Add more logging to the received chunks

Remove unused imports
Add a log on the time taken by the incremental facet updating
2025-12-24 21:37:03 +00:00 · 2024-01-25 20:16:59 +01:00 · 2024-01-25 17:58:47 +01:00 · 2024-01-25 17:48:31 +01:00 · 2024-01-25 17:47:33 +01:00
16 changed files with 154 additions and 419 deletions
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -491,7 +491,7 @@ checksum = "8c3c1a368f70d6cf7302d78f8f7093da241fb8e8807c05cc9e51a125895a6d5b"

 [[package]]
 name = "benchmarks"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "anyhow",
 "bytes",
@@ -1402,7 +1402,7 @@ dependencies = [

 [[package]]
 name = "dump"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "anyhow",
 "big_s",
@@ -1634,7 +1634,7 @@ dependencies = [

 [[package]]
 name = "file-store"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "faux",
 "tempfile",
@@ -1656,7 +1656,7 @@ dependencies = [

 [[package]]
 name = "filter-parser"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "insta",
 "nom",
@@ -1687,7 +1687,7 @@ dependencies = [

 [[package]]
 name = "flatten-serde-json"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "criterion",
 "serde_json",
@@ -1805,7 +1805,7 @@ dependencies = [

 [[package]]
 name = "fuzzers"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "arbitrary",
 "clap",
@@ -2763,7 +2763,7 @@ dependencies = [

 [[package]]
 name = "index-scheduler"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "anyhow",
 "big_s",
@@ -2960,7 +2960,7 @@ dependencies = [

 [[package]]
 name = "json-depth-checker"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "criterion",
 "serde_json",
@@ -3472,7 +3472,7 @@ checksum = "490cc448043f947bae3cbee9c203358d62dbee0db12107a74be5c30ccfd09771"

 [[package]]
 name = "meili-snap"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "insta",
 "md5",
@@ -3481,7 +3481,7 @@ dependencies = [

 [[package]]
 name = "meilisearch"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "actix-cors",
 "actix-http",
@@ -3572,7 +3572,7 @@ dependencies = [

 [[package]]
 name = "meilisearch-auth"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "base64 0.21.5",
 "enum-iterator",
@@ -3591,7 +3591,7 @@ dependencies = [

 [[package]]
 name = "meilisearch-types"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "actix-web",
 "anyhow",
@@ -3621,7 +3621,7 @@ dependencies = [

 [[package]]
 name = "meilitool"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "anyhow",
 "clap",
@@ -3669,7 +3669,7 @@ dependencies = [

 [[package]]
 name = "milli"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "arroy",
 "big_s",
@@ -4076,7 +4076,7 @@ checksum = "e3148f5046208a5d56bcfc03053e3ca6334e51da8dfb19b6cdc8b306fae3283e"

 [[package]]
 name = "permissive-json-pointer"
-version = "1.6.1"
+version = "1.6.0"
 dependencies = [
 "big_s",
 "serde_json",
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -19,7 +19,7 @@ members = [
 ]

 [workspace.package]
-version = "1.6.1"
+version = "1.6.0"
 authors = ["Quentin de Quelen <quentin@dequelen.me>", "Clément Renault <clement@meilisearch.com>"]
 description = "Meilisearch HTTP server"
 homepage = "https://meilisearch.com"
--- a/meilisearch/Cargo.toml
+++ b/meilisearch/Cargo.toml
@@ -154,5 +154,5 @@ greek = ["meilisearch-types/greek"]
 khmer = ["meilisearch-types/khmer"]

