexScheduler {
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}
|
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};
|
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let (document_changes, operation_stats, primary_key) = indexer.into_changes(
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&indexer_alloc,
|
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index,
|
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&rtxn,
|
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primary_key.as_deref(),
|
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&mut new_fields_ids_map,
|
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&|| must_stop_processing.get(),
|
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&send_progress,
|
||||
)?;
|
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let (document_changes, operation_stats, primary_key) = indexer
|
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.into_changes(
|
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&indexer_alloc,
|
||||
index,
|
||||
&rtxn,
|
||||
primary_key.as_deref(),
|
||||
&mut new_fields_ids_map,
|
||||
&|| must_stop_processing.get(),
|
||||
&send_progress,
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
|
||||
|
||||
let mut addition = 0;
|
||||
for (stats, task) in operation_stats.into_iter().zip(&mut tasks) {
|
||||
@ -1321,14 +1355,15 @@ impl IndexScheduler {
|
||||
embedders,
|
||||
&|| must_stop_processing.get(),
|
||||
&send_progress,
|
||||
)?;
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(index_uid.clone())))?;
|
||||
|
||||
tracing::info!(indexing_result = ?addition, processed_in = ?started_processing_at.elapsed(), "document indexing done");
|
||||
}
|
||||
|
||||
Ok(tasks)
|
||||
}
|
||||
IndexOperation::DocumentEdition { mut task, .. } => {
|
||||
IndexOperation::DocumentEdition { index_uid, mut task } => {
|
||||
let (filter, code) = if let KindWithContent::DocumentEdition {
|
||||
filter_expr,
|
||||
context: _,
|
||||
@ -1342,16 +1377,11 @@ impl IndexScheduler {
|
||||
};
|
||||
|
||||
let candidates = match filter.as_ref().map(Filter::from_json) {
|
||||
Some(Ok(Some(filter))) => {
|
||||
filter.evaluate(index_wtxn, index).map_err(|err| match err {
|
||||
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
|
||||
Error::from(err).with_custom_error_code(Code::InvalidDocumentFilter)
|
||||
}
|
||||
e => e.into(),
|
||||
})?
|
||||
}
|
||||
Some(Ok(Some(filter))) => filter
|
||||
.evaluate(index_wtxn, index)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())))?,
|
||||
None | Some(Ok(None)) => index.documents_ids(index_wtxn)?,
|
||||
Some(Err(e)) => return Err(e.into()),
|
||||
Some(Err(e)) => return Err(Error::from_milli(e, Some(index_uid.clone()))),
|
||||
};
|
||||
|
||||
let (original_filter, context, function) = if let Some(Details::DocumentEdition {
|
||||
@ -1386,8 +1416,9 @@ impl IndexScheduler {
|
||||
// candidates not empty => index not empty => a primary key is set
|
||||
let primary_key = index.primary_key(&rtxn)?.unwrap();
|
||||
|
||||
let primary_key = PrimaryKey::new_or_insert(primary_key, &mut new_fields_ids_map)
|
||||
.map_err(milli::Error::from)?;
|
||||
let primary_key =
|
||||
PrimaryKey::new_or_insert(primary_key, &mut new_fields_ids_map)
|
||||
.map_err(|err| Error::from_milli(err.into(), Some(index_uid.clone())))?;
|
||||
|
||||
let result_count = Ok((candidates.len(), candidates.len())) as Result<_>;
|
||||
|
||||
@ -1406,11 +1437,17 @@ impl IndexScheduler {
|
||||
};
|
||||
|
||||
let indexer = UpdateByFunction::new(candidates, context.clone(), code.clone());
|
||||
let document_changes =
|
||||
pool.install(|| indexer.into_changes(&primary_key)).unwrap()?;
|
||||
|
||||
let embedders = index.embedding_configs(index_wtxn)?;
|
||||
let embedders = self.embedders(embedders)?;
|
||||
let document_changes = pool
|
||||
.install(|| {
|
||||
indexer
|
||||
.into_changes(&primary_key)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())))
|
||||
})
|
||||
.unwrap()?;
|
||||
let embedders = index
|
||||
.embedding_configs(index_wtxn)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())))?;
|
||||
let embedders = self.embedders(index_uid.clone(), embedders)?;
|
||||
|
||||
indexer::index(
|
||||
index_wtxn,
|
||||
@ -1424,7 +1461,8 @@ impl IndexScheduler {
|
||||
embedders,
|
||||
&|| must_stop_processing.get(),
|
||||
&send_progress,
|
||||
)?;
|
||||
)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())))?;
|
||||
|
||||
// tracing::info!(indexing_result = ?addition, processed_in = ?started_processing_at.elapsed(), "document indexing done");
|
||||
}
|
||||
@ -1455,7 +1493,7 @@ impl IndexScheduler {
|
||||
|
||||
Ok(vec![task])
|
||||
}
|
||||
IndexOperation::DocumentDeletion { mut tasks, index_uid: _ } => {
|
||||
IndexOperation::DocumentDeletion { mut tasks, index_uid } => {
|
||||
let mut to_delete = RoaringBitmap::new();
|
||||
let external_documents_ids = index.external_documents_ids();
|
||||
|
||||
@ -1476,35 +1514,23 @@ impl IndexScheduler {
|
||||
deleted_documents: Some(will_be_removed),
|
||||
});
|
||||
}
|
||||
KindWithContent::DocumentDeletionByFilter { index_uid: _, filter_expr } => {
|
||||
KindWithContent::DocumentDeletionByFilter { index_uid, filter_expr } => {
|
||||
let before = to_delete.len();
|
||||
let filter = match Filter::from_json(filter_expr) {
|
||||
Ok(filter) => filter,
|
||||
Err(err) => {
|
||||
// theorically, this should be catched by deserr before reaching the index-scheduler and cannot happens
|
||||
task.status = Status::Failed;
|
||||
task.error = match err {
|
||||
milli::Error::UserError(
|
||||
milli::UserError::InvalidFilterExpression { .. },
|
||||
) => Some(
|
||||
Error::from(err)
|
||||
.with_custom_error_code(Code::InvalidDocumentFilter)
|
||||
.into(),
|
||||
),
|
||||
e => Some(e.into()),
|
||||
};
|
||||
task.error = Some(
|
||||
Error::from_milli(err, Some(index_uid.clone())).into(),
|
||||
);
|
||||
None
|
||||
}
|
||||
};
|
||||
if let Some(filter) = filter {
|
||||
let candidates =
|
||||
filter.evaluate(index_wtxn, index).map_err(|err| match err {
|
||||
milli::Error::UserError(
|
||||
milli::UserError::InvalidFilter(_),
|
||||
) => Error::from(err)
|
||||
.with_custom_error_code(Code::InvalidDocumentFilter),
|
||||
e => e.into(),
|
||||
});
|
||||
let candidates = filter
|
||||
.evaluate(index_wtxn, index)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())));
|
||||
match candidates {
|
||||
Ok(candidates) => to_delete |= candidates,
|
||||
Err(err) => {
|
||||
@ -1540,8 +1566,9 @@ impl IndexScheduler {
|
||||
// to_delete not empty => index not empty => primary key set
|
||||
let primary_key = index.primary_key(&rtxn)?.unwrap();
|
||||
|
||||
let primary_key = PrimaryKey::new_or_insert(primary_key, &mut new_fields_ids_map)
|
||||
.map_err(milli::Error::from)?;
|
||||
let primary_key =
|
||||
PrimaryKey::new_or_insert(primary_key, &mut new_fields_ids_map)
|
||||
.map_err(|err| Error::from_milli(err.into(), Some(index_uid.clone())))?;
|
||||
|
||||
if !tasks.iter().all(|res| res.error.is_some()) {
|
||||
let local_pool;
|
||||
@ -1560,8 +1587,10 @@ impl IndexScheduler {
|
||||
let mut indexer = indexer::DocumentDeletion::new();
|
||||
indexer.delete_documents_by_docids(to_delete);
|
||||
let document_changes = indexer.into_changes(&indexer_alloc, primary_key);
|
||||
let embedders = index.embedding_configs(index_wtxn)?;
|
||||
let embedders = self.embedders(embedders)?;
|
||||
let embedders = index
|
||||
.embedding_configs(index_wtxn)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())))?;
|
||||
let embedders = self.embedders(index_uid.clone(), embedders)?;
|
||||
|
||||
indexer::index(
|
||||
index_wtxn,
|
||||
@ -1575,14 +1604,15 @@ impl IndexScheduler {
|
||||
embedders,
|
||||
&|| must_stop_processing.get(),
|
||||
&send_progress,
|
||||
)?;
|
||||
)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())))?;
|
||||
|
||||
// tracing::info!(indexing_result = ?addition, processed_in = ?started_processing_at.elapsed(), "document indexing done");
|
||||
}
|
||||
|
||||
Ok(tasks)
|
||||
}
|
||||
IndexOperation::Settings { index_uid: _, settings, mut tasks } => {
|
||||
IndexOperation::Settings { index_uid, settings, mut tasks } => {
|
||||
let indexer_config = self.index_mapper.indexer_config();
|
||||
let mut builder = milli::update::Settings::new(index_wtxn, index, indexer_config);
|
||||
|
||||
@ -1596,10 +1626,12 @@ impl IndexScheduler {
|
||||
task.status = Status::Succeeded;
|
||||
}
|
||||
|
||||
builder.execute(
|
||||
|indexing_step| tracing::debug!(update = ?indexing_step),
|
||||
|| must_stop_processing.get(),
|
||||
)?;
|
||||
builder
|
||||
.execute(
|
||||
|indexing_step| tracing::debug!(update = ?indexing_step),
|
||||
|| must_stop_processing.get(),
|
||||
)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())))?;
|
||||
|
||||
Ok(tasks)
|
||||
}
|
||||
|
@ -1,13 +1,12 @@
|
||||
use std::fmt::Display;
|
||||
|
||||
use crate::TaskId;
|
||||
use meilisearch_types::batches::BatchId;
|
||||
use meilisearch_types::error::{Code, ErrorCode};
|
||||
use meilisearch_types::tasks::{Kind, Status};
|
||||
use meilisearch_types::{heed, milli};
|
||||
use thiserror::Error;
|
||||
|
||||
use crate::TaskId;
|
||||
|
||||
#[derive(Copy, Clone, Debug, PartialEq, Eq)]
|
||||
pub enum DateField {
|
||||
BeforeEnqueuedAt,
|
||||
@ -122,8 +121,11 @@ pub enum Error {
|
||||
Dump(#[from] dump::Error),
|
||||
#[error(transparent)]
|
||||
Heed(#[from] heed::Error),
|
||||
#[error(transparent)]
|
||||
Milli(#[from] milli::Error),
|
||||
#[error("{}", match .index_uid {
|
||||
Some(uid) if !uid.is_empty() => format!("Index `{}`: {error}", uid),
|
||||
_ => format!("{error}")
|
||||
})]
|
||||
Milli { error: milli::Error, index_uid: Option<String> },
|
||||
#[error("An unexpected crash occurred when processing the task.")]
|
||||
ProcessBatchPanicked,
|
||||
#[error(transparent)]
|
||||
@ -190,7 +192,7 @@ impl Error {
|
||||
| Error::AbortedTask
|
||||
| Error::Dump(_)
|
||||
| Error::Heed(_)
|
||||
| Error::Milli(_)
|
||||
| Error::Milli { .. }
|
||||
| Error::ProcessBatchPanicked
|
||||
| Error::FileStore(_)
|
||||
| Error::IoError(_)
|
||||
@ -209,6 +211,20 @@ impl Error {
|
||||
pub fn with_custom_error_code(self, code: Code) -> Self {
|
||||
Self::WithCustomErrorCode(code, Box::new(self))
|
||||
}
|
||||
|
||||
pub fn from_milli(err: milli::Error, index_uid: Option<String>) -> Self {
|
||||
match err {
|
||||
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
|
||||
Self::Milli { error: err, index_uid }
|
||||
.with_custom_error_code(Code::InvalidDocumentFilter)
|
||||
}
|
||||
milli::Error::UserError(milli::UserError::InvalidFilterExpression { .. }) => {
|
||||
Self::Milli { error: err, index_uid }
|
||||
.with_custom_error_code(Code::InvalidDocumentFilter)
|
||||
}
|
||||
_ => Self::Milli { error: err, index_uid },
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl ErrorCode for Error {
|
||||
@ -236,7 +252,7 @@ impl ErrorCode for Error {
|
||||
// TODO: not sure of the Code to use
|
||||
Error::NoSpaceLeftInTaskQueue => Code::NoSpaceLeftOnDevice,
|
||||
Error::Dump(e) => e.error_code(),
|
||||
Error::Milli(e) => e.error_code(),
|
||||
Error::Milli { error, .. } => error.error_code(),
|
||||
Error::ProcessBatchPanicked => Code::Internal,
|
||||
Error::Heed(e) => e.error_code(),
|
||||
Error::HeedTransaction(e) => e.error_code(),
|
||||
|
@ -3,14 +3,13 @@ use std::path::Path;
|
||||
use std::time::Duration;
|
||||
|
||||
use meilisearch_types::heed::{EnvClosingEvent, EnvFlags, EnvOpenOptions};
|
||||
use meilisearch_types::milli::Index;
|
||||
use meilisearch_types::milli::{Index, Result};
|
||||
use time::OffsetDateTime;
|
||||
use uuid::Uuid;
|
||||
|
||||
use super::IndexStatus::{self, Available, BeingDeleted, Closing, Missing};
|
||||
use crate::clamp_to_page_size;
|
||||
use crate::lru::{InsertionOutcome, LruMap};
|
||||
use crate::{clamp_to_page_size, Result};
|
||||
|
||||
/// Keep an internally consistent view of the open indexes in memory.
|
||||
///
|
||||
/// This view is made of an LRU cache that will evict the least frequently used indexes when new indexes are opened.
