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Author SHA1 Message Date
b3952e8b3d Only spawn request threads if necessary 2024-06-18 15:34:39 +02:00
129 changed files with 1321 additions and 8471 deletions

View File

@ -43,11 +43,4 @@ jobs:
- name: Run benchmarks on PR ${{ github.event.issue.id }}
run: |
cargo xtask bench --api-key "${{ secrets.BENCHMARK_API_KEY }}" \
--dashboard-url "${{ vars.BENCHMARK_DASHBOARD_URL }}" \
--reason "[Comment](${{ github.event.comment.html_url }}) on [#${{ github.event.issue.number }}](${{ github.event.issue.html_url }})" \
-- ${{ steps.command.outputs.command-arguments }} > benchlinks.txt
- name: Send comment in PR
run: |
gh pr comment ${{github.event.issue.number}} --body-file benchlinks.txt
cargo xtask bench --api-key "${{ secrets.BENCHMARK_API_KEY }}" --dashboard-url "${{ vars.BENCHMARK_DASHBOARD_URL }}" --reason "[Comment](${{ github.event.comment.html_url }}) on [#${{ github.event.issue.number }}](${{ github.event.issue.html_url }})" -- ${{ steps.command.outputs.command-arguments }}

View File

@ -187,8 +187,8 @@ They are JSON files with the following structure (comments are not actually supp
},
// Core of the workload.
// A list of commands to run sequentially.
// Optional: A precommand is a request to the Meilisearch instance that is executed before the profiling runs.
"precommands": [
// A command is a request to the Meilisearch instance that is executed while the profiling runs.
"commands": [
{
// Meilisearch route to call. `http://localhost:7700/` will be prepended.
"route": "indexes/movies/settings",
@ -224,11 +224,8 @@ They are JSON files with the following structure (comments are not actually supp
// - DontWait: run the next command without waiting the response to this one.
// - WaitForResponse: run the next command as soon as the response from the server is received.
// - WaitForTask: run the next command once **all** the Meilisearch tasks created up to now have finished processing.
"synchronous": "WaitForTask"
}
],
// A command is a request to the Meilisearch instance that is executed while the profiling runs.
"commands": [
"synchronous": "DontWait"
},
{
"route": "indexes/movies/documents",
"method": "POST",