 [package.metadata.mini-dashboard]
-assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.13/build.zip"
-sha1 = "e20cc9b390003c6c844f4b8bcc5c5013191a77ff"
+assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.12/build.zip"
+sha1 = "acfe9a018c93eb0604ea87ee87bff7df5474e18e"
--- a/meilisearch/tests/common/mod.rs
+++ b/meilisearch/tests/common/mod.rs
@@ -64,7 +64,7 @@ impl Display for Value {
        write!(
            f,
            "{}",
-            json_string!(self, { ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]", ".duration" => "[duration]" })
+            json_string!(self, { ".enqueuedAt" => "[date]", ".processedAt" => "[date]", ".finishedAt" => "[date]", ".duration" => "[duration]" })
        )
    }
 }
--- a/meilisearch/tests/documents/add_documents.rs
+++ b/meilisearch/tests/documents/add_documents.rs
@@ -1760,181 +1760,6 @@ async fn add_documents_invalid_geo_field() {
      "finishedAt": "[date]"
    }
    "###);
-
-    // The three next tests are related to #4333
-
-    // _geo has a lat and lng but set to `null`
-    let documents = json!([
-        {
-            "id": "12",
-            "_geo": { "lng": null, "lat": 67}
-        }
-    ]);
-
-    let (response, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let response = index.wait_task(response.uid()).await;
-    snapshot!(json_string!(response, { ".duration" => "[duration]", ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]" }),
-        @r###"
-    {
-      "uid": 14,
-      "indexUid": "test",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "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"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    // _geo has a lat and lng but set to `null`
-    let documents = json!([
-        {
-            "id": "12",
-            "_geo": { "lng": 35, "lat": null }
-        }
-    ]);
-
-    let (response, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let response = index.wait_task(response.uid()).await;
-    snapshot!(json_string!(response, { ".duration" => "[duration]", ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]" }),
-        @r###"
-    {
-      "uid": 15,
-      "indexUid": "test",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 0
-      },
-      "error": {
-        "message": "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"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    // _geo has a lat and lng but set to `null`
-    let documents = json!([
-        {
-            "id": "13",
-            "_geo": { "lng": null, "lat": null }
-        }
-    ]);
-
-    let (response, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let response = index.wait_task(response.uid()).await;
-    snapshot!(json_string!(response, { ".duration" => "[duration]", ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]" }),
-        @r###"
-    {
-      "uid": 16,
-      "indexUid": "test",
-      "status": "failed",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "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`.",
-        "code": "invalid_document_geo_field",
-        "type": "invalid_request",
-        "link": "https://docs.meilisearch.com/errors#invalid_document_geo_field"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-}
-
-// Related to #4333
-#[actix_rt::test]
-async fn add_invalid_geo_and_then_settings() {
-    let server = Server::new().await;
-    let index = server.index("test");
-    index.create(Some("id")).await;
-
-    // _geo is not an object
-    let documents = json!([
-        {
-            "id": "11",
-            "_geo": { "lat": null, "lng": null },
-        }
-    ]);
-    let (ret, code) = index.add_documents(documents, None).await;
-    snapshot!(code, @"202 Accepted");
-    let ret = index.wait_task(ret.uid()).await;
-    snapshot!(ret, @r###"
-    {
-      "uid": 1,
-      "indexUid": "test",
-      "status": "succeeded",
-      "type": "documentAdditionOrUpdate",
-      "canceledBy": null,
-      "details": {
-        "receivedDocuments": 1,
-        "indexedDocuments": 1
-      },
-      "error": null,
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
-
-    let (ret, code) = index.update_settings(json!({"sortableAttributes": ["_geo"]})).await;
-    snapshot!(code, @"202 Accepted");
-    let ret = index.wait_task(ret.uid()).await;
-    snapshot!(ret, @r###"
-    {
-      "uid": 2,
-      "indexUid": "test",
-      "status": "failed",
-      "type": "settingsUpdate",
-      "canceledBy": null,
-      "details": {
-        "sortableAttributes": [
-          "_geo"
-        ]
-      },
-      "error": {
-        "message": "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"
-      },
-      "duration": "[duration]",
-      "enqueuedAt": "[date]",
-      "startedAt": "[date]",
-      "finishedAt": "[date]"
-    }
-    "###);
 }

 #[actix_rt::test]
--- a/meilisearch/tests/search/hybrid.rs
+++ b/meilisearch/tests/search/hybrid.rs
@@ -87,52 +87,6 @@ async fn simple_search() {
    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_semanticScore":0.99029034},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_semanticScore":0.97434163},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_semanticScore":0.9472136}]"###);
 }