|
||||
|
@ -3,8 +3,13 @@ use std::sync::{Arc, RwLock};
|
||||
use std::time::Duration;
|
||||
use std::{fs, thread};
|
||||
|
||||
use self::index_map::IndexMap;
|
||||
use self::IndexStatus::{Available, BeingDeleted, Closing, Missing};
|
||||
use crate::uuid_codec::UuidCodec;
|
||||
use crate::{Error, Result};
|
||||
use meilisearch_types::heed::types::{SerdeJson, Str};
|
||||
use meilisearch_types::heed::{Database, Env, RoTxn, RwTxn};
|
||||
use meilisearch_types::milli;
|
||||
use meilisearch_types::milli::update::IndexerConfig;
|
||||
use meilisearch_types::milli::{FieldDistribution, Index};
|
||||
use serde::{Deserialize, Serialize};
|
||||
@ -12,11 +17,6 @@ use time::OffsetDateTime;
|
||||
use tracing::error;
|
||||
use uuid::Uuid;
|
||||
|
||||
use self::index_map::IndexMap;
|
||||
use self::IndexStatus::{Available, BeingDeleted, Closing, Missing};
|
||||
use crate::uuid_codec::UuidCodec;
|
||||
use crate::{Error, Result};
|
||||
|
||||
mod index_map;
|
||||
|
||||
const INDEX_MAPPING: &str = "index-mapping";
|
||||
@ -121,7 +121,7 @@ impl IndexStats {
|
||||
/// # Parameters
|
||||
///
|
||||
/// - rtxn: a RO transaction for the index, obtained from `Index::read_txn()`.
|
||||
pub fn new(index: &Index, rtxn: &RoTxn) -> Result<Self> {
|
||||
pub fn new(index: &Index, rtxn: &RoTxn) -> milli::Result<Self> {
|
||||
Ok(IndexStats {
|
||||
number_of_documents: index.number_of_documents(rtxn)?,
|
||||
database_size: index.on_disk_size()?,
|
||||
@ -183,13 +183,18 @@ impl IndexMapper {
|
||||
// Error if the UUIDv4 somehow already exists in the map, since it should be fresh.
|
||||
// This is very unlikely to happen in practice.
|
||||
// TODO: it would be better to lazily create the index. But we need an Index::open function for milli.
|
||||
let index = self.index_map.write().unwrap().create(
|
||||
&uuid,
|
||||
&index_path,
|
||||
date,
|
||||
self.enable_mdb_writemap,
|
||||
self.index_base_map_size,
|
||||
)?;
|
||||
let index = self
|
||||
.index_map
|
||||
.write()
|
||||
.unwrap()
|
||||
.create(
|
||||
&uuid,
|
||||
&index_path,
|
||||
date,
|
||||
self.enable_mdb_writemap,
|
||||
self.index_base_map_size,
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
|
||||
|
||||
wtxn.commit()?;
|
||||
|
||||
@ -357,7 +362,9 @@ impl IndexMapper {
|
||||
};
|
||||
let index_path = self.base_path.join(uuid.to_string());
|
||||
// take the lock to reopen the environment.
|
||||
reopen.reopen(&mut self.index_map.write().unwrap(), &index_path)?;
|
||||
reopen
|
||||
.reopen(&mut self.index_map.write().unwrap(), &index_path)
|
||||
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
|
||||
continue;
|
||||
}
|
||||
BeingDeleted => return Err(Error::IndexNotFound(name.to_string())),
|
||||
@ -372,13 +379,15 @@ impl IndexMapper {
|
||||
Missing => {
|
||||
let index_path = self.base_path.join(uuid.to_string());
|
||||
|
||||
break index_map.create(
|
||||
&uuid,
|
||||
&index_path,
|
||||
None,
|
||||
self.enable_mdb_writemap,
|
||||
self.index_base_map_size,
|
||||
)?;
|
||||
break index_map
|
||||
.create(
|
||||
&uuid,
|
||||
&index_path,
|
||||
None,
|
||||
self.enable_mdb_writemap,
|
||||
self.index_base_map_size,
|
||||
)
|
||||
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))?;
|
||||
}
|
||||
Available(index) => break index,
|
||||
Closing(_) => {
|
||||
@ -460,6 +469,7 @@ impl IndexMapper {
|
||||
let index = self.index(rtxn, index_uid)?;
|
||||
let index_rtxn = index.read_txn()?;
|
||||
IndexStats::new(&index, &index_rtxn)
|
||||
.map_err(|e| Error::from_milli(e, Some(uuid.to_string())))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
@ -1678,9 +1678,10 @@ impl IndexScheduler {
|
||||
tracing::info!("A batch of tasks was successfully completed with {success} successful tasks and {failure} failed tasks.");
|
||||
}
|
||||
// If we have an abortion error we must stop the tick here and re-schedule tasks.
|
||||
Err(Error::Milli(milli::Error::InternalError(
|
||||
milli::InternalError::AbortedIndexation,
|
||||
)))
|
||||
Err(Error::Milli {
|
||||
error: milli::Error::InternalError(milli::InternalError::AbortedIndexation),
|
||||
..
|
||||
})
|
||||
| Err(Error::AbortedTask) => {
|
||||
#[cfg(test)]
|
||||
self.breakpoint(Breakpoint::AbortedIndexation);
|
||||
@ -1699,9 +1700,10 @@ impl IndexScheduler {
|
||||
// 2. close the associated environment
|
||||
// 3. resize it
|
||||
// 4. re-schedule tasks
|
||||
Err(Error::Milli(milli::Error::UserError(
|
||||
milli::UserError::MaxDatabaseSizeReached,
|
||||
))) if index_uid.is_some() => {
|
||||
Err(Error::Milli {
|
||||
error: milli::Error::UserError(milli::UserError::MaxDatabaseSizeReached),
|
||||
..
|
||||
}) if index_uid.is_some() => {
|
||||
// fixme: add index_uid to match to avoid the unwrap
|
||||
let index_uid = index_uid.unwrap();
|
||||
// fixme: handle error more gracefully? not sure when this could happen
|
||||
@ -1943,6 +1945,7 @@ impl IndexScheduler {
|
||||
// TODO: consider using a type alias or a struct embedder/template
|
||||
pub fn embedders(
|
||||
&self,
|
||||
index_uid: String,
|
||||
embedding_configs: Vec<IndexEmbeddingConfig>,
|
||||
) -> Result<EmbeddingConfigs> {
|
||||
let res: Result<_> = embedding_configs
|
||||
@ -1953,8 +1956,12 @@ impl IndexScheduler {
|
||||
config: milli::vector::EmbeddingConfig { embedder_options, prompt, quantized },
|
||||
..
|
||||
}| {
|
||||
let prompt =
|
||||
Arc::new(prompt.try_into().map_err(meilisearch_types::milli::Error::from)?);
|
||||
let prompt = Arc::new(
|
||||
prompt
|
||||
.try_into()
|
||||
.map_err(meilisearch_types::milli::Error::from)
|
||||
.map_err(|err| Error::from_milli(err, Some(index_uid.clone())))?,
|
||||
);
|
||||
// optimistically return existing embedder
|
||||
{
|
||||
let embedders = self.embedders.read().unwrap();
|
||||
@ -1970,7 +1977,9 @@ impl IndexScheduler {
|
||||
let embedder = Arc::new(
|
||||
Embedder::new(embedder_options.clone())
|
||||
.map_err(meilisearch_types::milli::vector::Error::from)
|
||||
.map_err(meilisearch_types::milli::Error::from)?,
|
||||
.map_err(|err| {
|
||||
Error::from_milli(err.into(), Some(index_uid.clone()))
|
||||
})?,
|
||||
);
|
||||
{
|
||||
let mut embedders = self.embedders.write().unwrap();
|
||||
@ -4319,10 +4328,35 @@ mod tests {
|
||||
let proc = index_scheduler.processing_tasks.read().unwrap().clone();
|
||||
|
||||
let query = Query { statuses: Some(vec![Status::Processing]), ..Default::default() };
|
||||
let (batches, _) = index_scheduler
|
||||
.get_batch_ids_from_authorized_indexes(&rtxn, &proc, &query, &AuthFilter::default())
|
||||
let (mut batches, _) = index_scheduler
|
||||
.get_batches_from_authorized_indexes(query.clone(), &AuthFilter::default())
|
||||
.unwrap();
|
||||
snapshot!(snapshot_bitmap(&batches), @"[0,]"); // only the processing batch in the first tick
|
||||
assert_eq!(batches.len(), 1);
|
||||
batches[0].started_at = OffsetDateTime::UNIX_EPOCH;
|
||||
// Insta cannot snapshot our batches because the batch stats contains an enum as key: https://github.com/mitsuhiko/insta/issues/689
|
||||
let batch = serde_json::to_string_pretty(&batches[0]).unwrap();
|
||||
snapshot!(batch, @r#"
|
||||
{
|
||||
"uid": 0,
|
||||
"details": {
|
||||
"primaryKey": "mouse"
|
||||
},
|
||||
"stats": {
|
||||
"totalNbTasks": 1,
|
||||
"status": {
|
||||
"processing": 1
|
||||
},
|
||||
"types": {
|
||||
"indexCreation": 1
|
||||
},
|
||||
"indexUids": {
|
||||
"catto": 1
|
||||
}
|
||||
},
|
||||
"startedAt": "1970-01-01T00:00:00Z",
|
||||
"finishedAt": null
|
||||
}
|
||||
"#);
|
||||
|
||||
let query = Query { statuses: Some(vec![Status::Enqueued]), ..Default::default() };
|
||||
let (batches, _) = index_scheduler
|
||||
@ -6146,7 +6180,7 @@ mod tests {
|
||||
insta::assert_json_snapshot!(simple_hf_config.embedder_options);
|
||||
let simple_hf_name = name.clone();
|
||||
|
||||
let configs = index_scheduler.embedders(configs).unwrap();
|
||||
let configs = index_scheduler.embedders("doggos".to_string(), configs).unwrap();
|
||||
let (hf_embedder, _, _) = configs.get(&simple_hf_name).unwrap();
|
||||
let beagle_embed =
|
||||
hf_embedder.embed_one(S("Intel the beagle best doggo"), None).unwrap();
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(1):
|
||||
[1,]
|
||||
{uid: 1, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"beavero":2}}, }
|
||||
{uid: 1, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"beavero":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, batch_uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "catto", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(1):
|
||||
[1,]
|
||||
{uid: 1, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"beavero":2}}, }
|
||||
{uid: 1, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"beavero":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, batch_uid: 0, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "catto", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"dumpUid":null}, stats: {"totalNbTasks":1,"status":{"enqueued":1},"types":{"dumpCreation":1},"indexUids":{}}, }
|
||||
{uid: 0, details: {"dumpUid":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"dumpCreation":1},"indexUids":{}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { dump_uid: None }, kind: DumpCreation { keys: [], instance_uid: None }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"catto":2}}, }
|
||||
{uid: 0, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"catto":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "catto", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"catto":2}}, }
|
||||
{uid: 0, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"catto":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "catto", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"catto":2}}, }
|
||||
{uid: 0, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"catto":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "catto", primary_key: None, method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"doggos":2}}, }
|
||||
{uid: 0, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"doggos":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"doggos":2}}, }
|
||||
{uid: 0, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"doggos":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -9,8 +9,8 @@ source: crates/index-scheduler/src/lib.rs
|
||||
0 {uid: 0, batch_uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: Set({"catto"}), sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: NotSet, search_cutoff_ms: NotSet, localized_attributes: NotSet, facet_search: NotSet, prefix_search: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: Set({"catto"}), sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: NotSet, search_cutoff_ms: NotSet, localized_attributes: NotSet, facet_search: NotSet, prefix_search: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
|
||||
1 {uid: 1, batch_uid: 1, status: succeeded, details: { received_documents: 3, indexed_documents: Some(3) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 3, allow_index_creation: true }}
|
||||
2 {uid: 2, batch_uid: 2, status: succeeded, details: { received_document_ids: 1, deleted_documents: Some(1) }, kind: DocumentDeletion { index_uid: "doggos", documents_ids: ["1"] }}
|
||||
3 {uid: 3, batch_uid: 2, status: failed, error: ResponseError { code: 200, message: "Invalid type for filter subexpression: expected: String, Array, found: true.", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: true, deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: Bool(true) }}
|
||||
4 {uid: 4, batch_uid: 2, status: failed, error: ResponseError { code: 200, message: "Attribute `id` is not filterable. Available filterable attributes are: `catto`.\n1:3 id = 2", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: "id = 2", deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("id = 2") }}
|
||||
3 {uid: 3, batch_uid: 2, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Invalid type for filter subexpression: expected: String, Array, found: true.", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: true, deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: Bool(true) }}
|
||||
4 {uid: 4, batch_uid: 2, status: failed, error: ResponseError { code: 200, message: "Index `doggos`: Attribute `id` is not filterable. Available filterable attributes are: `catto`.\n1:3 id = 2", error_code: "invalid_document_filter", error_type: "invalid_request", error_link: "https://docs.meilisearch.com/errors#invalid_document_filter" }, details: { original_filter: "id = 2", deleted_documents: Some(0) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("id = 2") }}
|
||||
5 {uid: 5, batch_uid: 2, status: succeeded, details: { original_filter: "catto EXISTS", deleted_documents: Some(1) }, kind: DocumentDeletionByFilter { index_uid: "doggos", filter_expr: String("catto EXISTS") }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"doggos":2}}, }
|
||||
{uid: 0, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"doggos":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"receivedDocuments":2,"indexedDocuments":null}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"documentAdditionOrUpdate":2},"indexUids":{"doggos":2}}, }
|
||||
{uid: 0, details: {"receivedDocuments":1,"indexedDocuments":null}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"documentAdditionOrUpdate":1},"indexUids":{"doggos":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: ReplaceDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"primaryKey":"id"}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"indexCreation":2},"indexUids":{"index_a":2}}, }
|
||||
{uid: 0, details: {"primaryKey":"id"}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"indexCreation":1},"indexUids":{"index_a":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { primary_key: Some("id") }, kind: IndexCreation { index_uid: "index_a", primary_key: Some("id") }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"primaryKey":"id"}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"indexCreation":2},"indexUids":{"index_a":2}}, }
|
||||
{uid: 0, details: {"primaryKey":"id"}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"indexCreation":1},"indexUids":{"index_a":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { primary_key: Some("id") }, kind: IndexCreation { index_uid: "index_a", primary_key: Some("id") }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[0,]
|
||||
{uid: 0, details: {"primaryKey":"id"}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"indexCreation":2},"indexUids":{"index_a":2}}, }
|
||||
{uid: 0, details: {"primaryKey":"id"}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"indexCreation":1},"indexUids":{"index_a":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { primary_key: Some("id") }, kind: IndexCreation { index_uid: "index_a", primary_key: Some("id") }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(1):
|
||||
[1,]
|
||||
{uid: 1, details: {"primaryKey":"sheep"}, stats: {"totalNbTasks":2,"status":{"enqueued":2},"types":{"indexCreation":2},"indexUids":{"doggo":2}}, }
|
||||
{uid: 1, details: {"primaryKey":"sheep"}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"indexCreation":1},"indexUids":{"doggo":1}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, batch_uid: 0, status: succeeded, details: { primary_key: Some("mouse") }, kind: IndexCreation { index_uid: "catto", primary_key: Some("mouse") }}
|
||||
|
@ -5,7 +5,7 @@ snapshot_kind: text
|
||||
### Autobatching Enabled = true
|
||||
### Processing batch Some(0):
|
||||
[3,]
|
||||
{uid: 0, details: {"matchedTasks":2,"deletedTasks":null,"originalFilter":"test_query"}, stats: {"totalNbTasks":1,"status":{"enqueued":1},"types":{"taskDeletion":1},"indexUids":{}}, }
|
||||
{uid: 0, details: {"matchedTasks":2,"deletedTasks":null,"originalFilter":"test_query"}, stats: {"totalNbTasks":1,"status":{"processing":1},"types":{"taskDeletion":1},"indexUids":{}}, }
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { primary_key: Some("mouse") }, kind: IndexCreation { index_uid: "catto", primary_key: Some("mouse") }}
|
||||
|
@ -67,7 +67,7 @@ impl ProcessingBatch {
|
||||
task.batch_uid = Some(self.uid);
|
||||
// We don't store the statuses in the map since they're all enqueued but we must
|
||||
// still store them in the stats since that can be displayed.