274
Cargo.lock generated
View File

@ -80,7 +80,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e01ed3140b2f8d422c68afa1ed2e85d996ea619c988ac834d255db32138655cb"
dependencies = [
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -378,9 +378,9 @@ dependencies = [
[[package]]
name = "arroy"
version = "0.3.1"
version = "0.2.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "73897699bf04bac935c0b120990d2a511e91e563e0f9769f9c8bb983d98dfbc9"
checksum = "efddeb1e7c32a551cc07ef4c3e181e3cd5478fdaf4f0bd799983171c1f6efe57"
dependencies = [
"bytemuck",
"byteorder",
@ -424,7 +424,7 @@ checksum = "16e62a023e7c117e27523144c5d2459f4397fcc3cab0085af8e2224f643a0193"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -435,7 +435,7 @@ checksum = "c980ee35e870bd1a4d2c8294d4c04d0499e67bca1e4b5cefcc693c2fa00caea9"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -486,12 +486,6 @@ version = "0.21.7"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9d297deb1925b89f2ccc13d7635fa0714f12c87adce1c75356b39ca9b7178567"
[[package]]
name = "base64"
version = "0.22.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "72b3254f16251a8381aa12e40e3c4d2f0199f8c6508fbecb9d91f575e0fbb8c6"
[[package]]
name = "base64ct"
version = "1.6.0"
@ -500,7 +494,7 @@ checksum = "8c3c1a368f70d6cf7302d78f8f7093da241fb8e8807c05cc9e51a125895a6d5b"
[[package]]
name = "benchmarks"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"anyhow",
"bytes",
@ -558,7 +552,7 @@ dependencies = [
"regex",
"rustc-hash",
"shlex",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -645,7 +639,7 @@ dependencies = [
[[package]]
name = "build-info"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"anyhow",
"time",
@ -691,7 +685,7 @@ checksum = "4da9a32f3fed317401fa3c862968128267c3106685286e15d5aaa3d7389c2f60"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -851,9 +845,9 @@ checksum = "37b2a672a2cb129a2e41c10b1224bb368f9f37a2b16b612598138befd7b37eb5"
[[package]]
name = "cc"
version = "1.0.94"
version = "1.0.90"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "17f6e324229dc011159fcc089755d1e2e216a90d43a7dea6853ca740b84f35e7"
checksum = "8cd6604a82acf3039f1144f54b8eb34e91ffba622051189e71b781822d5ee1f5"
dependencies = [
"jobserver",
"libc",
@ -998,7 +992,7 @@ dependencies = [
"heck",
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -1310,7 +1304,7 @@ dependencies = [
"proc-macro2",
"quote",
"strsim",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -1332,7 +1326,7 @@ checksum = "836a9bbc7ad63342d6d6e7b815ccab164bc77a2d95d84bc3117a8c0d5c98e2d5"
dependencies = [
"darling_core 0.20.3",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -1362,7 +1356,7 @@ checksum = "67e77553c4162a157adbf834ebae5b415acbecbeafc7a74b0e886657506a7611"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -1466,7 +1460,7 @@ dependencies = [
"convert_case 0.6.0",
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -1536,16 +1530,16 @@ checksum = "fea41bba32d969b513997752735605054bc0dfa92b4c56bf1189f2e174be7a10"
[[package]]
name = "doxygen-rs"
version = "0.4.2"
version = "0.2.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "415b6ec780d34dcf624666747194393603d0373b7141eef01d12ee58881507d9"
checksum = "bff670ea0c9bbb8414e7efa6e23ebde2b8f520a7eef78273a3918cf1903e7505"
dependencies = [
"phf",
]
[[package]]
name = "dump"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"anyhow",
"big_s",
@ -1684,7 +1678,7 @@ dependencies = [
"heck",
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -1704,7 +1698,7 @@ checksum = "03cdc46ec28bd728e67540c528013c6a10eb69a02eb31078a1bda695438cbfb8"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -1787,13 +1781,13 @@ dependencies = [
"darling 0.20.3",
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
"uuid",
]
[[package]]
name = "file-store"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"faux",
"tempfile",
@ -1816,7 +1810,7 @@ dependencies = [
[[package]]
name = "filter-parser"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"insta",
"nom",
@ -1836,7 +1830,7 @@ dependencies = [
[[package]]
name = "flatten-serde-json"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"criterion",
"serde_json",
@ -1919,7 +1913,7 @@ checksum = "87750cf4b7a4c0625b1529e4c543c2182106e4dedc60a2a6455e00d212c489ac"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -1954,7 +1948,7 @@ dependencies = [
[[package]]
name = "fuzzers"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"arbitrary",
"clap",
@ -2123,9 +2117,9 @@ checksum = "36d244a08113319b5ebcabad2b8b7925732d15eec46d7e7ac3c11734f3b7a6ad"
[[package]]
name = "getrandom"
version = "0.2.14"
version = "0.2.12"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "94b22e06ecb0110981051723910cbf0b5f5e09a2062dd7663334ee79a9d1286c"
checksum = "190092ea657667030ac6a35e305e62fc4dd69fd98ac98631e5d3a2b1575a12b5"
dependencies = [
"cfg-if",
"js-sys",
@ -2262,11 +2256,12 @@ checksum = "95505c38b4572b2d910cecb0281560f54b440a19336cbbcb27bf6ce6adc6f5a8"