-#[actix_rt::test]
-async fn highlighter() {
-    let server = Server::new().await;
-    let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
-
-    let (response, code) = index
-        .search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
-            "hybrid": {"semanticRatio": 0.2},
-            "attributesToHighlight": [
-                     "desc"
-                   ],
-                   "highlightPreTag": "**BEGIN**",
-                   "highlightPostTag": "**END**"
-        }))
-        .await;
-    snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":["2.0","3.0"]}}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}}},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}}}]"###);
-
-    let (response, code) = index
-        .search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
-            "hybrid": {"semanticRatio": 0.8},
-            "attributesToHighlight": [
-                     "desc"
-                   ],
-                   "highlightPreTag": "**BEGIN**",
-                   "highlightPostTag": "**END**"
-        }))
-        .await;
-    snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":["2.0","3.0"]}},"_semanticScore":0.99029034},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}},"_semanticScore":0.97434163},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}},"_semanticScore":0.9472136}]"###);
-
-    // no highlighting on full semantic
-    let (response, code) = index
-        .search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
-            "hybrid": {"semanticRatio": 1.0},
-            "attributesToHighlight": [
-                     "desc"
-                   ],
-                   "highlightPreTag": "**BEGIN**",
-                   "highlightPostTag": "**END**"
-        }))
-        .await;
-    snapshot!(code, @"200 OK");
-    snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":["2.0","3.0"]}},"_semanticScore":0.99029034},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}},"_semanticScore":0.97434163},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}}}]"###);
-}
-
 #[actix_rt::test]
 async fn invalid_semantic_ratio() {
    let server = Server::new().await;
--- a/milli/src/search/hybrid.rs
+++ b/milli/src/search/hybrid.rs
@@ -102,7 +102,7 @@ impl ScoreWithRatioResult {
        }

        SearchResult {
-            matching_words: right.matching_words,
+            matching_words: left.matching_words,
            candidates: left.candidates | right.candidates,
            documents_ids,
            document_scores,
--- a/milli/src/update/facet/incremental.rs
+++ b/milli/src/update/facet/incremental.rs
@@ -61,6 +61,7 @@ impl FacetsUpdateIncremental {
        }
    }

+    #[logging_timer::time("FacetsUpdateIncremental::{}")]
    pub fn execute(self, wtxn: &mut RwTxn) -> crate::Result<()> {
        let mut cursor = self.delta_data.into_cursor()?;
        while let Some((key, value)) = cursor.move_on_next()? {
--- a/milli/src/update/facet/mod.rs
+++ b/milli/src/update/facet/mod.rs
@@ -76,26 +76,18 @@ pub const FACET_MAX_GROUP_SIZE: u8 = 8;
 pub const FACET_GROUP_SIZE: u8 = 4;
 pub const FACET_MIN_LEVEL_SIZE: u8 = 5;

-use std::collections::BTreeSet;
 use std::fs::File;
 use std::io::BufReader;
-use std::iter::FromIterator;

-use charabia::normalizer::{Normalize, NormalizerOption};
-use grenad::{CompressionType, SortAlgorithm};
-use heed::types::{Bytes, DecodeIgnore, SerdeJson};
-use heed::BytesEncode;
 use log::debug;
 use time::OffsetDateTime;

 use self::incremental::FacetsUpdateIncremental;
 use super::FacetsUpdateBulk;
 use crate::facet::FacetType;
-use crate::heed_codec::facet::{FacetGroupKey, FacetGroupKeyCodec, FacetGroupValueCodec};
+use crate::heed_codec::facet::{FacetGroupKeyCodec, FacetGroupValueCodec};
 use crate::heed_codec::BytesRefCodec;
-use crate::update::index_documents::create_sorter;
-use crate::update::merge_btreeset_string;
-use crate::{BEU16StrCodec, Index, Result, MAX_FACET_VALUE_LENGTH};
+use crate::{Index, Result};

 pub mod bulk;
 pub mod incremental;
@@ -170,91 +162,91 @@ impl<'i> FacetsUpdate<'i> {
            incremental_update.execute(wtxn)?;
        }

-        // We clear the list of normalized-for-search facets
-        // and the previous FSTs to compute everything from scratch
-        self.index.facet_id_normalized_string_strings.clear(wtxn)?;
-        self.index.facet_id_string_fst.clear(wtxn)?;
+        // // We clear the list of normalized-for-search facets
+        // // and the previous FSTs to compute everything from scratch
+        // self.index.facet_id_normalized_string_strings.clear(wtxn)?;
+        // self.index.facet_id_string_fst.clear(wtxn)?;

-        // As we can't use the same write transaction to read and write in two different databases
-        // we must create a temporary sorter that we will write into LMDB afterward.
-        // As multiple unnormalized facet values can become the same normalized facet value
-        // we must merge them together.
-        let mut sorter = create_sorter(
-            SortAlgorithm::Unstable,
-            merge_btreeset_string,
-            CompressionType::None,
-            None,
-            None,
-            None,
-        );
+        // // As we can't use the same write transaction to read and write in two different databases
+        // // we must create a temporary sorter that we will write into LMDB afterward.
+        // // As multiple unnormalized facet values can become the same normalized facet value
+        // // we must merge them together.
+        // let mut sorter = create_sorter(
+        //     SortAlgorithm::Unstable,
+        //     merge_btreeset_string,
+        //     CompressionType::None,
+        //     None,
+        //     None,
+        //     None,
+        // );