|
||||
*self.stats.status.entry(task.status).or_default() += 1;
|
||||
*self.stats.status.entry(Status::Processing).or_default() += 1;
|
||||
|
||||
self.kinds.insert(task.kind.as_kind());
|
||||
*self.stats.types.entry(task.kind.as_kind()).or_default() += 1;
|
||||
|
@ -279,6 +279,7 @@ InvalidSearchPage , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchQ , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidFacetSearchQuery , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidFacetSearchName , InvalidRequest , BAD_REQUEST ;
|
||||
FacetSearchDisabled , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchVector , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchShowMatchesPosition , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchShowRankingScore , InvalidRequest , BAD_REQUEST ;
|
||||
|
@ -4,6 +4,7 @@ use byte_unit::{Byte, UnitType};
|
||||
use meilisearch_types::document_formats::{DocumentFormatError, PayloadType};
|
||||
use meilisearch_types::error::{Code, ErrorCode, ResponseError};
|
||||
use meilisearch_types::index_uid::{IndexUid, IndexUidFormatError};
|
||||
use meilisearch_types::milli;
|
||||
use meilisearch_types::milli::OrderBy;
|
||||
use serde_json::Value;
|
||||
use tokio::task::JoinError;
|
||||
@ -62,8 +63,11 @@ pub enum MeilisearchHttpError {
|
||||
HeedError(#[from] meilisearch_types::heed::Error),
|
||||
#[error(transparent)]
|
||||
IndexScheduler(#[from] index_scheduler::Error),
|
||||
#[error(transparent)]
|
||||
Milli(#[from] meilisearch_types::milli::Error),
|
||||
#[error("{}", match .index_name {
|
||||
Some(name) if !name.is_empty() => format!("Index `{}`: {error}", name),
|
||||
_ => format!("{error}")
|
||||
})]
|
||||
Milli { error: milli::Error, index_name: Option<String> },
|
||||
#[error(transparent)]
|
||||
Payload(#[from] PayloadError),
|
||||
#[error(transparent)]
|
||||
@ -76,6 +80,12 @@ pub enum MeilisearchHttpError {
|
||||
MissingSearchHybrid,
|
||||
}
|
||||
|
||||
impl MeilisearchHttpError {
|
||||
pub(crate) fn from_milli(error: milli::Error, index_name: Option<String>) -> Self {
|
||||
Self::Milli { error, index_name }
|
||||
}
|
||||
}
|
||||
|
||||
impl ErrorCode for MeilisearchHttpError {
|
||||
fn error_code(&self) -> Code {
|
||||
match self {
|
||||
@ -95,7 +105,7 @@ impl ErrorCode for MeilisearchHttpError {
|
||||
MeilisearchHttpError::SerdeJson(_) => Code::Internal,
|
||||
MeilisearchHttpError::HeedError(_) => Code::Internal,
|
||||
MeilisearchHttpError::IndexScheduler(e) => e.error_code(),
|
||||
MeilisearchHttpError::Milli(e) => e.error_code(),
|
||||
MeilisearchHttpError::Milli { error, .. } => error.error_code(),
|
||||
MeilisearchHttpError::Payload(e) => e.error_code(),
|
||||
MeilisearchHttpError::FileStore(_) => Code::Internal,
|
||||
MeilisearchHttpError::DocumentFormat(e) => e.error_code(),
|
||||
|
@ -395,6 +395,7 @@ fn import_dump(
|
||||
for index_reader in dump_reader.indexes()? {
|
||||
let mut index_reader = index_reader?;
|
||||
let metadata = index_reader.metadata();
|
||||
let uid = metadata.uid.clone();
|
||||
tracing::info!("Importing index `{}`.", metadata.uid);
|
||||
|
||||
let date = Some((metadata.created_at, metadata.updated_at));
|
||||
@ -432,7 +433,7 @@ fn import_dump(
|
||||
let reader = DocumentsBatchReader::from_reader(reader)?;
|
||||
|
||||
let embedder_configs = index.embedding_configs(&wtxn)?;
|
||||
let embedders = index_scheduler.embedders(embedder_configs)?;
|
||||
let embedders = index_scheduler.embedders(uid, embedder_configs)?;
|
||||
|
||||
let builder = milli::update::IndexDocuments::new(
|
||||
&mut wtxn,
|
||||
|
@ -654,9 +654,8 @@ impl Opt {
|
||||
|
||||
#[derive(Debug, Default, Clone, Parser, Deserialize)]
|
||||
pub struct IndexerOpts {
|
||||
/// Specifies the maximum resident memory that Meilisearch can use for indexing.
|
||||
/// By default, Meilisearch limits the RAM usage to 5% of the total available memory.
|
||||
/// Note that the underlying store utilizes memory-mapping and makes use of the rest.
|
||||
/// Sets the maximum amount of RAM Meilisearch can use when indexing. By default, Meilisearch
|
||||
/// uses no more than two thirds of available memory.
|
||||
#[clap(long, env = MEILI_MAX_INDEXING_MEMORY, default_value_t)]
|
||||
#[serde(default)]
|
||||
pub max_indexing_memory: MaxMemory,
|
||||
@ -715,7 +714,7 @@ impl TryFrom<&IndexerOpts> for IndexerConfig {
|
||||
}
|
||||
}
|
||||
|
||||
/// A type used to detect the max resident memory available and use 5% of it.
|
||||
/// A type used to detect the max memory available and use 2/3 of it.
|
||||
#[derive(Debug, Clone, Copy, Deserialize, Serialize)]
|
||||
pub struct MaxMemory(Option<Byte>);
|
||||
|
||||
@ -729,7 +728,7 @@ impl FromStr for MaxMemory {
|
||||
|
||||
impl Default for MaxMemory {
|
||||
fn default() -> MaxMemory {
|
||||
MaxMemory(total_memory_bytes().map(|bytes| bytes * 5 / 100).map(Byte::from_u64))
|
||||
MaxMemory(total_memory_bytes().map(|bytes| bytes * 2 / 3).map(Byte::from_u64))
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -185,7 +185,8 @@ pub async fn search(
|
||||
|
||||
let index = index_scheduler.index(&index_uid)?;
|
||||
let features = index_scheduler.features();
|
||||
let search_kind = search_kind(&search_query, &index_scheduler, &index, features)?;
|
||||
let search_kind =
|
||||
search_kind(&search_query, &index_scheduler, index_uid.to_string(), &index, features)?;
|
||||
let permit = search_queue.try_get_search_permit().await?;
|
||||
let search_result = tokio::task::spawn_blocking(move || {
|
||||
perform_facet_search(
|
||||
|
@ -5,7 +5,7 @@ use actix_web::web::Data;
|
||||
use actix_web::{web, HttpRequest, HttpResponse};
|
||||
use deserr::actix_web::{AwebJson, AwebQueryParameter};
|
||||
use deserr::{DeserializeError, Deserr, ValuePointerRef};
|
||||
use index_scheduler::IndexScheduler;
|
||||
use index_scheduler::{Error, IndexScheduler};
|
||||
use meilisearch_types::deserr::query_params::Param;
|
||||
use meilisearch_types::deserr::{immutable_field_error, DeserrJsonError, DeserrQueryParamError};
|
||||
use meilisearch_types::error::deserr_codes::*;
|
||||
@ -107,7 +107,10 @@ pub async fn list_indexes(
|
||||
if !filters.is_index_authorized(uid) {
|
||||
return Ok(None);
|
||||
}
|
||||
Ok(Some(IndexView::new(uid.to_string(), index)?))
|
||||
Ok(Some(
|
||||
IndexView::new(uid.to_string(), index)
|
||||
.map_err(|e| Error::from_milli(e, Some(uid.to_string())))?,
|
||||
))
|
||||
})?;
|
||||
// Won't cause to open all indexes because IndexView doesn't keep the `Index` opened.
