mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-11-26 03:55:07 +08:00
Replace the hnsw crate by the instant-distance one
This commit is contained in:
parent
86d8bb3a3e
commit
29ab54b259
71
Cargo.lock
generated
71
Cargo.lock
generated
@ -1197,12 +1197,6 @@ dependencies = [
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"winapi",
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"winapi",
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]
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]
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[[package]]
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name = "doc-comment"
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version = "0.3.3"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "fea41bba32d969b513997752735605054bc0dfa92b4c56bf1189f2e174be7a10"
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[[package]]
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[[package]]
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name = "dump"
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name = "dump"
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version = "1.3.0"
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version = "1.3.0"
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@ -1707,15 +1701,6 @@ dependencies = [
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"byteorder",
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"byteorder",
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]
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]
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[[package]]
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name = "hashbrown"
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version = "0.11.2"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "ab5ef0d4909ef3724cc8cce6ccc8572c5c817592e9285f5464f8e86f8bd3726e"
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dependencies = [
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"ahash 0.7.6",
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]
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[[package]]
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[[package]]
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name = "hashbrown"
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name = "hashbrown"
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version = "0.12.3"
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version = "0.12.3"
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@ -1814,22 +1799,6 @@ dependencies = [
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"digest",
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"digest",
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]
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]
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[[package]]
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name = "hnsw"
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version = "0.11.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "2b9740ebf8769ec4ad6762cc951ba18f39bba6dfbc2fbbe46285f7539af79752"
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dependencies = [
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"ahash 0.7.6",
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"hashbrown 0.11.2",
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"libm",
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"num-traits",
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"rand_core",
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"serde",
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"smallvec",
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"space",
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]
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[[package]]
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[[package]]
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name = "http"
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name = "http"
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version = "0.2.9"
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version = "0.2.9"
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@ -2008,6 +1977,21 @@ dependencies = [
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"cfg-if",
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"cfg-if",
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]
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]
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[[package]]
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name = "instant-distance"
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version = "0.6.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "8c619cdaa30bb84088963968bee12a45ea5fbbf355f2c021bcd15589f5ca494a"
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dependencies = [
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"num_cpus",
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"ordered-float",
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"parking_lot",
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"rand",
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"rayon",
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"serde",
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"serde-big-array",
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]
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[[package]]
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[[package]]
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name = "io-lifetimes"
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name = "io-lifetimes"
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version = "1.0.11"
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version = "1.0.11"
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@ -2701,9 +2685,9 @@ dependencies = [
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"geoutils",
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"geoutils",
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"grenad",
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"grenad",
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"heed",
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"heed",
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"hnsw",
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"indexmap 1.9.3",
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"indexmap 1.9.3",
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"insta",
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"insta",
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"instant-distance",
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"itertools",
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"itertools",
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"json-depth-checker",
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"json-depth-checker",
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"levenshtein_automata",
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"levenshtein_automata",
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@ -2727,7 +2711,6 @@ dependencies = [
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"smallstr",
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"smallstr",
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"smallvec",
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"smallvec",
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"smartstring",
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"smartstring",
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"space",
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"tempfile",
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"tempfile",
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"thiserror",
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"thiserror",
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"time",
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"time",
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@ -3607,6 +3590,15 @@ dependencies = [
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"serde_derive",
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"serde_derive",
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]
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]
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[[package]]
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name = "serde-big-array"
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version = "0.5.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "11fc7cc2c76d73e0f27ee52abbd64eec84d46f370c88371120433196934e4b7f"
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dependencies = [
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"serde",
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]
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[[package]]
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[[package]]
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name = "serde-cs"
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name = "serde-cs"
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version = "0.2.4"
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version = "0.2.4"
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@ -3756,9 +3748,6 @@ name = "smallvec"
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version = "1.10.0"
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version = "1.10.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "a507befe795404456341dfab10cef66ead4c041f62b8b11bbb92bffe5d0953e0"
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checksum = "a507befe795404456341dfab10cef66ead4c041f62b8b11bbb92bffe5d0953e0"
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dependencies = [
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"serde",
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]
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[[package]]
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[[package]]