-        // We iterate on the list of original, semi-normalized, facet values
-        // and normalize them for search, inserting them in LMDB in any given order.
-        let options = NormalizerOption { lossy: true, ..Default::default() };
-        let database = self.index.facet_id_string_docids.remap_data_type::<DecodeIgnore>();
-        for result in database.iter(wtxn)? {
-            let (facet_group_key, ()) = result?;
-            if let FacetGroupKey { field_id, level: 0, left_bound } = facet_group_key {
-                let mut normalized_facet = left_bound.normalize(&options);
-                let normalized_truncated_facet: String;
-                if normalized_facet.len() > MAX_FACET_VALUE_LENGTH {
-                    normalized_truncated_facet = normalized_facet
-                        .char_indices()
-                        .take_while(|(idx, _)| *idx < MAX_FACET_VALUE_LENGTH)
-                        .map(|(_, c)| c)
-                        .collect();
-                    normalized_facet = normalized_truncated_facet.into();
-                }
-                let set = BTreeSet::from_iter(std::iter::once(left_bound));
-                let key = (field_id, normalized_facet.as_ref());
-                let key = BEU16StrCodec::bytes_encode(&key).map_err(heed::Error::Encoding)?;
-                let val = SerdeJson::bytes_encode(&set).map_err(heed::Error::Encoding)?;
-                sorter.insert(key, val)?;
-            }
-        }
+        // // We iterate on the list of original, semi-normalized, facet values
+        // // and normalize them for search, inserting them in LMDB in any given order.
+        // let options = NormalizerOption { lossy: true, ..Default::default() };
+        // let database = self.index.facet_id_string_docids.remap_data_type::<DecodeIgnore>();
+        // for result in database.iter(wtxn)? {
+        //     let (facet_group_key, ()) = result?;
+        //     if let FacetGroupKey { field_id, level: 0, left_bound } = facet_group_key {
+        //         let mut normalized_facet = left_bound.normalize(&options);
+        //         let normalized_truncated_facet: String;
+        //         if normalized_facet.len() > MAX_FACET_VALUE_LENGTH {
+        //             normalized_truncated_facet = normalized_facet
+        //                 .char_indices()
+        //                 .take_while(|(idx, _)| *idx < MAX_FACET_VALUE_LENGTH)
+        //                 .map(|(_, c)| c)
+        //                 .collect();
+        //             normalized_facet = normalized_truncated_facet.into();
+        //         }
+        //         let set = BTreeSet::from_iter(std::iter::once(left_bound));
+        //         let key = (field_id, normalized_facet.as_ref());
+        //         let key = BEU16StrCodec::bytes_encode(&key).map_err(heed::Error::Encoding)?;
+        //         let val = SerdeJson::bytes_encode(&set).map_err(heed::Error::Encoding)?;
+        //         sorter.insert(key, val)?;
+        //     }
+        // }

-        // In this loop we don't need to take care of merging bitmaps
-        // as the grenad sorter already merged them for us.
-        let mut merger_iter = sorter.into_stream_merger_iter()?;
-        while let Some((key_bytes, btreeset_bytes)) = merger_iter.next()? {
-            self.index.facet_id_normalized_string_strings.remap_types::<Bytes, Bytes>().put(
-                wtxn,
-                key_bytes,
-                btreeset_bytes,
-            )?;
-        }
+        // // In this loop we don't need to take care of merging bitmaps
+        // // as the grenad sorter already merged them for us.
+        // let mut merger_iter = sorter.into_stream_merger_iter()?;
+        // while let Some((key_bytes, btreeset_bytes)) = merger_iter.next()? {
+        //     self.index.facet_id_normalized_string_strings.remap_types::<Bytes, Bytes>().put(
+        //         wtxn,
+        //         key_bytes,
+        //         btreeset_bytes,
+        //     )?;
+        // }