|
||||
let indexes: Vec<IndexView> = indexes.into_iter().flatten().collect();
|
||||
|
@ -243,11 +243,19 @@ pub async fn search_with_url_query(
|
||||
let index = index_scheduler.index(&index_uid)?;
|
||||
let features = index_scheduler.features();
|
||||
|
||||
let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
|
||||
let search_kind =
|
||||
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
|
||||
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)?;
|
||||
let permit = search_queue.try_get_search_permit().await?;
|
||||
let search_result = tokio::task::spawn_blocking(move || {
|
||||
perform_search(&index, query, search_kind, retrieve_vector, index_scheduler.features())
|
||||
perform_search(
|
||||
index_uid.to_string(),
|
||||
&index,
|
||||
query,
|
||||
search_kind,
|
||||
retrieve_vector,
|
||||
index_scheduler.features(),
|
||||
)
|
||||
})
|
||||
.await;
|
||||
permit.drop().await;
|
||||
@ -287,12 +295,20 @@ pub async fn search_with_post(
|
||||
|
||||
let features = index_scheduler.features();
|
||||
|
||||
let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
|
||||
let search_kind =
|
||||
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
|
||||
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
|
||||
|
||||
let permit = search_queue.try_get_search_permit().await?;
|
||||
let search_result = tokio::task::spawn_blocking(move || {
|
||||
perform_search(&index, query, search_kind, retrieve_vectors, index_scheduler.features())
|
||||
perform_search(
|
||||
index_uid.to_string(),
|
||||
&index,
|
||||
query,
|
||||
search_kind,
|
||||
retrieve_vectors,
|
||||
index_scheduler.features(),
|
||||
)
|
||||
})
|
||||
.await;
|
||||
permit.drop().await;
|
||||
@ -314,6 +330,7 @@ pub async fn search_with_post(
|
||||
pub fn search_kind(
|
||||
query: &SearchQuery,
|
||||
index_scheduler: &IndexScheduler,
|
||||
index_uid: String,
|
||||
index: &milli::Index,
|
||||
features: RoFeatures,
|
||||
) -> Result<SearchKind, ResponseError> {
|
||||
@ -332,7 +349,7 @@ pub fn search_kind(
|
||||
(None, _, None) => Ok(SearchKind::KeywordOnly),
|
||||
// hybrid.semantic_ratio == 1.0 => vector
|
||||
(_, Some(HybridQuery { semantic_ratio, embedder }), v) if **semantic_ratio == 1.0 => {
|
||||
SearchKind::semantic(index_scheduler, index, embedder, v.map(|v| v.len()))
|
||||
SearchKind::semantic(index_scheduler, index_uid, index, embedder, v.map(|v| v.len()))
|
||||
}
|
||||
// hybrid.semantic_ratio == 0.0 => keyword
|
||||
(_, Some(HybridQuery { semantic_ratio, embedder: _ }), _) if **semantic_ratio == 0.0 => {
|
||||
@ -340,13 +357,14 @@ pub fn search_kind(
|
||||
}
|
||||
// no query, hybrid, vector => semantic
|
||||
(None, Some(HybridQuery { semantic_ratio: _, embedder }), Some(v)) => {
|
||||
SearchKind::semantic(index_scheduler, index, embedder, Some(v.len()))
|
||||
SearchKind::semantic(index_scheduler, index_uid, index, embedder, Some(v.len()))
|
||||
}
|
||||
// query, no hybrid, no vector => keyword
|
||||
(Some(_), None, None) => Ok(SearchKind::KeywordOnly),
|
||||
// query, hybrid, maybe vector => hybrid
|
||||
(Some(_), Some(HybridQuery { semantic_ratio, embedder }), v) => SearchKind::hybrid(
|
||||
index_scheduler,
|
||||
index_uid,
|
||||
index,
|
||||
embedder,
|
||||
**semantic_ratio,
|
||||
|
@ -103,8 +103,13 @@ async fn similar(
|
||||
|
||||
let index = index_scheduler.index(&index_uid)?;
|
||||
|
||||
let (embedder_name, embedder, quantized) =
|
||||
SearchKind::embedder(&index_scheduler, &index, &query.embedder, None)?;
|
||||
let (embedder_name, embedder, quantized) = SearchKind::embedder(
|
||||
&index_scheduler,
|
||||
index_uid.to_string(),
|
||||
&index,
|
||||
&query.embedder,
|
||||
None,
|
||||
)?;
|
||||
|
||||
tokio::task::spawn_blocking(move || {
|
||||
perform_similar(
|
||||
|
@ -125,14 +125,28 @@ pub async fn multi_search_with_post(
|
||||
})
|
||||
.with_index(query_index)?;
|
||||
|
||||
let search_kind =
|
||||
search_kind(&query, index_scheduler.get_ref(), &index, features)
|
||||
.with_index(query_index)?;
|
||||
let index_uid_str = index_uid.to_string();
|
||||
|
||||
let search_kind = search_kind(
|
||||
&query,
|
||||
index_scheduler.get_ref(),
|
||||
index_uid_str.clone(),
|
||||
&index,
|
||||
features,
|
||||
)
|
||||
.with_index(query_index)?;
|
||||
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)
|
||||
.with_index(query_index)?;
|
||||
|
||||
let search_result = tokio::task::spawn_blocking(move || {
|
||||
perform_search(&index, query, search_kind, retrieve_vector, features)
|
||||
perform_search(
|
||||
index_uid_str.clone(),
|
||||
&index,
|
||||
query,
|
||||
search_kind,
|
||||
retrieve_vector,
|
||||
features,
|
||||
)
|
||||
})
|
||||
.await
|
||||
.with_index(query_index)?;
|
||||
|
@ -560,7 +560,8 @@ pub fn perform_federated_search(
|
||||
// use an immediately invoked lambda to capture the result without returning from the function
|
||||
|
||||
let res: Result<(), ResponseError> = (|| {
|
||||
let search_kind = search_kind(&query, index_scheduler, &index, features)?;
|
||||
let search_kind =
|
||||
search_kind(&query, index_scheduler, index_uid.to_string(), &index, features)?;
|
||||
|
||||
let canonicalization_kind = match (&search_kind, &query.q) {
|
||||
(SearchKind::SemanticOnly { .. }, _) => {
|
||||
@ -636,7 +637,8 @@ pub fn perform_federated_search(
|
||||
search.offset(0);
|
||||
search.limit(required_hit_count);
|
||||
|
||||
let (result, _semantic_hit_count) = super::search_from_kind(search_kind, search)?;
|
||||
let (result, _semantic_hit_count) =
|
||||
super::search_from_kind(index_uid.to_string(), search_kind, search)?;
|
||||
let format = AttributesFormat {
|
||||
attributes_to_retrieve: query.attributes_to_retrieve,
|
||||
retrieve_vectors,
|
||||
@ -670,7 +672,10 @@ pub fn perform_federated_search(
|
||||
|
||||
let formatter_builder = HitMaker::formatter_builder(matching_words, tokenizer);
|
||||
|
||||
let hit_maker = HitMaker::new(&index, &rtxn, format, formatter_builder)?;
|
||||
let hit_maker =
|
||||
HitMaker::new(&index, &rtxn, format, formatter_builder).map_err(|e| {
|
||||
MeilisearchHttpError::from_milli(e, Some(index_uid.to_string()))
|
||||
})?;
|
||||
|
||||
results_by_query.push(SearchResultByQuery {
|
||||
federation_options,
|
||||
|
@ -19,7 +19,9 @@ use meilisearch_types::locales::Locale;
|
||||
use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy};
|
||||
use meilisearch_types::milli::vector::parsed_vectors::ExplicitVectors;
|
||||
use meilisearch_types::milli::vector::Embedder;
|
||||
use meilisearch_types::milli::{FacetValueHit, OrderBy, SearchForFacetValues, TimeBudget};
|
||||
use meilisearch_types::milli::{
|
||||
FacetValueHit, InternalError, OrderBy, SearchForFacetValues, TimeBudget,
|
||||
};
|
||||
use meilisearch_types::settings::DEFAULT_PAGINATION_MAX_TOTAL_HITS;
|
||||
use meilisearch_types::{milli, Document};
|
||||
use milli::tokenizer::{Language, TokenizerBuilder};
|
||||
@ -281,35 +283,38 @@ pub enum SearchKind {
|
||||
impl SearchKind {
|
||||
pub(crate) fn semantic(
|
||||
index_scheduler: &index_scheduler::IndexScheduler,
|
||||
index_uid: String,
|
||||
index: &Index,
|
||||
embedder_name: &str,
|
||||
vector_len: Option<usize>,
|
||||
) -> Result<Self, ResponseError> {
|
||||
let (embedder_name, embedder, quantized) =
|
||||
Self::embedder(index_scheduler, index, embedder_name, vector_len)?;
|
||||
Self::embedder(index_scheduler, index_uid, index, embedder_name, vector_len)?;
|
||||
Ok(Self::SemanticOnly { embedder_name, embedder, quantized })
|
||||
}
|
||||
|
||||
pub(crate) fn hybrid(
|
||||
index_scheduler: &index_scheduler::IndexScheduler,
|
||||
index_uid: String,
|
||||
index: &Index,
|
||||
embedder_name: &str,
|
||||
semantic_ratio: f32,
|
||||
vector_len: Option<usize>,
|
||||
) -> Result<Self, ResponseError> {
|
||||
let (embedder_name, embedder, quantized) =
|
||||
Self::embedder(index_scheduler, index, embedder_name, vector_len)?;
|
||||
Self::embedder(index_scheduler, index_uid, index, embedder_name, vector_len)?;
|
||||
Ok(Self::Hybrid { embedder_name, embedder, quantized, semantic_ratio })
|
||||
}
|
||||
|
||||
pub(crate) fn embedder(
|
||||
index_scheduler: &index_scheduler::IndexScheduler,
|
||||
index_uid: String,
|
||||
index: &Index,
|
||||
embedder_name: &str,
|
||||
vector_len: Option<usize>,
|
||||
) -> Result<(String, Arc<Embedder>, bool), ResponseError> {
|
||||
let embedder_configs = index.embedding_configs(&index.read_txn()?)?;
|
||||
let embedders = index_scheduler.embedders(embedder_configs)?;
|
||||
let embedders = index_scheduler.embedders(index_uid, embedder_configs)?;
|
||||
|
||||
let (embedder, _, quantized) = embedders
|
||||
.get(embedder_name)
|
||||
@ -890,6 +895,7 @@ fn prepare_search<'t>(
|
||||
}
|
||||
|
||||
pub fn perform_search(
|
||||
index_uid: String,
|
||||
index: &Index,
|
||||
query: SearchQuery,
|
||||
search_kind: SearchKind,
|
||||
@ -916,7 +922,7 @@ pub fn perform_search(
|
||||
used_negative_operator,
|
||||
},
|
||||
semantic_hit_count,
|
||||
) = search_from_kind(search_kind, search)?;
|
||||
) = search_from_kind(index_uid, search_kind, search)?;
|
||||
|
||||
let SearchQuery {
|
||||
q,
|
||||
@ -1069,17 +1075,27 @@ fn compute_facet_distribution_stats<S: AsRef<str>>(
|
||||
}
|
||||
|
||||
pub fn search_from_kind(
|
||||
index_uid: String,
|
||||
search_kind: SearchKind,
|
||||
search: milli::Search<'_>,
|
||||
) -> Result<(milli::SearchResult, Option<u32>), MeilisearchHttpError> {
|
||||
let (milli_result, semantic_hit_count) = match &search_kind {
|
||||
SearchKind::KeywordOnly => (search.execute()?, None),
|
||||
SearchKind::KeywordOnly => {
|
||||
let results = search
|
||||
.execute()
|
||||
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid.to_string())))?;
|
||||
(results, None)
|
||||
}
|
||||
SearchKind::SemanticOnly { .. } => {
|
||||
let results = search.execute()?;
|
||||
let results = search
|
||||
.execute()
|
||||
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid.to_string())))?;
|
||||
let semantic_hit_count = results.document_scores.len() as u32;
|
||||
(results, Some(semantic_hit_count))
|
||||
}
|
||||
SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?,
|
||||
SearchKind::Hybrid { semantic_ratio, .. } => search
|
||||
.execute_hybrid(*semantic_ratio)
|
||||
.map_err(|e| MeilisearchHttpError::from_milli(e, Some(index_uid)))?,
|
||||
};
|
||||
Ok((milli_result, semantic_hit_count))
|
||||
}
|
||||
@ -1181,7 +1197,7 @@ impl<'a> HitMaker<'a> {
|
||||
rtxn: &'a RoTxn<'a>,
|
||||
format: AttributesFormat,
|
||||
mut formatter_builder: MatcherBuilder<'a>,
|
||||
) -> Result<Self, MeilisearchHttpError> {
|
||||
) -> milli::Result<Self> {
|
||||
formatter_builder.crop_marker(format.crop_marker);
|
||||
formatter_builder.highlight_prefix(format.highlight_pre_tag);
|
||||
formatter_builder.highlight_suffix(format.highlight_post_tag);
|
||||
@ -1276,11 +1292,7 @@ impl<'a> HitMaker<'a> {
|
||||
})
|
||||
}
|
||||
|
||||
pub fn make_hit(
|
||||
&self,
|
||||
id: u32,
|
||||
score: &[ScoreDetails],
|
||||
) -> Result<SearchHit, MeilisearchHttpError> {
|
||||
pub fn make_hit(&self, id: u32, score: &[ScoreDetails]) -> milli::Result<SearchHit> {
|
||||
let (_, obkv) =
|
||||
self.index.iter_documents(self.rtxn, std::iter::once(id))?.next().unwrap()?;
|
||||
|
||||
@ -1323,7 +1335,10 @@ impl<'a> HitMaker<'a> {
|
||||
.is_some_and(|conf| conf.user_provided.contains(id));
|
||||
let embeddings =
|
||||
ExplicitVectors { embeddings: Some(vector.into()), regenerate: !user_provided };
|
||||
vectors.insert(name, serde_json::to_value(embeddings)?);
|
||||
vectors.insert(
|
||||
name,
|
||||
serde_json::to_value(embeddings).map_err(InternalError::SerdeJson)?,
|
||||
);
|
||||
}
|
||||
document.insert("_vectors".into(), vectors.into());
|
||||
}
|
||||
@ -1369,7 +1384,7 @@ fn make_hits<'a>(
|
||||
format: AttributesFormat,
|
||||
matching_words: milli::MatchingWords,
|
||||
documents_ids_scores: impl Iterator<Item = (u32, &'a Vec<ScoreDetails>)> + 'a,
|
||||
) -> Result<Vec<SearchHit>, MeilisearchHttpError> {
|
||||
) -> milli::Result<Vec<SearchHit>> {
|
||||
let mut documents = Vec::new();
|
||||
|
||||
let dictionary = index.dictionary(rtxn)?;
|
||||
@ -1407,6 +1422,13 @@ pub fn perform_facet_search(
|
||||
None => TimeBudget::default(),
|
||||
};
|
||||
|
||||
if !index.facet_search(&rtxn)? {
|
||||
return Err(ResponseError::from_msg(
|
||||
"The facet search is disabled for this index".to_string(),
|
||||
Code::FacetSearchDisabled,
|
||||
));
|
||||
}
|
||||
|
||||
// In the faceted search context, we want to use the intersection between the locales provided by the user
|
||||
// and the locales of the facet string.
|
||||
// If the facet string is not localized, we **ignore** the locales provided by the user because the facet data has no locale.
|
||||
@ -1690,12 +1712,12 @@ fn make_document(
|
||||
displayed_attributes: &BTreeSet<FieldId>,
|
||||
field_ids_map: &FieldsIdsMap,
|
||||
obkv: &obkv::KvReaderU16,
|
||||
) -> Result<Document, MeilisearchHttpError> {
|
||||
) -> milli::Result<Document> {
|
||||
let mut document = serde_json::Map::new();
|
||||
|
||||
// recreate the original json
|
||||
for (key, value) in obkv.iter() {
|
||||
let value = serde_json::from_slice(value)?;
|
||||
let value = serde_json::from_slice(value).map_err(InternalError::SerdeJson)?;
|
||||
let key = field_ids_map.name(key).expect("Missing field name").to_string();
|
||||
|
||||
document.insert(key, value);
|
||||
@ -1720,7 +1742,7 @@ fn format_fields(
|
||||
displayable_ids: &BTreeSet<FieldId>,
|
||||
locales: Option<&[Language]>,
|
||||
localized_attributes: &[LocalizedAttributesRule],
|
||||
) -> Result<(Option<MatchesPosition>, Document), MeilisearchHttpError> {
|
||||
) -> milli::Result<(Option<MatchesPosition>, Document)> {
|
||||
let mut matches_position = compute_matches.then(BTreeMap::new);
|
||||
let mut document = document.clone();
|
||||
|
||||
@ -1898,7 +1920,7 @@ fn parse_filter_array(arr: &[Value]) -> Result<Option<Filter>, MeilisearchHttpEr
|
||||
}
|
||||
}
|
||||
|
||||
Ok(Filter::from_array(ands)?)
|
||||
Filter::from_array(ands).map_err(|e| MeilisearchHttpError::from_milli(e, None))
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
|
@ -52,6 +52,25 @@ impl Value {
|
||||
}
|
||||
self
|
||||
}
|
||||
|
||||
/// Return `true` if the `status` field is set to `failed`.
|
||||
/// Panic if the `status` field doesn't exists.