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name = "smartstring"
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name = "smartstring"
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@ -3781,16 +3770,6 @@ dependencies = [
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"winapi",
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"winapi",
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]
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]
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[[package]]
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name = "space"
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version = "0.17.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "c5ab9701ae895386d13db622abf411989deff7109b13b46b6173bb4ce5c1d123"
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dependencies = [
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"doc-comment",
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"num-traits",
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]
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[[package]]
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[[package]]
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name = "spin"
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name = "spin"
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version = "0.5.2"
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version = "0.5.2"
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@ -33,8 +33,8 @@ heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.6", default-f
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"lmdb",
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"lmdb",
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"sync-read-txn",
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"sync-read-txn",
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] }
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] }
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hnsw = { version = "0.11.0", features = ["serde1"] }
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indexmap = { version = "1.9.3", features = ["serde"] }
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indexmap = { version = "1.9.3", features = ["serde"] }
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instant-distance = { version = "0.6.1", features = ["with-serde"] }
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json-depth-checker = { path = "../json-depth-checker" }
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json-depth-checker = { path = "../json-depth-checker" }
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levenshtein_automata = { version = "0.2.1", features = ["fst_automaton"] }
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levenshtein_automata = { version = "0.2.1", features = ["fst_automaton"] }
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memmap2 = "0.5.10"
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memmap2 = "0.5.10"
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@ -48,7 +48,6 @@ rstar = { version = "0.10.0", features = ["serde"] }
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serde = { version = "1.0.160", features = ["derive"] }
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serde = { version = "1.0.160", features = ["derive"] }
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serde_json = { version = "1.0.95", features = ["preserve_order"] }
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serde_json = { version = "1.0.95", features = ["preserve_order"] }
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slice-group-by = "0.3.0"
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slice-group-by = "0.3.0"
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space = "0.17.0"
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smallstr = { version = "0.3.0", features = ["serde"] }
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smallstr = { version = "0.3.0", features = ["serde"] }
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smallvec = "1.10.0"
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smallvec = "1.10.0"
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smartstring = "1.0.1"
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smartstring = "1.0.1"
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@ -1,20 +1,36 @@
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use std::ops;
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use instant_distance::Point;
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use serde::{Deserialize, Serialize};
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use serde::{Deserialize, Serialize};
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use space::Metric;
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#[derive(Debug, Default, Clone, Copy, Serialize, Deserialize)]
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use crate::normalize_vector;
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pub struct DotProduct;
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impl Metric<Vec<f32>> for DotProduct {
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#[derive(Debug, Default, Clone, Serialize, Deserialize)]
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type Unit = u32;
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pub struct NDotProductPoint(Vec<f32>);
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// Following <https://docs.rs/space/0.17.0/space/trait.Metric.html>.
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impl NDotProductPoint {
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//
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pub fn new(point: Vec<f32>) -> Self {
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// Here is a playground that validate the ordering of the bit representation of floats in range 0.0..=1.0:
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NDotProductPoint(normalize_vector(point))
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// <https://play.rust-lang.org/?version=stable&mode=debug&edition=2021&gist=6c59e31a3cc5036b32edf51e8937b56e>
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}
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fn distance(&self, a: &Vec<f32>, b: &Vec<f32>) -> Self::Unit {
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let dist = 1.0 - dot_product_similarity(a, b);
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pub fn into_inner(self) -> Vec<f32> {
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self.0
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}
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}
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impl ops::Deref for NDotProductPoint {
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type Target = [f32];
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fn deref(&self) -> &Self::Target {
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self.0.as_slice()
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}
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}
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impl Point for NDotProductPoint {
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fn distance(&self, other: &Self) -> f32 {
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let dist = 1.0 - dot_product_similarity(&self.0, &other.0);
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debug_assert!(!dist.is_nan());
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debug_assert!(!dist.is_nan());
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dist.to_bits()
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dist
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}
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}
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}
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}
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@ -8,12 +8,11 @@ use charabia::{Language, Script};
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use heed::flags::Flags;
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use heed::flags::Flags;
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use heed::types::*;
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use heed::types::*;
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use heed::{CompactionOption, Database, PolyDatabase, RoTxn, RwTxn};
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use heed::{CompactionOption, Database, PolyDatabase, RoTxn, RwTxn};
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use rand_pcg::Pcg32;
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use roaring::RoaringBitmap;
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use roaring::RoaringBitmap;
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use rstar::RTree;
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use rstar::RTree;
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use time::OffsetDateTime;
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use time::OffsetDateTime;
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use crate::distance::DotProduct;
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use crate::distance::NDotProductPoint;
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use crate::error::{InternalError, UserError};
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use crate::error::{InternalError, UserError};
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use crate::facet::FacetType;
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use crate::facet::FacetType;
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use crate::fields_ids_map::FieldsIdsMap;
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use crate::fields_ids_map::FieldsIdsMap;
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@ -31,7 +30,7 @@ use crate::{
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};
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};
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/// The HNSW data-structure that we serialize, fill and search in.