-        // We compute one FST by string facet
-        let mut text_fsts = vec![];
-        let mut current_fst: Option<(u16, fst::SetBuilder<Vec<u8>>)> = None;
-        let database =
-            self.index.facet_id_normalized_string_strings.remap_data_type::<DecodeIgnore>();
-        for result in database.iter(wtxn)? {
-            let ((field_id, normalized_facet), _) = result?;
-            current_fst = match current_fst.take() {
-                Some((fid, fst_builder)) if fid != field_id => {
-                    let fst = fst_builder.into_set();
-                    text_fsts.push((fid, fst));
-                    Some((field_id, fst::SetBuilder::memory()))
-                }
-                Some((field_id, fst_builder)) => Some((field_id, fst_builder)),
-                None => Some((field_id, fst::SetBuilder::memory())),
-            };
+        // // We compute one FST by string facet
+        // let mut text_fsts = vec![];
+        // let mut current_fst: Option<(u16, fst::SetBuilder<Vec<u8>>)> = None;
+        // let database =
+        //     self.index.facet_id_normalized_string_strings.remap_data_type::<DecodeIgnore>();
+        // for result in database.iter(wtxn)? {
+        //     let ((field_id, normalized_facet), _) = result?;
+        //     current_fst = match current_fst.take() {
+        //         Some((fid, fst_builder)) if fid != field_id => {
+        //             let fst = fst_builder.into_set();
+        //             text_fsts.push((fid, fst));
+        //             Some((field_id, fst::SetBuilder::memory()))
+        //         }
+        //         Some((field_id, fst_builder)) => Some((field_id, fst_builder)),
+        //         None => Some((field_id, fst::SetBuilder::memory())),
+        //     };

-            if let Some((_, fst_builder)) = current_fst.as_mut() {
-                fst_builder.insert(normalized_facet)?;
-            }
-        }
+        //     if let Some((_, fst_builder)) = current_fst.as_mut() {
+        //         fst_builder.insert(normalized_facet)?;
+        //     }
+        // }

-        if let Some((field_id, fst_builder)) = current_fst {
-            let fst = fst_builder.into_set();
-            text_fsts.push((field_id, fst));
-        }
+        // if let Some((field_id, fst_builder)) = current_fst {
+        //     let fst = fst_builder.into_set();
+        //     text_fsts.push((field_id, fst));
+        // }

-        // We write those FSTs in LMDB now
-        for (field_id, fst) in text_fsts {
-            self.index.facet_id_string_fst.put(wtxn, &field_id, &fst)?;
-        }
+        // // We write those FSTs in LMDB now
+        // for (field_id, fst) in text_fsts {
+        //     self.index.facet_id_string_fst.put(wtxn, &field_id, &fst)?;
+        // }

        Ok(())
    }
--- a/milli/src/update/index_documents/extract/extract_geo_points.rs
+++ b/milli/src/update/index_documents/extract/extract_geo_points.rs
@@ -34,9 +34,7 @@ pub fn extract_geo_points<R: io::Read + io::Seek>(
        // since we only need the primary key when we throw an error
        // we create this getter to lazily get it when needed
        let document_id = || -> Value {
-            let reader = KvReaderDelAdd::new(obkv.get(primary_key_id).unwrap());
-            let document_id =
-                reader.get(DelAdd::Deletion).or(reader.get(DelAdd::Addition)).unwrap();
+            let document_id = obkv.get(primary_key_id).unwrap();
            serde_json::from_slice(document_id).unwrap()
        };

--- a/milli/src/update/index_documents/extract/extract_vector_points.rs
+++ b/milli/src/update/index_documents/extract/extract_vector_points.rs
@@ -339,7 +339,9 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
    indexer: GrenadParameters,
    embedder: Arc<Embedder>,
 ) -> Result<grenad::Reader<BufReader<File>>> {
-    let n_chunks = embedder.chunk_count_hint(); // chunk level parallelism
+    let rt = tokio::runtime::Builder::new_current_thread().enable_io().enable_time().build()?;
+
+    let n_chunks = embedder.chunk_count_hint(); // chunk level parellelism
    let n_vectors_per_chunk = embedder.prompt_count_in_chunk_hint(); // number of vectors in a single chunk

    // docid, state with embedding
@@ -373,8 +375,11 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
        current_chunk_ids.push(docid);

        if chunks.len() == chunks.capacity() {
-            let chunked_embeds = embedder
-                .embed_chunks(std::mem::replace(&mut chunks, Vec::with_capacity(n_chunks)))
+            let chunked_embeds = rt
+                .block_on(
+                    embedder
+                        .embed_chunks(std::mem::replace(&mut chunks, Vec::with_capacity(n_chunks))),
+                )
                .map_err(crate::vector::Error::from)
                .map_err(crate::Error::from)?;