|
||||
#[track_caller]
|
||||
pub fn is_fail(&self) -> bool {
|
||||
if !self["status"].is_string() {
|
||||
panic!("Called `is_fail` on {}", serde_json::to_string_pretty(&self.0).unwrap());
|
||||
}
|
||||
self["status"] == serde_json::Value::String(String::from("failed"))
|
||||
}
|
||||
|
||||
// Panic if the json doesn't contain the `status` field set to "succeeded"
|
||||
#[track_caller]
|
||||
pub fn failed(&self) -> &Self {
|
||||
if !self.is_fail() {
|
||||
panic!("Called failed on {}", serde_json::to_string_pretty(&self.0).unwrap());
|
||||
}
|
||||
self
|
||||
}
|
||||
}
|
||||
|
||||
impl From<serde_json::Value> for Value {
|
||||
|
@ -1681,7 +1681,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "The `_geo` field in the document with the id: `\"11\"` is not an object. Was expecting an object with the `_geo.lat` and `_geo.lng` fields but instead got `\"foobar\"`.",
|
||||
"message": "Index `test`: The `_geo` field in the document with the id: `\"11\"` is not an object. Was expecting an object with the `_geo.lat` and `_geo.lng` fields but instead got `\"foobar\"`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -1719,7 +1719,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not find latitude nor longitude in the document with the id: `\"11\"`. Was expecting `_geo.lat` and `_geo.lng` fields.",
|
||||
"message": "Index `test`: Could not find latitude nor longitude in the document with the id: `\"11\"`. Was expecting `_geo.lat` and `_geo.lng` fields.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -1757,7 +1757,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not find latitude nor longitude in the document with the id: `\"11\"`. Was expecting `_geo.lat` and `_geo.lng` fields.",
|
||||
"message": "Index `test`: Could not find latitude nor longitude in the document with the id: `\"11\"`. Was expecting `_geo.lat` and `_geo.lng` fields.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -1795,7 +1795,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not find longitude in the document with the id: `\"11\"`. Was expecting a `_geo.lng` field.",
|
||||
"message": "Index `test`: Could not find longitude in the document with the id: `\"11\"`. Was expecting a `_geo.lng` field.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -1833,7 +1833,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not find latitude in the document with the id: `\"11\"`. Was expecting a `_geo.lat` field.",
|
||||
"message": "Index `test`: Could not find latitude in the document with the id: `\"11\"`. Was expecting a `_geo.lat` field.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -1871,7 +1871,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not find longitude in the document with the id: `\"11\"`. Was expecting a `_geo.lng` field.",
|
||||
"message": "Index `test`: Could not find longitude in the document with the id: `\"11\"`. Was expecting a `_geo.lng` field.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -1909,7 +1909,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not find latitude in the document with the id: `\"11\"`. Was expecting a `_geo.lat` field.",
|
||||
"message": "Index `test`: Could not find latitude in the document with the id: `\"11\"`. Was expecting a `_geo.lat` field.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -1947,7 +1947,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not parse latitude nor longitude in the document with the id: `\"11\"`. Was expecting finite numbers but instead got `false` and `true`.",
|
||||
"message": "Index `test`: Could not parse latitude nor longitude in the document with the id: `\"11\"`. Was expecting finite numbers but instead got `false` and `true`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -1985,7 +1985,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not find longitude in the document with the id: `\"11\"`. Was expecting a `_geo.lng` field.",
|
||||
"message": "Index `test`: Could not find longitude in the document with the id: `\"11\"`. Was expecting a `_geo.lng` field.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -2023,7 +2023,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not find latitude in the document with the id: `\"11\"`. Was expecting a `_geo.lat` field.",
|
||||
"message": "Index `test`: Could not find latitude in the document with the id: `\"11\"`. Was expecting a `_geo.lat` field.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -2061,7 +2061,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not parse latitude nor longitude in the document with the id: `\"11\"`. Was expecting finite numbers but instead got `\"doggo\"` and `\"doggo\"`.",
|
||||
"message": "Index `test`: Could not parse latitude nor longitude in the document with the id: `\"11\"`. Was expecting finite numbers but instead got `\"doggo\"` and `\"doggo\"`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -2099,7 +2099,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "The `_geo` field in the document with the id: `\"11\"` contains the following unexpected fields: `{\"doggo\":\"are the best\"}`.",
|
||||
"message": "Index `test`: The `_geo` field in the document with the id: `\"11\"` contains the following unexpected fields: `{\"doggo\":\"are the best\"}`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -2138,7 +2138,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not parse longitude in the document with the id: `\"12\"`. Was expecting a finite number but instead got `null`.",
|
||||
"message": "Index `test`: Could not parse longitude in the document with the id: `\"12\"`. Was expecting a finite number but instead got `null`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -2175,7 +2175,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not parse latitude in the document with the id: `\"12\"`. Was expecting a finite number but instead got `null`.",
|
||||
"message": "Index `test`: Could not parse latitude in the document with the id: `\"12\"`. Was expecting a finite number but instead got `null`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -2212,7 +2212,7 @@ async fn add_documents_invalid_geo_field() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not parse latitude nor longitude in the document with the id: `\"13\"`. Was expecting finite numbers but instead got `null` and `null`.",
|
||||
"message": "Index `test`: Could not parse latitude nor longitude in the document with the id: `\"13\"`. Was expecting finite numbers but instead got `null` and `null`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
@ -2279,7 +2279,7 @@ async fn add_invalid_geo_and_then_settings() {
|
||||
]
|
||||
},
|
||||
"error": {
|
||||
"message": "Could not parse latitude in the document with the id: `\"11\"`. Was expecting a finite number but instead got `null`.",
|
||||
"message": "Index `test`: Could not parse latitude in the document with the id: `\"11\"`. Was expecting a finite number but instead got `null`.",
|
||||
"code": "invalid_document_geo_field",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
|
||||
|
@ -604,7 +604,7 @@ async fn delete_document_by_filter() {
|
||||
"originalFilter": "\"doggo = bernese\""
|
||||
},
|
||||
"error": {
|
||||
"message": "Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
|
||||
"message": "Index `EMPTY_INDEX`: Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
|
||||
"code": "invalid_document_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"
|
||||
@ -636,7 +636,7 @@ async fn delete_document_by_filter() {
|
||||
"originalFilter": "\"catto = jorts\""
|
||||
},
|
||||
"error": {
|
||||
"message": "Attribute `catto` is not filterable. Available filterable attributes are: `id`, `title`.\n1:6 catto = jorts",
|
||||
"message": "Index `SHARED_DOCUMENTS`: Attribute `catto` is not filterable. Available filterable attributes are: `id`, `title`.\n1:6 catto = jorts",
|
||||
"code": "invalid_document_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"
|
||||
|
@ -95,7 +95,7 @@ async fn error_update_existing_primary_key() {
|
||||
let response = index.wait_task(2).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Index already has a primary key: `id`.",
|
||||
"message": "Index `test`: Index already has a primary key: `id`.",
|
||||
"code": "index_primary_key_already_exists",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#index_primary_key_already_exists"
|
||||
|
@ -711,7 +711,7 @@ async fn filter_invalid_attribute_array() {
|
||||
index.wait_task(task.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
|
||||
"message": format!("Index `{}`: Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass", index.uid),
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -733,7 +733,7 @@ async fn filter_invalid_attribute_string() {
|
||||
index.wait_task(task.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
|
||||
"message": format!("Index `{}`: Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass", index.uid),
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -940,7 +940,7 @@ async fn sort_unsortable_attribute() {
|
||||
index.wait_task(response.uid()).await.succeeded();
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Attribute `title` is not sortable. Available sortable attributes are: `id`.",
|
||||
"message": format!("Index `{}`: Attribute `title` is not sortable. Available sortable attributes are: `id`.", index.uid),
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
@ -998,7 +998,7 @@ async fn sort_unset_ranking_rule() {
|
||||
index.wait_task(response.uid()).await.succeeded();
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "You must specify where `sort` is listed in the rankingRules setting to use the sort parameter at search time.",
|
||||
"message": format!("Index `{}`: You must specify where `sort` is listed in the rankingRules setting to use the sort parameter at search time.", index.uid),
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
@ -1024,19 +1024,18 @@ async fn search_on_unknown_field() {
|
||||
index.update_settings_searchable_attributes(json!(["id", "title"])).await;
|
||||
index.wait_task(response.uid()).await.succeeded();
|
||||
|
||||
let expected_response = json!({
|
||||
"message": format!("Index `{}`: Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.", index.uid),
|
||||
"code": "invalid_search_attributes_to_search_on",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
|
||||
});
|
||||
index
|
||||
.search(
|
||||
json!({"q": "Captain Marvel", "attributesToSearchOn": ["unknown"]}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"code": "invalid_search_attributes_to_search_on",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
|
||||
}
|
||||
"###);
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
},
|
||||
)
|
||||
.await;
|
||||
@ -1050,19 +1049,18 @@ async fn search_on_unknown_field_plus_joker() {
|
||||
index.update_settings_searchable_attributes(json!(["id", "title"])).await;
|
||||
index.wait_task(response.uid()).await.succeeded();
|
||||
|
||||
let expected_response = json!({
|
||||
"message": format!("Index `{}`: Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.", index.uid),
|
||||
"code": "invalid_search_attributes_to_search_on",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
|
||||
});
|
||||
index
|
||||
.search(
|
||||
json!({"q": "Captain Marvel", "attributesToSearchOn": ["*", "unknown"]}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"code": "invalid_search_attributes_to_search_on",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
|
||||
}
|
||||
"###);
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
},
|
||||
)
|
||||
.await;
|
||||
@ -1071,15 +1069,8 @@ async fn search_on_unknown_field_plus_joker() {
|
||||
.search(
|
||||
json!({"q": "Captain Marvel", "attributesToSearchOn": ["unknown", "*"]}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Attribute `unknown` is not searchable. Available searchable attributes are: `id, title`.",
|
||||
"code": "invalid_search_attributes_to_search_on",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_search_on"
|
||||
}
|
||||
"###);
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
},
|
||||
)
|
||||
.await;
|
||||
@ -1092,47 +1083,44 @@ async fn distinct_at_search_time() {
|
||||
let (task, _) = index.create(None).await;
|
||||
index.wait_task(task.uid()).await.succeeded();
|
||||
|
||||
let expected_response = json!({
|
||||
"message": format!("Index `{}`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. This index does not have configured filterable attributes.", index.uid),
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
});
|
||||
let (response, code) =
|
||||
index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. This index does not have configured filterable attributes.",
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
}
|
||||
"###);
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
|
||||
let (task, _) = index.update_settings_filterable_attributes(json!(["color", "machin"])).await;
|
||||
index.wait_task(task.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": format!("Index `{}`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, machin`.", index.uid),
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
});
|
||||
let (response, code) =
|
||||
index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, machin`.",
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
}
|
||||
"###);
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
|
||||
let (task, _) = index.update_settings_displayed_attributes(json!(["color"])).await;
|
||||
index.wait_task(task.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": format!("Index `{}`: Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, <..hidden-attributes>`.", index.uid),
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
});
|
||||
let (response, code) =
|
||||
index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, <..hidden-attributes>`.",
|
||||
"code": "invalid_search_distinct",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
|
||||
}
|
||||
"###);
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
|
||||
let (response, code) =
|
||||
index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": true})).await;
|
||||
|
@ -221,8 +221,15 @@ async fn add_documents_and_deactivate_facet_search() {
|
||||
let (response, code) =
|
||||
index.facet_search(json!({"facetName": "genres", "facetQuery": "a"})).await;
|
||||
|
||||
assert_eq!(code, 200, "{}", response);
|
||||
assert_eq!(dbg!(response)["facetHits"].as_array().unwrap().len(), 0);
|
||||
assert_eq!(code, 400, "{}", response);
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "The facet search is disabled for this index",
|
||||
"code": "facet_search_disabled",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#facet_search_disabled"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
@ -245,8 +252,15 @@ async fn deactivate_facet_search_and_add_documents() {
|
||||
let (response, code) =
|
||||
index.facet_search(json!({"facetName": "genres", "facetQuery": "a"})).await;
|
||||
|
||||
assert_eq!(code, 200, "{}", response);
|
||||
assert_eq!(dbg!(response)["facetHits"].as_array().unwrap().len(), 0);
|
||||
assert_eq!(code, 400, "{}", response);
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "The facet search is disabled for this index",
|
||||
"code": "facet_search_disabled",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#facet_search_disabled"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
|
@ -1070,7 +1070,7 @@ async fn federation_one_query_error() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[1]`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
|
||||
"message": "Inside `.queries[1]`: Index `nested`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -1102,7 +1102,7 @@ async fn federation_one_query_sort_error() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[1]`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
|
||||
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
@ -1166,7 +1166,7 @@ async fn federation_multiple_query_errors() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[0]`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
|
||||
"message": "Inside `.queries[0]`: Index `test`: Attribute `title` is not filterable. This index does not have configured filterable attributes.\n1:6 title = toto",
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -1198,7 +1198,7 @@ async fn federation_multiple_query_sort_errors() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[0]`: Attribute `title` is not sortable. This index does not have configured sortable attributes.",
|
||||
"message": "Inside `.queries[0]`: Index `test`: Attribute `title` is not sortable. This index does not have configured sortable attributes.",
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
@ -1231,7 +1231,7 @@ async fn federation_multiple_query_errors_interleaved() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[1]`: Attribute `doggos` is not filterable. This index does not have configured filterable attributes.\n1:7 doggos IN [intel, kefir]",
|
||||
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not filterable. This index does not have configured filterable attributes.\n1:7 doggos IN [intel, kefir]",
|
||||
"code": "invalid_search_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_filter"
|
||||
@ -1264,7 +1264,7 @@ async fn federation_multiple_query_sort_errors_interleaved() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Inside `.queries[1]`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
|
||||
"message": "Inside `.queries[1]`: Index `nested`: Attribute `doggos` is not sortable. This index does not have configured sortable attributes.",
|
||||
"code": "invalid_search_sort",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_search_sort"
|
||||
|
@ -129,11 +129,11 @@ async fn perform_on_demand_snapshot() {
|
||||
|
||||
index.load_test_set().await;
|
||||
|
||||
server.index("doggo").create(Some("bone")).await;
|
||||
index.wait_task(2).await;
|
||||
let (task, _) = server.index("doggo").create(Some("bone")).await;
