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Add embedders stats
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@ -106,6 +106,12 @@ pub struct IndexStats {
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/// are not returned to the disk after a deletion, this number is typically larger than
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/// `used_database_size` that only includes the size of the used pages.
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pub database_size: u64,
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/// Number of embeddings in the index.
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/// Option: retrocompatible with the stats of the pre-v1.13.0 versions of meilisearch
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pub number_of_embeddings: Option<u64>,
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/// Number of embedded documents in the index.
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/// Option: retrocompatible with the stats of the pre-v1.13.0 versions of meilisearch
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pub number_of_embedded_documents: Option<u64>,
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/// Size taken by the used pages of the index' DB, in bytes.
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///
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/// As the DB backend does not return to the disk the pages that are not currently used by the DB,
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@ -130,8 +136,11 @@ impl IndexStats {
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///
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/// - rtxn: a RO transaction for the index, obtained from `Index::read_txn()`.
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pub fn new(index: &Index, rtxn: &RoTxn) -> milli::Result<Self> {
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let arroy_stats = index.arroy_stats(rtxn)?;
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Ok(IndexStats {
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number_of_documents: index.number_of_documents(rtxn)?,
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number_of_embeddings: Some(arroy_stats.number_of_embeddings),
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number_of_embedded_documents: Some(arroy_stats.documents.len()),
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database_size: index.on_disk_size()?,
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used_database_size: index.used_size()?,
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primary_key: index.primary_key(rtxn)?.map(|s| s.to_string()),
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@ -496,6 +496,12 @@ pub struct IndexStats {
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pub number_of_documents: u64,
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/// Whether or not the index is currently ingesting document
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pub is_indexing: bool,
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/// Number of embeddings in the index
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#[serde(skip_serializing_if = "Option::is_none")]
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pub number_of_embeddings: Option<u64>,
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/// Number of embedded documents in the index
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#[serde(skip_serializing_if = "Option::is_none")]
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pub number_of_embedded_documents: Option<u64>,
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/// Association of every field name with the number of times it occurs in the documents.
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#[schema(value_type = HashMap<String, u64>)]
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pub field_distribution: FieldDistribution,
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@ -506,6 +512,8 @@ impl From<index_scheduler::IndexStats> for IndexStats {
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IndexStats {
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number_of_documents: stats.inner_stats.number_of_documents,
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is_indexing: stats.is_indexing,
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number_of_embeddings: stats.inner_stats.number_of_embeddings,
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number_of_embedded_documents: stats.inner_stats.number_of_embedded_documents,
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field_distribution: stats.inner_stats.field_distribution,
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}
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}
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@ -524,6 +532,8 @@ impl From<index_scheduler::IndexStats> for IndexStats {
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(status = OK, description = "The stats of the index", body = IndexStats, content_type = "application/json", example = json!(
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{
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"numberOfDocuments": 10,
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"numberOfEmbeddings": 10,
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"numberOfEmbeddedDocuments": 10,
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"isIndexing": true,
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"fieldDistribution": {
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"genre": 10,
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@ -22,7 +22,7 @@ use crate::heed_codec::version::VersionCodec;
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use crate::heed_codec::{BEU16StrCodec, FstSetCodec, StrBEU16Codec, StrRefCodec};
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use crate::order_by_map::OrderByMap;
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use crate::proximity::ProximityPrecision;
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use crate::vector::{ArroyWrapper, Embedding, EmbeddingConfig};
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use crate::vector::{ArroyStats, ArroyWrapper, Embedding, EmbeddingConfig};
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use crate::{
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default_criteria, CboRoaringBitmapCodec, Criterion, DocumentId, ExternalDocumentsIds,
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FacetDistribution, FieldDistribution, FieldId, FieldIdMapMissingEntry, FieldIdWordCountCodec,
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@ -1731,6 +1731,18 @@ impl Index {
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let compute_prefixes = self.prefix_search(rtxn)?.unwrap_or_default();
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Ok(PrefixSettings { compute_prefixes, max_prefix_length: 4, prefix_count_threshold: 100 })
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}
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pub fn arroy_stats(&self, rtxn: &RoTxn<'_>) -> Result<ArroyStats> {
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let mut stats = ArroyStats::default();
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let embedding_configs = self.embedding_configs(rtxn)?;
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for config in embedding_configs {
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let embedder_id = self.embedder_category_id.get(rtxn, &config.name)?.unwrap();
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let reader =
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ArroyWrapper::new(self.vector_arroy, embedder_id, config.config.quantized());
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reader.aggregate_stats(rtxn, &mut stats)?;
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}
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Ok(stats)
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}
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}
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#[derive(Debug, Deserialize, Serialize)]
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@ -410,8 +410,43 @@ impl ArroyWrapper {
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fn quantized_db(&self) -> arroy::Database<BinaryQuantizedCosine> {
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self.database.remap_data_type()
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}
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pub fn aggregate_stats(
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&self,
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rtxn: &RoTxn,
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stats: &mut ArroyStats,
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) -> Result<(), arroy::Error> {
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if self.quantized {
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for reader in self.readers(rtxn, self.quantized_db()) {
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let reader = reader?;
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let documents = reader.item_ids();
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if documents.is_empty() {
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break;
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}
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stats.documents |= documents;
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stats.number_of_embeddings += documents.len() as u64;
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}
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} else {
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for reader in self.readers(rtxn, self.angular_db()) {
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let reader = reader?;
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let documents = reader.item_ids();
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if documents.is_empty() {
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break;
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}
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stats.documents |= documents;
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stats.number_of_embeddings += documents.len() as u64;
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}
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}
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Ok(())
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}
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}
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#[derive(Debug, Default, Clone)]
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pub struct ArroyStats {
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pub number_of_embeddings: u64,
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pub documents: RoaringBitmap,
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}
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/// One or multiple embeddings stored consecutively in a flat vector.
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pub struct Embeddings<F> {
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data: Vec<F>,
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