@@ -391,8 +396,8 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(

    // send last chunk
    if !chunks.is_empty() {
-        let chunked_embeds = embedder
-            .embed_chunks(std::mem::take(&mut chunks))
+        let chunked_embeds = rt
+            .block_on(embedder.embed_chunks(std::mem::take(&mut chunks)))
            .map_err(crate::vector::Error::from)
            .map_err(crate::Error::from)?;
        for (docid, embeddings) in chunks_ids
@@ -405,15 +410,13 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
    }

    if !current_chunk.is_empty() {
-        let embeds = embedder
-            .embed_chunks(vec![std::mem::take(&mut current_chunk)])
+        let embeds = rt
+            .block_on(embedder.embed(std::mem::take(&mut current_chunk)))
            .map_err(crate::vector::Error::from)
            .map_err(crate::Error::from)?;

-        if let Some(embeds) = embeds.first() {
-            for (docid, embeddings) in current_chunk_ids.iter().zip(embeds.iter()) {
-                state_writer.insert(docid.to_be_bytes(), cast_slice(embeddings.as_inner()))?;
-            }
+        for (docid, embeddings) in current_chunk_ids.iter().zip(embeds.iter()) {
+            state_writer.insert(docid.to_be_bytes(), cast_slice(embeddings.as_inner()))?;
        }
    }

--- a/milli/src/update/index_documents/typed_chunk.rs
+++ b/milli/src/update/index_documents/typed_chunk.rs
@@ -123,6 +123,8 @@ pub(crate) fn write_typed_chunk_into_index(
 ) -> Result<(RoaringBitmap, bool)> {
    puffin::profile_function!(typed_chunk.to_debug_string());

+    log::debug!("Received a chunk to process: {}", typed_chunk.to_debug_string());
+
    let mut is_merged_database = false;
    match typed_chunk {
        TypedChunk::Documents(obkv_documents_iter) => {
--- a/milli/src/vector/error.rs
+++ b/milli/src/vector/error.rs
@@ -67,10 +67,6 @@ pub enum EmbedErrorKind {
    OpenAiUnhandledStatusCode(u16),
    #[error("attempt to embed the following text in a configuration where embeddings must be user provided: {0:?}")]
    ManualEmbed(String),
-    #[error("could not initialize asynchronous runtime: {0}")]
-    OpenAiRuntimeInit(std::io::Error),
-    #[error("initializing web client for sending embedding requests failed: {0}")]
-    InitWebClient(reqwest::Error),
 }

 impl EmbedError {
@@ -121,14 +117,6 @@ impl EmbedError {
    pub(crate) fn embed_on_manual_embedder(texts: String) -> EmbedError {
        Self { kind: EmbedErrorKind::ManualEmbed(texts), fault: FaultSource::User }
    }
-
-    pub(crate) fn openai_runtime_init(inner: std::io::Error) -> EmbedError {
-        Self { kind: EmbedErrorKind::OpenAiRuntimeInit(inner), fault: FaultSource::Runtime }
-    }
-
-    pub fn openai_initialize_web_client(inner: reqwest::Error) -> Self {
-        Self { kind: EmbedErrorKind::InitWebClient(inner), fault: FaultSource::Runtime }
-    }
 }

 #[derive(Debug, thiserror::Error)]
@@ -195,6 +183,10 @@ impl NewEmbedderError {
        }
    }

+    pub fn openai_initialize_web_client(inner: reqwest::Error) -> Self {
+        Self { kind: NewEmbedderErrorKind::InitWebClient(inner), fault: FaultSource::Runtime }
+    }
+
    pub fn openai_invalid_api_key_format(inner: reqwest::header::InvalidHeaderValue) -> Self {
        Self { kind: NewEmbedderErrorKind::InvalidApiKeyFormat(inner), fault: FaultSource::User }
    }
@@ -245,6 +237,8 @@ pub enum NewEmbedderErrorKind {
    #[error("loading model failed: {0}")]
    LoadModel(candle_core::Error),
    // openai
+    #[error("initializing web client for sending embedding requests failed: {0}")]
+    InitWebClient(reqwest::Error),
    #[error("The API key passed to Authorization error was in an invalid format: {0}")]
    InvalidApiKeyFormat(reqwest::header::InvalidHeaderValue),
 }
--- a/milli/src/vector/hf.rs
+++ b/milli/src/vector/hf.rs
@@ -145,8 +145,7 @@ impl Embedder {
        let token_ids = tokens
            .iter()
            .map(|tokens| {
-                let mut tokens = tokens.get_ids().to_vec();
-                tokens.truncate(512);
+                let tokens = tokens.get_ids().to_vec();
                Tensor::new(tokens.as_slice(), &self.model.device).map_err(EmbedError::tensor_shape)
            })
            .collect::<Result<Vec<_>, EmbedError>>()?;
--- a/milli/src/vector/mod.rs
+++ b/milli/src/vector/mod.rs
@@ -163,24 +163,18 @@ impl Embedder {
    ) -> std::result::Result<Vec<Embeddings<f32>>, EmbedError> {
        match self {
            Embedder::HuggingFace(embedder) => embedder.embed(texts),
-            Embedder::OpenAi(embedder) => {
-                let client = embedder.new_client()?;
-                embedder.embed(texts, &client).await
-            }
+            Embedder::OpenAi(embedder) => embedder.embed(texts).await,
            Embedder::UserProvided(embedder) => embedder.embed(texts),
        }
    }