|
||||
index.wait_task(task.uid()).await.succeeded();
|
||||
|
||||
server.index("doggo").create(Some("bone")).await;
|
||||
index.wait_task(2).await;
|
||||
let (task, _) = server.index("doggo").create(Some("bone")).await;
|
||||
index.wait_task(task.uid()).await.failed();
|
||||
|
||||
let (task, code) = server.create_snapshot().await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
|
@ -448,7 +448,7 @@ async fn test_summarized_delete_documents_by_filter() {
|
||||
"originalFilter": "\"doggo = bernese\""
|
||||
},
|
||||
"error": {
|
||||
"message": "Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
|
||||
"message": "Index `test`: Attribute `doggo` is not filterable. This index does not have configured filterable attributes.\n1:6 doggo = bernese",
|
||||
"code": "invalid_document_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_document_filter"
|
||||
|
@ -318,7 +318,7 @@ async fn try_to_disable_binary_quantization() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "`.embedders.manual.binaryQuantized`: Cannot disable the binary quantization.\n - Note: Binary quantization is a lossy operation that cannot be reverted.\n - Hint: Add a new embedder that is non-quantized and regenerate the vectors.",
|
||||
"message": "Index `doggo`: `.embedders.manual.binaryQuantized`: Cannot disable the binary quantization.\n - Note: Binary quantization is a lossy operation that cannot be reverted.\n - Hint: Add a new embedder that is non-quantized and regenerate the vectors.",
|
||||
"code": "invalid_settings_embedders",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
|
||||
|
@ -250,7 +250,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Missing field `._vectors.manual.regenerate`\n - note: `._vectors.manual` must be an array of floats, an array of arrays of floats, or an object with field `regenerate`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Missing field `._vectors.manual.regenerate`\n - note: `._vectors.manual` must be an array of floats, an array of arrays of floats, or an object with field `regenerate`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -280,7 +280,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Missing field `._vectors.manual.regenerate`\n - note: `._vectors.manual` must be an array of floats, an array of arrays of floats, or an object with field `regenerate`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Missing field `._vectors.manual.regenerate`\n - note: `._vectors.manual` must be an array of floats, an array of arrays of floats, or an object with field `regenerate`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -311,7 +311,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Could not parse `._vectors.manual.regenerate`: invalid type: string \"yes please\", expected a boolean at line 1 column 26",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Could not parse `._vectors.manual.regenerate`: invalid type: string \"yes please\", expected a boolean at line 1 column 26",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -340,7 +340,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings`: expected null or an array, but found a boolean: `true`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings`: expected null or an array, but found a boolean: `true`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -369,7 +369,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -398,7 +398,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -440,7 +440,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -469,7 +469,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[1]`: expected an array, but found a number: `0.3`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[1]`: expected an array, but found a number: `0.3`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -498,7 +498,7 @@ async fn user_provided_embeddings_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[0][1]`: expected a number, but found a boolean: `true`",
|
||||
"message": "Index `doggo`: Bad embedder configuration in the document with id: `0`. Invalid value type at `._vectors.manual.embeddings[0][1]`: expected a number, but found a boolean: `true`",
|
||||
"code": "invalid_vectors_type",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
|
||||
@ -539,7 +539,7 @@ async fn user_provided_vectors_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `manual`: no vectors provided for document `40` and at least 4 other document(s)\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: opt-out for a document with `_vectors.manual: null`",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document `40` and at least 4 other document(s)\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: opt-out for a document with `_vectors.manual: null`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -569,7 +569,7 @@ async fn user_provided_vectors_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `manual`: no vectors provided for document `42`\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vector` by `_vectors` in 1 document(s).",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document `42`\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vector` by `_vectors` in 1 document(s).",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -599,7 +599,7 @@ async fn user_provided_vectors_error() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `manual`: no vectors provided for document `42`\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vectors.manaul` by `_vectors.manual` in 1 document(s).",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `manual`: no vectors provided for document `42`\n- Note: `manual` has `source: userProvided`, so documents must provide embeddings as an array in `_vectors.manual`.\n- Hint: try replacing `_vectors.manaul` by `_vectors.manual` in 1 document(s).",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
|
@ -713,7 +713,7 @@ async fn bad_api_key() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"Incorrect API key provided: Bearer doggo. You can find your API key at https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":\"invalid_api_key\"}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"Incorrect API key provided: Bearer doggo. You can find your API key at https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":\"invalid_api_key\"}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -757,7 +757,7 @@ async fn bad_api_key() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"You didn't provide an API key. You need to provide your API key in an Authorization header using Bearer auth (i.e. Authorization: Bearer YOUR_KEY), or as the password field (with blank username) if you're accessing the API from your browser and are prompted for a username and password. You can obtain an API key from https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":null}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `default`: user error: could not authenticate against OpenAI server\n - server replied with `{\"error\":{\"message\":\"You didn't provide an API key. You need to provide your API key in an Authorization header using Bearer auth (i.e. Authorization: Bearer YOUR_KEY), or as the password field (with blank username) if you're accessing the API from your browser and are prompted for a username and password. You can obtain an API key from https://platform.openai.com/account/api-keys.\",\"type\":\"invalid_request_error\",\"param\":null,\"code\":null}}`\n - Hint: Check the `apiKey` parameter in the embedder configuration, and the `MEILI_OPENAI_API_KEY` and `OPENAI_API_KEY` environment variables",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
|
@ -985,7 +985,7 @@ async fn bad_settings() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting a single \"{{embedding}}\", expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting a single \"{{embedding}}\", expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1025,7 +1025,7 @@ async fn bad_settings() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `rest`: runtime error: was expecting embeddings of dimension `2`, got embeddings of dimensions `3`",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `rest`: runtime error: was expecting embeddings of dimension `2`, got embeddings of dimensions `3`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1178,7 +1178,7 @@ async fn server_returns_bad_request() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"test\\\", expected struct MultipleRequest at line 1 column 6\"}`",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"test\\\", expected struct MultipleRequest at line 1 column 6\"}`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1247,7 +1247,7 @@ async fn server_returns_bad_request() {
|
||||
"indexedDocuments": 0
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `rest`: user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"name: kefir\\\\n\\\", expected struct MultipleRequest at line 1 column 15\"}`",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `rest`: user error: sent a bad request to embedding server\n - Hint: check that the `request` in the embedder configuration matches the remote server's API\n - server replied with `{\"error\":\"Invalid request: invalid type: string \\\"name: kefir\\\\n\\\", expected struct MultipleRequest at line 1 column 15\"}`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1306,7 +1306,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting the array of \"{{embedding}}\"s, configuration expects `response` to be an array with at least 1 item(s) but server sent an object with 1 field(s)",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting the array of \"{{embedding}}\"s, configuration expects `response` to be an array with at least 1 item(s) but server sent an object with 1 field(s)",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1362,7 +1362,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting item #0 from the array of \"{{embedding}}\"s, expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response`, while extracting item #0 from the array of \"{{embedding}}\"s, expected `response` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected a sequence",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1414,7 +1414,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output`, while extracting a single \"{{embedding}}\", expected `output` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected f32",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output`, while extracting a single \"{{embedding}}\", expected `output` to be an array of numbers, but failed to parse server response:\n - invalid type: map, expected f32",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1478,7 +1478,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.embedding`, while extracting item #0 from the array of \"{{embedding}}\"s, configuration expects `embedding` to be an object with key `data` but server sent an array of size 3",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.embedding`, while extracting item #0 from the array of \"{{embedding}}\"s, configuration expects `embedding` to be an object with key `data` but server sent an array of size 3",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1542,7 +1542,7 @@ async fn server_returns_bad_response() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output[0]`, while extracting a single \"{{embedding}}\", configuration expects key \"embeddings\", which is missing in response\n - Hint: item #0 inside `output` has key `embedding`, did you mean `response.output[0].embedding` in embedder configuration?",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with runtime error: error extracting embeddings from the response:\n - in `response.output[0]`, while extracting a single \"{{embedding}}\", configuration expects key \"embeddings\", which is missing in response\n - Hint: item #0 inside `output` has key `embedding`, did you mean `response.output[0].embedding` in embedder configuration?",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1908,7 +1908,7 @@ async fn server_custom_header() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"missing header 'my-nonstandard-auth'\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"missing header 'my-nonstandard-auth'\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -1951,7 +1951,7 @@ async fn server_custom_header() {
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"message": "Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"thou shall not pass, Balrog\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
|
||||
"message": "Index `doggo`: Error while generating embeddings: runtime error: could not determine model dimensions:\n - test embedding failed with user error: could not authenticate against embedding server\n - server replied with `{\"error\":\"thou shall not pass, Balrog\"}`\n - Hint: Check the `apiKey` parameter in the embedder configuration",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
@ -2099,7 +2099,7 @@ async fn searchable_reindex() {
|
||||
]
|
||||
},
|
||||
"error": {
|
||||
"message": "While embedding documents for embedder `rest`: error: received unexpected HTTP 404 from embedding server\n - server replied with `{\"error\":\"text not found\",\"text\":\"breed: patou\\n\"}`",
|
||||
"message": "Index `doggo`: While embedding documents for embedder `rest`: error: received unexpected HTTP 404 from embedding server\n - server replied with `{\"error\":\"text not found\",\"text\":\"breed: patou\\n\"}`",
|
||||
"code": "vector_embedding_error",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#vector_embedding_error"
|
||||
|
@ -21,11 +21,15 @@ use super::ref_cell_ext::RefCellExt;
|
||||
use super::thread_local::{FullySend, ThreadLocal};
|
||||
use super::StdResult;
|
||||
use crate::heed_codec::facet::{FieldDocIdFacetF64Codec, FieldDocIdFacetStringCodec};
|
||||
use crate::heed_codec::StrBEU16Codec;
|
||||
use crate::index::db_name;
|
||||
use crate::index::main_key::{GEO_FACETED_DOCUMENTS_IDS_KEY, GEO_RTREE_KEY};
|
||||
use crate::update::new::KvReaderFieldId;
|
||||
use crate::vector::Embedding;
|
||||
use crate::{CboRoaringBitmapCodec, DocumentId, Error, Index, InternalError};
|
||||
use crate::{
|
||||
CboRoaringBitmapCodec, DocumentId, Error, FieldIdWordCountCodec, Index, InternalError,
|
||||
U8StrStrCodec,
|
||||
};
|
||||
|
||||
/// Creates a tuple of senders/receiver to be used by
|
||||
/// the extractors and the writer loop.
|
||||
@ -403,6 +407,32 @@ impl Database {
|
||||
Database::FieldIdDocidFacetF64s => db_name::FIELD_ID_DOCID_FACET_F64S,
|
||||
}
|
||||
}
|
||||
|
||||
pub fn stringify_key(&self, key: &[u8]) -> String {
|
||||
use heed::types::*;
|
||||
|
||||
match self {
|
||||
Database::WordDocids => format!("{:?}", Str::bytes_decode(key).unwrap()),
|
||||
Database::WordFidDocids => format!("{:?}", StrBEU16Codec::bytes_decode(key).unwrap()),
|
||||
Database::WordPositionDocids => {
|
||||
format!("{:?}", StrBEU16Codec::bytes_decode(key).unwrap())
|
||||
}
|
||||
Database::WordPairProximityDocids => {
|
||||
format!("{:?}", U8StrStrCodec::bytes_decode(key).unwrap())
|
||||
}
|
||||
Database::ExactWordDocids => format!("{:?}", Str::bytes_decode(key).unwrap()),
|
||||
Database::FidWordCountDocids => {
|
||||
format!("{:?}", FieldIdWordCountCodec::bytes_decode(key).unwrap())
|
||||
}
|
||||
Database::FieldIdDocidFacetStrings => {
|
||||
format!("{:?}", FieldDocIdFacetStringCodec::bytes_decode(key).unwrap())
|
||||
}
|
||||
Database::FieldIdDocidFacetF64s => {
|
||||
format!("{:?}", FieldDocIdFacetF64Codec::bytes_decode(key).unwrap())
|
||||
}
|
||||
d => unimplemented!("stringify_key for {:?}", d),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl From<FacetKind> for Database {
|
||||
|
@ -1,7 +1,10 @@
|
||||
use bumpalo::Bump;
|
||||
use heed::RoTxn;
|
||||
|
||||
use super::document::{DocumentFromDb, DocumentFromVersions, MergedDocument, Versions};
|
||||
use super::document::{
|
||||
Document as _, DocumentFromDb, DocumentFromVersions, MergedDocument, Versions,
|
||||
};
|
||||
use super::extract::perm_json_p;
|
||||
use super::vector_document::{
|
||||
MergedVectorDocument, VectorDocumentFromDb, VectorDocumentFromVersions,
|
||||
};
|
||||
@ -164,6 +167,80 @@ impl<'doc> Update<'doc> {
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns whether the updated version of the document is different from the current version for the passed subset of fields.
|
||||
///
|
||||
/// `true` if at least one top-level-field that is a exactly a member of field or a parent of a member of field changed.
|
||||
/// Otherwise `false`.
|
||||
pub fn has_changed_for_fields<'t, Mapper: FieldIdMapper>(
|
||||
&self,
|
||||
fields: Option<&[&str]>,
|
||||
rtxn: &'t RoTxn,
|
||||
index: &'t Index,
|
||||
mapper: &'t Mapper,
|
||||
) -> Result<bool> {
|
||||
let mut changed = false;
|
||||
let mut cached_current = None;
|
||||
let mut updated_selected_field_count = 0;
|
||||
|
||||
for entry in self.updated().iter_top_level_fields() {
|
||||
let (key, updated_value) = entry?;
|
||||
|
||||
if perm_json_p::select_field(key, fields, &[]) == perm_json_p::Selection::Skip {
|
||||
continue;
|
||||
}
|
||||
|
||||
updated_selected_field_count += 1;
|
||||
let current = match cached_current {
|
||||
Some(current) => current,
|
||||
None => self.current(rtxn, index, mapper)?,
|
||||
};
|
||||
let current_value = current.top_level_field(key)?;
|
||||
let Some(current_value) = current_value else {
|
||||
changed = true;
|
||||
break;
|
||||
};
|
||||
|
||||
if current_value.get() != updated_value.get() {
|
||||
changed = true;
|
||||
break;
|
||||
}
|
||||
cached_current = Some(current);
|
||||
}
|
||||
|
||||
if !self.has_deletion {
|
||||
// no field deletion, so fields that don't appear in `updated` cannot have changed
|
||||
return Ok(changed);
|
||||
}
|
||||
|
||||
if changed {
|
||||
return Ok(true);
|
||||
}
|
||||
|
||||
// we saw all updated fields, and set `changed` if any field wasn't in `current`.