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/// The HNSW data-structure that we serialize, fill and search in.
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pub type Hnsw = hnsw::Hnsw<DotProduct, Vec<f32>, Pcg32, 12, 24>;
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pub type Hnsw = instant_distance::Hnsw<NDotProductPoint>;
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pub const DEFAULT_MIN_WORD_LEN_ONE_TYPO: u8 = 5;
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pub const DEFAULT_MIN_WORD_LEN_ONE_TYPO: u8 = 5;
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pub const DEFAULT_MIN_WORD_LEN_TWO_TYPOS: u8 = 9;
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pub const DEFAULT_MIN_WORD_LEN_TWO_TYPOS: u8 = 9;
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@ -28,7 +28,7 @@ use db_cache::DatabaseCache;
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use exact_attribute::ExactAttribute;
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use exact_attribute::ExactAttribute;
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use graph_based_ranking_rule::{Exactness, Fid, Position, Proximity, Typo};
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use graph_based_ranking_rule::{Exactness, Fid, Position, Proximity, Typo};
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use heed::RoTxn;
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use heed::RoTxn;
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use hnsw::Searcher;
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use instant_distance::Search;
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use interner::{DedupInterner, Interner};
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use interner::{DedupInterner, Interner};
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pub use logger::visual::VisualSearchLogger;
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pub use logger::visual::VisualSearchLogger;
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pub use logger::{DefaultSearchLogger, SearchLogger};
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pub use logger::{DefaultSearchLogger, SearchLogger};
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@ -40,19 +40,18 @@ use ranking_rules::{
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use resolve_query_graph::{compute_query_graph_docids, PhraseDocIdsCache};
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use resolve_query_graph::{compute_query_graph_docids, PhraseDocIdsCache};
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use roaring::RoaringBitmap;
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use roaring::RoaringBitmap;
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use sort::Sort;
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use sort::Sort;
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use space::Neighbor;
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use self::distinct::facet_string_values;
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use self::distinct::facet_string_values;
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use self::geo_sort::GeoSort;
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use self::geo_sort::GeoSort;
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pub use self::geo_sort::Strategy as GeoSortStrategy;
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pub use self::geo_sort::Strategy as GeoSortStrategy;
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use self::graph_based_ranking_rule::Words;
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use self::graph_based_ranking_rule::Words;
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use self::interner::Interned;
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use self::interner::Interned;
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use crate::distance::NDotProductPoint;
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use crate::error::FieldIdMapMissingEntry;
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use crate::error::FieldIdMapMissingEntry;
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use crate::score_details::{ScoreDetails, ScoringStrategy};
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use crate::score_details::{ScoreDetails, ScoringStrategy};
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use crate::search::new::distinct::apply_distinct_rule;
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use crate::search::new::distinct::apply_distinct_rule;
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use crate::{
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use crate::{
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normalize_vector, AscDesc, DocumentId, Filter, Index, Member, Result, TermsMatchingStrategy,
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AscDesc, DocumentId, Filter, Index, Member, Result, TermsMatchingStrategy, UserError, BEU32,
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UserError, BEU32,
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};
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};
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/// A structure used throughout the execution of a search query.
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/// A structure used throughout the execution of a search query.