-    /// # Panics
-    ///
-    /// - if called from an asynchronous context
-    pub fn embed_chunks(
+    pub async fn embed_chunks(
        &self,
        text_chunks: Vec<Vec<String>>,
    ) -> std::result::Result<Vec<Vec<Embeddings<f32>>>, EmbedError> {
        match self {
            Embedder::HuggingFace(embedder) => embedder.embed_chunks(text_chunks),
-            Embedder::OpenAi(embedder) => embedder.embed_chunks(text_chunks),
+            Embedder::OpenAi(embedder) => embedder.embed_chunks(text_chunks).await,
            Embedder::UserProvided(embedder) => embedder.embed_chunks(text_chunks),
        }
    }
--- a/milli/src/vector/openai.rs
+++ b/milli/src/vector/openai.rs
@@ -8,7 +8,7 @@ use super::{DistributionShift, Embedding, Embeddings};

 #[derive(Debug)]
 pub struct Embedder {
-    headers: reqwest::header::HeaderMap,
+    client: reqwest::Client,
    tokenizer: tiktoken_rs::CoreBPE,
    options: EmbedderOptions,
 }
@@ -95,13 +95,6 @@ impl EmbedderOptions {
 }

 impl Embedder {
-    pub fn new_client(&self) -> Result<reqwest::Client, EmbedError> {
-        reqwest::ClientBuilder::new()
-            .default_headers(self.headers.clone())
-            .build()
-            .map_err(EmbedError::openai_initialize_web_client)
-    }
-
    pub fn new(options: EmbedderOptions) -> Result<Self, NewEmbedderError> {
        let mut headers = reqwest::header::HeaderMap::new();
        let mut inferred_api_key = Default::default();
@@ -118,25 +111,25 @@ impl Embedder {
            reqwest::header::CONTENT_TYPE,
            reqwest::header::HeaderValue::from_static("application/json"),
        );
+        let client = reqwest::ClientBuilder::new()
+            .default_headers(headers)
+            .build()
+            .map_err(NewEmbedderError::openai_initialize_web_client)?;

        // looking at the code it is very unclear that this can actually fail.
        let tokenizer = tiktoken_rs::cl100k_base().unwrap();

-        Ok(Self { options, headers, tokenizer })
+        Ok(Self { options, client, tokenizer })
    }

-    pub async fn embed(
-        &self,
-        texts: Vec<String>,
-        client: &reqwest::Client,
-    ) -> Result<Vec<Embeddings<f32>>, EmbedError> {
+    pub async fn embed(&self, texts: Vec<String>) -> Result<Vec<Embeddings<f32>>, EmbedError> {
        let mut tokenized = false;

        for attempt in 0..7 {
            let result = if tokenized {
-                self.try_embed_tokenized(&texts, client).await
+                self.try_embed_tokenized(&texts).await
            } else {
-                self.try_embed(&texts, client).await
+                self.try_embed(&texts).await
            };

            let retry_duration = match result {
@@ -152,9 +145,9 @@ impl Embedder {
        }

        let result = if tokenized {
-            self.try_embed_tokenized(&texts, client).await
+            self.try_embed_tokenized(&texts).await
        } else {
-            self.try_embed(&texts, client).await
+            self.try_embed(&texts).await
        };

        result.map_err(Retry::into_error)
@@ -232,13 +225,13 @@ impl Embedder {
    async fn try_embed<S: AsRef<str> + serde::Serialize>(
        &self,
        texts: &[S],
-        client: &reqwest::Client,
    ) -> Result<Vec<Embeddings<f32>>, Retry> {
        for text in texts {
            log::trace!("Received prompt: {}", text.as_ref())
        }
        let request = OpenAiRequest { model: self.options.embedding_model.name(), input: texts };
-        let response = client
+        let response = self
+            .client
            .post(OPENAI_EMBEDDINGS_URL)
            .json(&request)
            .send()
@@ -263,11 +256,7 @@ impl Embedder {
            .collect())
    }