|
||||
// so if there are as many fields in `current` as in `updated`, then nothing changed.
|
||||
// If there is any more fields in `current`, then they are missing in `updated`.
|
||||
let has_deleted_fields = {
|
||||
let current = match cached_current {
|
||||
Some(current) => current,
|
||||
None => self.current(rtxn, index, mapper)?,
|
||||
};
|
||||
|
||||
let mut current_selected_field_count = 0;
|
||||
for entry in current.iter_top_level_fields() {
|
||||
let (key, _) = entry?;
|
||||
|
||||
if perm_json_p::select_field(key, fields, &[]) == perm_json_p::Selection::Skip {
|
||||
continue;
|
||||
}
|
||||
current_selected_field_count += 1;
|
||||
}
|
||||
|
||||
current_selected_field_count != updated_selected_field_count
|
||||
};
|
||||
|
||||
Ok(has_deleted_fields)
|
||||
}
|
||||
|
||||
pub fn updated_vectors(
|
||||
&self,
|
||||
doc_alloc: &'doc Bump,
|
||||
|
@ -60,10 +60,9 @@
|
||||
//! For now we can use a grenad sorter for spilling even thought I think
|
||||
//! it's not the most efficient way (too many files open, sorting entries).
|
||||
|
||||
use std::borrow::Borrow;
|
||||
use std::cmp::Ordering;
|
||||
use std::collections::binary_heap::PeekMut;
|
||||
use std::collections::{BTreeMap, BinaryHeap};
|
||||
use std::collections::BinaryHeap;
|
||||
use std::fs::File;
|
||||
use std::hash::BuildHasher;
|
||||
use std::io::BufReader;
|
||||
@ -71,7 +70,10 @@ use std::{io, iter, mem};
|
||||
|
||||
use bumpalo::Bump;
|
||||
use grenad::ReaderCursor;
|
||||
use hashbrown::hash_map::RawEntryMut;
|
||||
use hashbrown::HashMap;
|
||||
use raw_collections::bbbul::{BitPacker, BitPacker4x};
|
||||
use raw_collections::map::FrozenMap;
|
||||
use raw_collections::{Bbbul, FrozenBbbul};
|
||||
use roaring::RoaringBitmap;
|
||||
use rustc_hash::FxBuildHasher;
|
||||
@ -103,7 +105,9 @@ impl<'extractor> BalancedCaches<'extractor> {
|
||||
hasher: FxBuildHasher,
|
||||
max_memory,
|
||||
caches: InnerCaches::Normal(NormalCaches {
|
||||
caches: iter::repeat_with(BTreeMap::new).take(buckets).collect(),
|
||||
caches: iter::repeat_with(|| HashMap::with_hasher_in(FxBuildHasher, alloc))
|
||||
.take(buckets)
|
||||
.collect(),
|
||||
}),
|
||||
alloc,
|
||||
}
|
||||
@ -162,8 +166,8 @@ impl<'extractor> BalancedCaches<'extractor> {
|
||||
rayon::current_thread_index().unwrap_or(0)
|
||||
);
|
||||
|
||||
// let allocated: usize = normal_caches.caches.iter().map(|m| m.allocation_size()).sum();
|
||||
// tracing::trace!("The last allocated BTreeMap took {allocated} bytes");
|
||||
let allocated: usize = normal_caches.caches.iter().map(|m| m.allocation_size()).sum();
|
||||
tracing::trace!("The last allocated HashMap took {allocated} bytes");
|
||||
|
||||
let dummy = NormalCaches { caches: Vec::new() };
|
||||
let NormalCaches { caches: cache_maps } = mem::replace(normal_caches, dummy);
|
||||
@ -183,17 +187,21 @@ impl<'extractor> BalancedCaches<'extractor> {
|
||||
// that are the same size.
|
||||
let map = unsafe {
|
||||
std::mem::transmute::<
|
||||
&mut BTreeMap<
|
||||
&mut HashMap<
|
||||
&[u8],
|
||||
DelAddBbbul<BitPacker4x>, // from this
|
||||
FxBuildHasher,
|
||||
&Bump,
|
||||
>,
|
||||
&mut BTreeMap<
|
||||
&mut HashMap<
|
||||
&[u8],
|
||||
FrozenDelAddBbbul<BitPacker4x>, // to that
|
||||
FxBuildHasher,
|
||||
&Bump,
|
||||
>,
|
||||
>(map)
|
||||
};
|
||||
Ok(FrozenCache { bucket, cache: FrozenBTreeMap::new(map), spilled: Vec::new() })
|
||||
Ok(FrozenCache { bucket, cache: FrozenMap::new(map), spilled: Vec::new() })
|
||||
})
|
||||
.collect(),
|
||||
InnerCaches::Spilling(SpillingCaches { caches, spilled_entries, .. }) => caches
|
||||
@ -212,17 +220,21 @@ impl<'extractor> BalancedCaches<'extractor> {
|
||||
// that are the same size.
|
||||
let map = unsafe {
|
||||
std::mem::transmute::<
|
||||
&mut BTreeMap<
|
||||
&mut HashMap<
|
||||
&[u8],
|
||||
DelAddBbbul<BitPacker4x>, // from this
|
||||
FxBuildHasher,
|
||||
&Bump,
|
||||
>,
|
||||
&mut BTreeMap<
|
||||
&mut HashMap<
|
||||
&[u8],
|
||||
FrozenDelAddBbbul<BitPacker4x>, // to that
|
||||
FxBuildHasher,
|
||||
&Bump,
|
||||
>,
|
||||
>(map)
|
||||
};
|
||||
Ok(FrozenCache { bucket, cache: FrozenBTreeMap::new(map), spilled })
|
||||
Ok(FrozenCache { bucket, cache: FrozenMap::new(map), spilled })
|
||||
})
|
||||
.collect(),
|
||||
}
|
||||
@ -233,7 +245,14 @@ impl<'extractor> BalancedCaches<'extractor> {
|
||||
unsafe impl MostlySend for BalancedCaches<'_> {}
|
||||
|
||||
struct NormalCaches<'extractor> {
|
||||
caches: Vec<BTreeMap<&'extractor [u8], DelAddBbbul<'extractor, BitPacker4x>>>,
|
||||
caches: Vec<
|
||||
HashMap<
|
||||
&'extractor [u8],
|
||||
DelAddBbbul<'extractor, BitPacker4x>,
|
||||
FxBuildHasher,
|
||||
&'extractor Bump,
|
||||
>,
|
||||
>,
|
||||
}
|
||||
|
||||
impl<'extractor> NormalCaches<'extractor> {
|
||||
@ -247,13 +266,17 @@ impl<'extractor> NormalCaches<'extractor> {
|
||||
) {
|
||||
let hash = hasher.hash_one(key);
|
||||
let bucket = compute_bucket_from_hash(buckets, hash);
|
||||
let cache = &mut self.caches[bucket];
|
||||
match cache.get_mut(key) {
|
||||
Some(deladd) => {
|
||||
deladd.del.get_or_insert_with(|| Bbbul::new_in(alloc)).insert(n);
|
||||
|
||||
match self.caches[bucket].raw_entry_mut().from_hash(hash, |&k| k == key) {
|
||||
RawEntryMut::Occupied(mut entry) => {
|
||||
entry.get_mut().del.get_or_insert_with(|| Bbbul::new_in(alloc)).insert(n);
|
||||
}
|
||||
None => {
|
||||
cache.insert(alloc.alloc_slice_copy(key), DelAddBbbul::new_del_u32_in(n, alloc));
|
||||
RawEntryMut::Vacant(entry) => {
|
||||
entry.insert_hashed_nocheck(
|
||||
hash,
|
||||
alloc.alloc_slice_copy(key),
|
||||
DelAddBbbul::new_del_u32_in(n, alloc),
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -268,20 +291,30 @@ impl<'extractor> NormalCaches<'extractor> {
|
||||
) {
|
||||
let hash = hasher.hash_one(key);
|
||||
let bucket = compute_bucket_from_hash(buckets, hash);
|
||||
let cache = &mut self.caches[bucket];
|
||||
match cache.get_mut(key) {
|
||||
Some(deladd) => {
|
||||
deladd.add.get_or_insert_with(|| Bbbul::new_in(alloc)).insert(n);
|
||||
match self.caches[bucket].raw_entry_mut().from_hash(hash, |&k| k == key) {
|
||||
RawEntryMut::Occupied(mut entry) => {
|
||||
entry.get_mut().add.get_or_insert_with(|| Bbbul::new_in(alloc)).insert(n);
|
||||
}
|
||||
None => {
|
||||
cache.insert(alloc.alloc_slice_copy(key), DelAddBbbul::new_add_u32_in(n, alloc));
|
||||
RawEntryMut::Vacant(entry) => {
|
||||
entry.insert_hashed_nocheck(
|
||||
hash,
|
||||
alloc.alloc_slice_copy(key),
|
||||
DelAddBbbul::new_add_u32_in(n, alloc),
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
struct SpillingCaches<'extractor> {
|
||||
caches: Vec<BTreeMap<&'extractor [u8], DelAddBbbul<'extractor, BitPacker4x>>>,
|
||||
caches: Vec<
|
||||
HashMap<
|
||||
&'extractor [u8],
|
||||
DelAddBbbul<'extractor, BitPacker4x>,
|
||||
FxBuildHasher,
|
||||
&'extractor Bump,
|
||||
>,
|
||||
>,
|
||||
spilled_entries: Vec<grenad::Sorter<MergeDeladdCboRoaringBitmaps>>,
|
||||
deladd_buffer: Vec<u8>,
|
||||
cbo_buffer: Vec<u8>,
|
||||
@ -289,7 +322,14 @@ struct SpillingCaches<'extractor> {
|
||||
|
||||
impl<'extractor> SpillingCaches<'extractor> {
|
||||
fn from_cache_maps(
|
||||
caches: Vec<BTreeMap<&'extractor [u8], DelAddBbbul<'extractor, BitPacker4x>>>,
|
||||
caches: Vec<
|
||||
HashMap<
|
||||
&'extractor [u8],
|
||||
DelAddBbbul<'extractor, BitPacker4x>,
|
||||
FxBuildHasher,
|
||||
&'extractor Bump,
|
||||
>,
|
||||
>,
|
||||
) -> SpillingCaches<'extractor> {
|
||||
SpillingCaches {
|
||||
spilled_entries: iter::repeat_with(|| {
|
||||
@ -316,12 +356,12 @@ impl<'extractor> SpillingCaches<'extractor> {
|
||||
) -> Result<()> {
|
||||
let hash = hasher.hash_one(key);
|
||||
let bucket = compute_bucket_from_hash(buckets, hash);
|
||||
match self.caches[bucket].get_mut(key) {
|
||||
Some(deladd) => {
|
||||
deladd.del.get_or_insert_with(|| Bbbul::new_in(alloc)).insert(n);
|
||||
match self.caches[bucket].raw_entry_mut().from_hash(hash, |&k| k == key) {
|
||||
RawEntryMut::Occupied(mut entry) => {
|
||||
entry.get_mut().del.get_or_insert_with(|| Bbbul::new_in(alloc)).insert(n);
|
||||
Ok(())
|
||||
}
|
||||
None => spill_entry_to_sorter(
|
||||
RawEntryMut::Vacant(_entry) => spill_entry_to_sorter(
|
||||
&mut self.spilled_entries[bucket],
|
||||
&mut self.deladd_buffer,
|
||||
&mut self.cbo_buffer,
|
||||
@ -341,12 +381,12 @@ impl<'extractor> SpillingCaches<'extractor> {
|
||||
) -> Result<()> {
|
||||
let hash = hasher.hash_one(key);
|
||||
let bucket = compute_bucket_from_hash(buckets, hash);
|
||||
match self.caches[bucket].get_mut(key) {
|
||||
Some(deladd) => {
|
||||
deladd.add.get_or_insert_with(|| Bbbul::new_in(alloc)).insert(n);
|
||||
match self.caches[bucket].raw_entry_mut().from_hash(hash, |&k| k == key) {
|
||||
RawEntryMut::Occupied(mut entry) => {
|
||||
entry.get_mut().add.get_or_insert_with(|| Bbbul::new_in(alloc)).insert(n);
|
||||
Ok(())
|
||||
}
|
||||
None => spill_entry_to_sorter(
|
||||
RawEntryMut::Vacant(_entry) => spill_entry_to_sorter(
|
||||
&mut self.spilled_entries[bucket],
|
||||
&mut self.deladd_buffer,
|
||||
&mut self.cbo_buffer,
|
||||
@ -401,7 +441,13 @@ fn spill_entry_to_sorter(
|
||||
|
||||
pub struct FrozenCache<'a, 'extractor> {
|
||||
bucket: usize,
|
||||
cache: FrozenBTreeMap<'a, &'extractor [u8], FrozenDelAddBbbul<'extractor, BitPacker4x>>,
|
||||
cache: FrozenMap<
|
||||
'a,
|
||||
'extractor,
|
||||
&'extractor [u8],
|
||||
FrozenDelAddBbbul<'extractor, BitPacker4x>,
|
||||
FxBuildHasher,
|
||||
>,
|
||||
spilled: Vec<grenad::Reader<BufReader<File>>>,
|
||||
}
|
||||
|
||||
@ -420,36 +466,6 @@ pub fn transpose_and_freeze_caches<'a, 'extractor>(
|
||||
Ok(bucket_caches)
|
||||
}
|
||||
|
||||
pub struct FrozenBTreeMap<'a, K, V>(&'a mut BTreeMap<K, V>);
|
||||
|
||||
unsafe impl<'a, K, V> Send for FrozenBTreeMap<'a, K, V>
|
||||
where
|
||||
K: Send,
|
||||
V: Send,
|
||||
{
|
||||
}
|
||||
|
||||
impl<'a, K, V> FrozenBTreeMap<'a, K, V> {
|
||||
#[inline]
|
||||
pub fn new(map: &'a mut BTreeMap<K, V>) -> Self {
|
||||
Self(map)
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn iter_mut(&mut self) -> std::collections::btree_map::IterMut<'_, K, V> {
|
||||
self.0.iter_mut()
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn get_mut<Q>(&mut self, key: &Q) -> Option<&mut V>
|
||||
where
|
||||
K: Borrow<Q> + Ord,
|
||||
Q: Ord + ?Sized,
|
||||
{
|
||||
self.0.get_mut(key)
|
||||
}
|
||||
}
|
||||
|
||||
/// Merges the caches that must be all associated to the same bucket
|
||||
/// but make sure to sort the different buckets before performing the merges.