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@ -445,17 +444,16 @@ pub fn execute_search(
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check_sort_criteria(ctx, sort_criteria.as_ref())?;
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check_sort_criteria(ctx, sort_criteria.as_ref())?;
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if let Some(vector) = vector {
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if let Some(vector) = vector {
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let mut searcher = Searcher::new();
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let mut search = Search::default();
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let hnsw = ctx.index.vector_hnsw(ctx.txn)?.unwrap_or_default();
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let docids = match ctx.index.vector_hnsw(ctx.txn)? {
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let ef = hnsw.len().min(100);
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Some(hnsw) => {
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let mut dest = vec![Neighbor { index: 0, distance: 0 }; ef];
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let vector = NDotProductPoint::new(vector.clone());
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let vector = normalize_vector(vector.clone());
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let neighbors = hnsw.search(&vector, &mut search);
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let neighbors = hnsw.nearest(&vector, ef, &mut searcher, &mut dest[..]);
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let mut docids = Vec::new();
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let mut docids = Vec::new();
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let mut uniq_docids = RoaringBitmap::new();
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let mut uniq_docids = RoaringBitmap::new();
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for Neighbor { index, distance: _ } in neighbors.iter() {
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for instant_distance::Item { distance: _, pid, point: _ } in neighbors {
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let index = BEU32::new(*index as u32);
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let index = BEU32::new(pid.into_inner());
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let docid = ctx.index.vector_id_docid.get(ctx.txn, &index)?.unwrap().get();
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let docid = ctx.index.vector_id_docid.get(ctx.txn, &index)?.unwrap().get();
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if universe.contains(docid) && uniq_docids.insert(docid) {
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if universe.contains(docid) && uniq_docids.insert(docid) {
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docids.push(docid);
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docids.push(docid);
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@ -467,7 +465,10 @@ pub fn execute_search(
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// return the nearest documents that are also part of the candidates
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// return the nearest documents that are also part of the candidates
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// along with a dummy list of scores that are useless in this context.
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// along with a dummy list of scores that are useless in this context.
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let docids: Vec<_> = docids.into_iter().skip(from).take(length).collect();
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docids.into_iter().skip(from).take(length).collect()
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}
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None => Vec::new(),
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};
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return Ok(PartialSearchResult {
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return Ok(PartialSearchResult {
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candidates: universe,
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candidates: universe,
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@ -4,10 +4,9 @@ use std::collections::{BTreeSet, HashMap, HashSet};
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use fst::IntoStreamer;
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use fst::IntoStreamer;
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use heed::types::{ByteSlice, DecodeIgnore, Str, UnalignedSlice};
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use heed::types::{ByteSlice, DecodeIgnore, Str, UnalignedSlice};
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use heed::{BytesDecode, BytesEncode, Database, RwIter};
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use heed::{BytesDecode, BytesEncode, Database, RwIter};
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use hnsw::Searcher;
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use instant_distance::PointId;
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use roaring::RoaringBitmap;
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use roaring::RoaringBitmap;
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use serde::{Deserialize, Serialize};
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use serde::{Deserialize, Serialize};
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use space::KnnPoints;
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use time::OffsetDateTime;
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use time::OffsetDateTime;
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use super::facet::delete::FacetsDelete;
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use super::facet::delete::FacetsDelete;
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@ -436,24 +435,24 @@ impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
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|
||||||
// An ugly and slow way to remove the vectors from the HNSW
|
// An ugly and slow way to remove the vectors from the HNSW
|
||||||
// It basically reconstructs the HNSW from scratch without editing the current one.
|
// It basically reconstructs the HNSW from scratch without editing the current one.