-    async fn try_embed_tokenized(
-        &self,
-        text: &[String],
-        client: &reqwest::Client,
-    ) -> Result<Vec<Embeddings<f32>>, Retry> {
+    async fn try_embed_tokenized(&self, text: &[String]) -> Result<Vec<Embeddings<f32>>, Retry> {
        pub const OVERLAP_SIZE: usize = 200;
        let mut all_embeddings = Vec::with_capacity(text.len());
        for text in text {
@@ -275,7 +264,7 @@ impl Embedder {
            let encoded = self.tokenizer.encode_ordinary(text.as_str());
            let len = encoded.len();
            if len < max_token_count {
-                all_embeddings.append(&mut self.try_embed(&[text], client).await?);
+                all_embeddings.append(&mut self.try_embed(&[text]).await?);
                continue;
            }

@@ -284,26 +273,22 @@ impl Embedder {
                Embeddings::new(self.options.embedding_model.dimensions());
            while tokens.len() > max_token_count {
                let window = &tokens[..max_token_count];
-                embeddings_for_prompt.push(self.embed_tokens(window, client).await?).unwrap();
+                embeddings_for_prompt.push(self.embed_tokens(window).await?).unwrap();

                tokens = &tokens[max_token_count - OVERLAP_SIZE..];
            }

            // end of text
-            embeddings_for_prompt.push(self.embed_tokens(tokens, client).await?).unwrap();
+            embeddings_for_prompt.push(self.embed_tokens(tokens).await?).unwrap();

            all_embeddings.push(embeddings_for_prompt);
        }
        Ok(all_embeddings)
    }

-    async fn embed_tokens(
-        &self,
-        tokens: &[usize],
-        client: &reqwest::Client,
-    ) -> Result<Embedding, Retry> {
+    async fn embed_tokens(&self, tokens: &[usize]) -> Result<Embedding, Retry> {
        for attempt in 0..9 {
-            let duration = match self.try_embed_tokens(tokens, client).await {
+            let duration = match self.try_embed_tokens(tokens).await {
                Ok(embedding) => return Ok(embedding),
                Err(retry) => retry.into_duration(attempt),
            }
@@ -312,19 +297,14 @@ impl Embedder {
            tokio::time::sleep(duration).await;
        }

-        self.try_embed_tokens(tokens, client)
-            .await
-            .map_err(|retry| Retry::give_up(retry.into_error()))
+        self.try_embed_tokens(tokens).await.map_err(|retry| Retry::give_up(retry.into_error()))
    }

-    async fn try_embed_tokens(
-        &self,
-        tokens: &[usize],
-        client: &reqwest::Client,
-    ) -> Result<Embedding, Retry> {
+    async fn try_embed_tokens(&self, tokens: &[usize]) -> Result<Embedding, Retry> {
        let request =
            OpenAiTokensRequest { model: self.options.embedding_model.name(), input: tokens };
-        let response = client
+        let response = self
+            .client
            .post(OPENAI_EMBEDDINGS_URL)
            .json(&request)
            .send()
@@ -342,19 +322,12 @@ impl Embedder {
        Ok(response.data.pop().map(|data| data.embedding).unwrap_or_default())
    }

-    pub fn embed_chunks(
+    pub async fn embed_chunks(
        &self,
        text_chunks: Vec<Vec<String>>,
    ) -> Result<Vec<Vec<Embeddings<f32>>>, EmbedError> {
-        let rt = tokio::runtime::Builder::new_current_thread()
-            .enable_io()
-            .enable_time()
-            .build()
-            .map_err(EmbedError::openai_runtime_init)?;
-        let client = self.new_client()?;
-        rt.block_on(futures::future::try_join_all(
-            text_chunks.into_iter().map(|prompts| self.embed(prompts, &client)),
-        ))
+        futures::future::try_join_all(text_chunks.into_iter().map(|prompts| self.embed(prompts)))
+            .await
    }

    pub fn chunk_count_hint(&self) -> usize {
Author	SHA1	Message	Date
Clément Renault	6210377b90	Add more logging to the received chunks	2024-01-25 20:16:59 +01:00
Clément Renault	9e3d1e1bbd	Remove unused imports	2024-01-25 17:58:47 +01:00
Clément Renault	bceaf4f981	Add a log on the time taken by the incremental facet updating	2024-01-25 17:48:31 +01:00
Clément Renault	d29b301618	Disable the facet search	2024-01-25 17:47:33 +01:00