|
||||
///
|
||||
@ -475,7 +491,7 @@ where
|
||||
for (source_index, source) in readers.into_iter().enumerate() {
|
||||
let mut cursor = source.into_cursor()?;
|
||||
if cursor.move_on_next()?.is_some() {
|
||||
heap.push(CursorEntry { cursor, source_index });
|
||||
heap.push(Entry { cursor, source_index });
|
||||
}
|
||||
}
|
||||
|
||||
@ -528,11 +544,12 @@ where
|
||||
|
||||
// Then manage the content on the HashMap entries that weren't taken (mem::take).
|
||||
while let Some(mut map) = maps.pop() {
|
||||
for (key, bbbul) in map.iter_mut() {
|
||||
if bbbul.is_empty() {
|
||||
continue;
|
||||
}
|
||||
// Make sure we don't try to work with entries already managed by the spilled
|
||||
let mut ordered_entries: Vec<_> =
|
||||
map.iter_mut().filter(|(_, bbbul)| !bbbul.is_empty()).collect();
|
||||
ordered_entries.sort_unstable_by_key(|(key, _)| *key);
|
||||
|
||||
for (key, bbbul) in ordered_entries {
|
||||
let mut output = DelAddRoaringBitmap::empty();
|
||||
output.union_and_clear_bbbul(bbbul);
|
||||
|
||||
@ -550,29 +567,29 @@ where
|
||||
Ok(())
|
||||
}
|
||||
|
||||
struct CursorEntry<R> {
|
||||
struct Entry<R> {
|
||||
cursor: ReaderCursor<R>,
|
||||
source_index: usize,
|
||||
}
|
||||
|
||||
impl<R> Ord for CursorEntry<R> {
|
||||
fn cmp(&self, other: &CursorEntry<R>) -> Ordering {
|
||||
impl<R> Ord for Entry<R> {
|
||||
fn cmp(&self, other: &Entry<R>) -> Ordering {
|
||||
let skey = self.cursor.current().map(|(k, _)| k);
|
||||
let okey = other.cursor.current().map(|(k, _)| k);
|
||||
skey.cmp(&okey).then(self.source_index.cmp(&other.source_index)).reverse()
|
||||
}
|
||||
}
|
||||
|
||||
impl<R> Eq for CursorEntry<R> {}
|
||||
impl<R> Eq for Entry<R> {}
|
||||
|
||||
impl<R> PartialEq for CursorEntry<R> {
|
||||
fn eq(&self, other: &CursorEntry<R>) -> bool {
|
||||
impl<R> PartialEq for Entry<R> {
|
||||
fn eq(&self, other: &Entry<R>) -> bool {
|
||||
self.cmp(other) == Ordering::Equal
|
||||
}
|
||||
}
|
||||
|
||||
impl<R> PartialOrd for CursorEntry<R> {
|
||||
fn partial_cmp(&self, other: &CursorEntry<R>) -> Option<Ordering> {
|
||||
impl<R> PartialOrd for Entry<R> {
|
||||
fn partial_cmp(&self, other: &Entry<R>) -> Option<Ordering> {
|
||||
Some(self.cmp(other))
|
||||
}
|
||||
}
|
||||
|
@ -97,6 +97,15 @@ impl FacetedDocidsExtractor {
|
||||
},
|
||||
),
|
||||
DocumentChange::Update(inner) => {
|
||||
if !inner.has_changed_for_fields(
|
||||
Some(attributes_to_extract),
|
||||
rtxn,
|
||||
index,
|
||||
context.db_fields_ids_map,
|
||||
)? {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
extract_document_facets(
|
||||
attributes_to_extract,
|
||||
inner.current(rtxn, index, context.db_fields_ids_map)?,
|
||||
|
@ -28,7 +28,7 @@ pub struct WordDocidsBalancedCaches<'extractor> {
|
||||
exact_word_docids: BalancedCaches<'extractor>,
|
||||
word_position_docids: BalancedCaches<'extractor>,
|
||||
fid_word_count_docids: BalancedCaches<'extractor>,
|
||||
fid_word_count: HashMap<FieldId, (usize, usize)>,
|
||||
fid_word_count: HashMap<FieldId, (Option<usize>, Option<usize>)>,
|
||||
current_docid: Option<DocumentId>,
|
||||
}
|
||||
|
||||
@ -85,8 +85,8 @@ impl<'extractor> WordDocidsBalancedCaches<'extractor> {
|
||||
|
||||
self.fid_word_count
|
||||
.entry(field_id)
|
||||
.and_modify(|(_current_count, new_count)| *new_count += 1)
|
||||
.or_insert((0, 1));
|
||||
.and_modify(|(_current_count, new_count)| *new_count.get_or_insert(0) += 1)
|
||||
.or_insert((None, Some(1)));
|
||||
self.current_docid = Some(docid);
|
||||
|
||||
Ok(())
|
||||
@ -130,8 +130,8 @@ impl<'extractor> WordDocidsBalancedCaches<'extractor> {
|
||||
|
||||
self.fid_word_count
|
||||
.entry(field_id)
|
||||
.and_modify(|(current_count, _new_count)| *current_count += 1)
|
||||
.or_insert((1, 0));
|
||||
.and_modify(|(current_count, _new_count)| *current_count.get_or_insert(0) += 1)
|
||||
.or_insert((Some(1), None));
|
||||
|
||||
self.current_docid = Some(docid);
|
||||
|
||||
@ -141,14 +141,18 @@ impl<'extractor> WordDocidsBalancedCaches<'extractor> {
|
||||
fn flush_fid_word_count(&mut self, buffer: &mut BumpVec<u8>) -> Result<()> {
|
||||
for (fid, (current_count, new_count)) in self.fid_word_count.drain() {
|
||||
if current_count != new_count {
|
||||
if current_count <= MAX_COUNTED_WORDS {
|
||||
if let Some(current_count) =
|
||||
current_count.filter(|current_count| *current_count <= MAX_COUNTED_WORDS)
|
||||
{
|
||||
buffer.clear();
|
||||
buffer.extend_from_slice(&fid.to_be_bytes());
|
||||
buffer.push(current_count as u8);
|
||||
self.fid_word_count_docids
|
||||
.insert_del_u32(buffer, self.current_docid.unwrap())?;
|
||||
}
|
||||
if new_count <= MAX_COUNTED_WORDS {
|
||||
if let Some(new_count) =
|
||||
new_count.filter(|new_count| *new_count <= MAX_COUNTED_WORDS)
|
||||
{
|
||||
buffer.clear();
|
||||
buffer.extend_from_slice(&fid.to_be_bytes());
|
||||
buffer.push(new_count as u8);
|
||||
@ -351,6 +355,15 @@ impl WordDocidsExtractors {
|
||||
)?;
|
||||
}
|
||||
DocumentChange::Update(inner) => {
|
||||
if !inner.has_changed_for_fields(
|
||||
document_tokenizer.attribute_to_extract,
|
||||
&context.rtxn,
|
||||
context.index,
|
||||
context.db_fields_ids_map,
|
||||
)? {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let mut token_fn = |fname: &str, fid, pos, word: &str| {
|
||||
cached_sorter.insert_del_u32(
|
||||
fid,
|
||||
|
@ -70,6 +70,15 @@ impl SearchableExtractor for WordPairProximityDocidsExtractor {
|
||||
)?;
|
||||
}
|
||||
DocumentChange::Update(inner) => {
|
||||
if !inner.has_changed_for_fields(
|
||||
document_tokenizer.attribute_to_extract,
|
||||
rtxn,
|
||||
index,
|
||||
context.db_fields_ids_map,
|
||||
)? {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let document = inner.current(rtxn, index, context.db_fields_ids_map)?;
|
||||
process_document_tokens(
|
||||
document,
|
||||
|
@ -80,6 +80,15 @@ where
|
||||
let mut bbbuffers = Vec::new();
|
||||
let finished_extraction = AtomicBool::new(false);
|
||||
|
||||
// We reduce the actual memory used to 5%. The reason we do this here and not in Meilisearch
|
||||
// is because we still use the old indexer for the settings and it is highly impacted by the
|
||||
// max memory. So we keep the changes here and will remove these changes once we use the new
|
||||
// indexer to also index settings. Related to #5125 and #5141.
|
||||
let grenad_parameters = GrenadParameters {
|
||||
max_memory: grenad_parameters.max_memory.map(|mm| mm * 5 / 100),
|
||||
..grenad_parameters
|
||||
};
|
||||
|
||||
// We compute and remove the allocated BBQueues buffers capacity from the indexing memory.
|
||||
let minimum_capacity = 50 * 1024 * 1024 * pool.current_num_threads(); // 50 MiB
|
||||
let (grenad_parameters, total_bbbuffer_capacity) = grenad_parameters.max_memory.map_or(
|
||||
|
@ -80,16 +80,35 @@ where
|
||||
}
|
||||
merge_caches_sorted(frozen, |key, DelAddRoaringBitmap { del, add }| {
|
||||
let current = database.get(&rtxn, key)?;
|
||||
match merge_cbo_bitmaps(current, del, add)? {
|
||||
Operation::Write(bitmap) => {
|
||||
|
||||
if let (Some(del), Some(current)) = (&del, ¤t) {
|
||||
let current = CboRoaringBitmapCodec::deserialize_from(current).unwrap();
|
||||
let diff = del - ¤t;
|
||||
let external_ids = index.external_id_of(&rtxn, &diff).unwrap().into_iter().map(|id| id.unwrap()).collect::<Vec<_>>();
|
||||
if !del.is_subset(¤t) {
|
||||
eprintln!(
|
||||
"======================== {:?}: {} -> c: {:?} d: {:?} a: {:?} extra: {:?} extra_external_ids: {:?}",
|
||||
D::DATABASE,
|
||||
D::DATABASE.stringify_key(key),
|
||||
¤t,
|
||||
del,
|
||||
add,
|
||||
diff,
|
||||
external_ids
|
||||
);
|
||||
}
|
||||
}
|
||||
match merge_cbo_bitmaps(current, del, add) {
|
||||
Ok(Operation::Write(bitmap)) => {
|
||||
docids_sender.write(key, &bitmap)?;
|
||||
Ok(())
|
||||
}
|
||||
Operation::Delete => {
|
||||
Ok(Operation::Delete) => {
|
||||
docids_sender.delete(key)?;
|
||||
Ok(())
|
||||
}
|
||||
Operation::Ignore => Ok(()),
|
||||
Ok(Operation::Ignore) => Ok(()),
|
||||
Err(e) => Err(e),
|
||||
}
|
||||
})
|
||||
})
|
||||
@ -234,17 +253,46 @@ fn merge_cbo_bitmaps(
|
||||
(None, Some(_del), Some(add)) => Ok(Operation::Write(add)),
|
||||
(Some(_current), None, None) => Ok(Operation::Ignore), // but it's strange
|
||||
(Some(current), None, Some(add)) => Ok(Operation::Write(current | add)),
|
||||
(Some(current), Some(del), add) => {
|
||||
(Some(current), Some(mut del), add) => {
|
||||
debug_assert!(
|
||||
del.is_subset(¤t),
|
||||
"del is not a subset of current, which must be impossible."
|
||||
);
|
||||
let output = match add {
|
||||
Some(add) => (¤t - del) | add,
|
||||
None => ¤t - del,
|
||||
Some(add) => {
|
||||
del -= &add;
|
||||
|
||||
if del.is_empty() {
|
||||
if add.is_subset(¤t) {
|
||||
// no changes, no allocation
|
||||
None
|
||||
} else {
|
||||
// addition
|
||||
Some(current | add)
|
||||
}
|
||||
} else {
|
||||
if add.is_subset(¤t) {
|
||||
// deletion only, no union
|
||||
Some(current - del)
|
||||
} else {
|
||||
// deletion and addition
|
||||
Some((current - del) | add)
|
||||
}
|
||||
}
|
||||
}
|
||||
// deletion only, no union
|
||||
None => Some(current - del),
|
||||
};
|
||||
if output.is_empty() {
|
||||
Ok(Operation::Delete)
|
||||
} else if current == output {
|
||||
Ok(Operation::Ignore)
|
||||
} else {
|
||||
Ok(Operation::Write(output))
|
||||
|
||||
match output {
|
||||
Some(output) => {
|
||||
if output.is_empty() {
|
||||
Ok(Operation::Delete)
|
||||
} else {
|
||||
Ok(Operation::Write(output))
|
||||
}
|
||||
}
|
||||
None => Ok(Operation::Ignore),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
@ -139,7 +139,7 @@ pub fn run(args: BenchDeriveArgs) -> anyhow::Result<()> {
|
||||
rt.block_on(async {
|
||||
dashboard_client.send_machine_info(&env).await?;
|
||||
|
||||
let commit_message = build_info.commit_msg.context("missing commit message")?.split('\n').next().unwrap();
|
||||
let commit_message = build_info.commit_msg.unwrap_or_default().split('\n').next().unwrap();
|
||||
let max_workloads = args.workload_file.len();
|
||||
let reason: Option<&str> = args.reason.as_deref();
|
||||
let invocation_uuid = dashboard_client.create_invocation(build_info.clone(), commit_message, env, max_workloads, reason).await?;
|
||||
|
Reference in New Issue
Block a user