|
||||||
let current_hnsw = self.index.vector_hnsw(self.wtxn)?.unwrap_or_default();
|
if let Some(current_hnsw) = self.index.vector_hnsw(self.wtxn)? {
|
||||||
if !current_hnsw.is_empty() {
|
let mut points = Vec::new();
|
||||||
let mut new_hnsw = Hnsw::default();
|
let mut docids = Vec::new();
|
||||||
let mut searcher = Searcher::new();
|
|
||||||
let mut new_vector_id_docids = Vec::new();
|
|
||||||
|
|
||||||
for result in vector_id_docid.iter(self.wtxn)? {
|
for result in vector_id_docid.iter(self.wtxn)? {
|
||||||
let (vector_id, docid) = result?;
|
let (vector_id, docid) = result?;
|
||||||
if !self.to_delete_docids.contains(docid.get()) {
|
if !self.to_delete_docids.contains(docid.get()) {
|
||||||
let vector = current_hnsw.get_point(vector_id.get() as usize).clone();
|
let pid = PointId::from(vector_id.get());
|
||||||
let vector_id = new_hnsw.insert(vector, &mut searcher);
|
let vector = current_hnsw[pid].clone();
|
||||||
new_vector_id_docids.push((vector_id as u32, docid));
|
points.push(vector);
|
||||||
|
docids.push(docid);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
let (new_hnsw, pids) = Hnsw::builder().build_hnsw(points);
|
||||||
|
|
||||||
vector_id_docid.clear(self.wtxn)?;
|
vector_id_docid.clear(self.wtxn)?;
|
||||||
for (vector_id, docid) in new_vector_id_docids {
|
for (pid, docid) in pids.into_iter().zip(docids) {
|
||||||
vector_id_docid.put(self.wtxn, &BEU32::new(vector_id), &docid)?;
|
vector_id_docid.put(self.wtxn, &BEU32::new(pid.into_inner()), &docid)?;
|
||||||
}
|
}
|
||||||
self.index.put_vector_hnsw(self.wtxn, &new_hnsw)?;
|
self.index.put_vector_hnsw(self.wtxn, &new_hnsw)?;
|
||||||
}
|
}
|
||||||
|
@ -9,22 +9,19 @@ use charabia::{Language, Script};
|
|||||||
use grenad::MergerBuilder;
|
use grenad::MergerBuilder;
|
||||||
use heed::types::ByteSlice;
|
use heed::types::ByteSlice;
|
||||||
use heed::RwTxn;
|
use heed::RwTxn;
|
||||||
use hnsw::Searcher;
|
|
||||||
use roaring::RoaringBitmap;
|
use roaring::RoaringBitmap;
|
||||||
use space::KnnPoints;
|
|
||||||
|
|
||||||
use super::helpers::{
|
use super::helpers::{
|
||||||
self, merge_ignore_values, serialize_roaring_bitmap, valid_lmdb_key, CursorClonableMmap,
|
self, merge_ignore_values, serialize_roaring_bitmap, valid_lmdb_key, CursorClonableMmap,
|
||||||
};
|
};
|
||||||
use super::{ClonableMmap, MergeFn};
|
use super::{ClonableMmap, MergeFn};
|
||||||
|
use crate::distance::NDotProductPoint;
|
||||||
use crate::error::UserError;
|
use crate::error::UserError;
|
||||||
use crate::facet::FacetType;
|
use crate::facet::FacetType;
|
||||||
|
use crate::index::Hnsw;
|
||||||
use crate::update::facet::FacetsUpdate;
|
use crate::update::facet::FacetsUpdate;
|
||||||
use crate::update::index_documents::helpers::{as_cloneable_grenad, try_split_array_at};
|
use crate::update::index_documents::helpers::{as_cloneable_grenad, try_split_array_at};
|
||||||
use crate::{
|
use crate::{lat_lng_to_xyz, CboRoaringBitmapCodec, DocumentId, GeoPoint, Index, Result, BEU32};
|
||||||
lat_lng_to_xyz, normalize_vector, CboRoaringBitmapCodec, DocumentId, GeoPoint, Index, Result,
|
|
||||||
BEU32,
|
|
||||||
};
|
|
||||||
|
|
||||||
pub(crate) enum TypedChunk {
|
pub(crate) enum TypedChunk {
|
||||||
FieldIdDocidFacetStrings(grenad::Reader<CursorClonableMmap>),
|
FieldIdDocidFacetStrings(grenad::Reader<CursorClonableMmap>),
|
||||||
@ -230,17 +227,20 @@ pub(crate) fn write_typed_chunk_into_index(
|
|||||||
index.put_geo_faceted_documents_ids(wtxn, &geo_faceted_docids)?;
|
index.put_geo_faceted_documents_ids(wtxn, &geo_faceted_docids)?;
|
||||||
}
|
}
|
||||||
TypedChunk::VectorPoints(vector_points) => {
|
TypedChunk::VectorPoints(vector_points) => {
|
||||||
let mut hnsw = index.vector_hnsw(wtxn)?.unwrap_or_default();
|
let (pids, mut points): (Vec<_>, Vec<_>) = match index.vector_hnsw(wtxn)? {
|
||||||
let mut searcher = Searcher::new();
|
Some(hnsw) => hnsw.iter().map(|(pid, point)| (pid, point.clone())).unzip(),
|
||||||
|
None => Default::default(),
|
||||||
let mut expected_dimensions = match index.vector_id_docid.iter(wtxn)?.next() {
|
|
||||||
Some(result) => {
|
|
||||||
let (vector_id, _) = result?;
|
|
||||||
Some(hnsw.get_point(vector_id.get() as usize).len())
|
|
||||||
}
|
|
||||||
None => None,
|
|
||||||
};
|
};
|
||||||
|
|
||||||
|
// Convert the PointIds into DocumentIds
|
||||||
|
let mut docids = Vec::new();
|
||||||
|
for pid in pids {
|
||||||
|
let docid =
|
||||||
|
index.vector_id_docid.get(wtxn, &BEU32::new(pid.into_inner()))?.unwrap();
|
||||||
|
docids.push(docid.get());
|
||||||
|
}
|
||||||
|
|
||||||
|
let mut expected_dimensions = points.get(0).map(|p| p.len());
|
||||||
let mut cursor = vector_points.into_cursor()?;
|
let mut cursor = vector_points.into_cursor()?;
|
||||||
while let Some((key, value)) = cursor.move_on_next()? {
|
while let Some((key, value)) = cursor.move_on_next()? {
|
||||||
// convert the key back to a u32 (4 bytes)
|
// convert the key back to a u32 (4 bytes)
|
||||||
@ -256,12 +256,26 @@ pub(crate) fn write_typed_chunk_into_index(
|
|||||||
return Err(UserError::InvalidVectorDimensions { expected, found })?;
|
return Err(UserError::InvalidVectorDimensions { expected, found })?;
|
||||||
}
|
}
|
||||||
|
|
||||||
let vector = normalize_vector(vector);
|
points.push(NDotProductPoint::new(vector));
|
||||||
let vector_id = hnsw.insert(vector, &mut searcher) as u32;
|
docids.push(docid);
|
||||||
index.vector_id_docid.put(wtxn, &BEU32::new(vector_id), &BEU32::new(docid))?;
|
|
||||||
}
|
}
|
||||||
log::debug!("There are {} entries in the HNSW so far", hnsw.len());
|
|
||||||
index.put_vector_hnsw(wtxn, &hnsw)?;
|
assert_eq!(docids.len(), points.len());
|
||||||
|
|
||||||
|
let hnsw_length = points.len();
|
||||||
|
let (new_hnsw, pids) = Hnsw::builder().build_hnsw(points);
|
||||||
|
|
||||||
|
index.vector_id_docid.clear(wtxn)?;
|
||||||
|
for (docid, pid) in docids.into_iter().zip(pids) {
|
||||||
|
index.vector_id_docid.put(
|
||||||
|
wtxn,
|
||||||
|
&BEU32::new(pid.into_inner()),
|
||||||
|
&BEU32::new(docid),
|
||||||
|
)?;
|
||||||
|
}
|
||||||
|
|
||||||
|
log::debug!("There are {} entries in the HNSW so far", hnsw_length);
|
||||||
|
index.put_vector_hnsw(wtxn, &new_hnsw)?;
|
||||||
}
|
}
|
||||||
TypedChunk::ScriptLanguageDocids(hash_pair) => {
|
TypedChunk::ScriptLanguageDocids(hash_pair) => {
|
||||||
let mut buffer = Vec::new();
|
let mut buffer = Vec::new();
|
||||||
|
Loading…
Reference in New Issue
Block a user