[[package]]
name = "heed"
version = "0.20.1"
version = "0.20.0-alpha.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "6f7acb9683d7c7068aa46d47557bfa4e35a277964b350d9504a87b03610163fd"
checksum = "9648a50991c86df7d00c56c268c27754fcf4c80be2ba57fc4a00dc928c6fe934"
dependencies = [
"bitflags 2.5.0",
"bytemuck",
"byteorder",
"heed-traits",
"heed-types",
@ -2280,15 +2275,15 @@ dependencies = [
[[package]]
name = "heed-traits"
version = "0.20.0"
version = "0.20.0-alpha.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "eb3130048d404c57ce5a1ac61a903696e8fcde7e8c2991e9fcfc1f27c3ef74ff"
checksum = "5ab0b7d9cde969ad36dde692e487dc89d97f7168bf6a7bd3b894ad4bf7278298"
[[package]]
name = "heed-types"
version = "0.20.0"
version = "0.20.0-alpha.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3cb0d6ba3700c9a57e83c013693e3eddb68a6d9b6781cacafc62a0d992e8ddb3"
checksum = "f0cb3567a7363f28b597bf6e9897b9466397951dd0e52df2c8196dd8a71af44a"
dependencies = [
"bincode",
"byteorder",
@ -2418,7 +2413,7 @@ dependencies = [
"futures-util",
"http 0.2.11",
"hyper",
"rustls 0.21.12",
"rustls 0.21.10",
"tokio",
"tokio-rustls",
]
@ -2447,7 +2442,7 @@ checksum = "206ca75c9c03ba3d4ace2460e57b189f39f43de612c2f85836e65c929701bb2d"
[[package]]
name = "index-scheduler"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"anyhow",
"big_s",
@ -2464,6 +2459,7 @@ dependencies = [
"meilisearch-auth",
"meilisearch-types",
"page_size 0.5.0",
"puffin",
"rayon",
"roaring",
"serde",
@ -2642,7 +2638,7 @@ dependencies = [
[[package]]
name = "json-depth-checker"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"criterion",
"serde_json",
@ -3161,7 +3157,7 @@ checksum = "fc2fb41a9bb4257a3803154bdf7e2df7d45197d1941c9b1a90ad815231630721"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -3187,13 +3183,14 @@ checksum = "f9d642685b028806386b2b6e75685faadd3eb65a85fff7df711ce18446a422da"
[[package]]
name = "lmdb-master-sys"
version = "0.2.0"
version = "0.1.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "dc9048db3a58c0732d7236abc4909058f9d2708cfb6d7d047eb895fddec6419a"
checksum = "629c123f5321b48fa4f8f4d3b868165b748d9ba79c7103fb58e3a94f736bcedd"
dependencies = [
"cc",
"doxygen-rs",
"libc",
"pkg-config",
]
[[package]]
@ -3216,9 +3213,9 @@ checksum = "e34f76eb3611940e0e7d53a9aaa4e6a3151f69541a282fd0dad5571420c53ff1"
[[package]]
name = "lock_api"
version = "0.4.11"
version = "0.4.10"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3c168f8615b12bc01f9c17e2eb0cc07dcae1940121185446edc3744920e8ef45"
checksum = "c1cc9717a20b1bb222f333e6a92fd32f7d8a18ddc5a3191a11af45dcbf4dcd16"
dependencies = [
"autocfg",
"scopeguard",
@ -3230,6 +3227,12 @@ version = "0.4.21"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "90ed8c1e510134f979dbc4f070f87d4313098b704861a105fe34231c70a3901c"
[[package]]
name = "lz4_flex"
version = "0.10.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "8b8c72594ac26bfd34f2d99dfced2edfaddfe8a476e3ff2ca0eb293d925c4f83"
[[package]]
name = "macro_rules_attribute"
version = "0.2.0"
@ -3255,7 +3258,7 @@ dependencies = [
"once_cell",
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -3272,7 +3275,7 @@ checksum = "490cc448043f947bae3cbee9c203358d62dbee0db12107a74be5c30ccfd09771"
[[package]]
name = "meili-snap"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"insta",
"md5",
@ -3281,7 +3284,7 @@ dependencies = [
[[package]]
name = "meilisearch"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"actix-cors",
"actix-http",
@ -3334,11 +3337,12 @@ dependencies = [
"pin-project-lite",
"platform-dirs",
"prometheus",
"puffin",
"rand",
"rayon",
"regex",
"reqwest",
"rustls 0.21.12",
"rustls 0.21.10",
"rustls-pemfile",
"segment",
"serde",
@ -3373,7 +3377,7 @@ dependencies = [
[[package]]
name = "meilisearch-auth"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"base64 0.21.7",
"enum-iterator",
@ -3392,7 +3396,7 @@ dependencies = [
[[package]]
name = "meilisearch-types"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"actix-web",
"anyhow",
@ -3422,7 +3426,7 @@ dependencies = [
[[package]]
name = "meilitool"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"anyhow",
"clap",
@ -3461,7 +3465,7 @@ dependencies = [
[[package]]
name = "milli"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"arroy",
"big_s",
@ -3501,6 +3505,7 @@ dependencies = [
"obkv",
"once_cell",
"ordered-float",
"puffin",
"rand",
"rand_pcg",
"rayon",
@ -3593,7 +3598,7 @@ checksum = "371717c0a5543d6a800cac822eac735aa7d2d2fbb41002e9856a4089532dbdce"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -3901,7 +3906,7 @@ checksum = "e3148f5046208a5d56bcfc03053e3ca6334e51da8dfb19b6cdc8b306fae3283e"
[[package]]
name = "permissive-json-pointer"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"big_s",
"serde_json",
@ -3937,7 +3942,7 @@ dependencies = [
"pest_meta",
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -3991,7 +3996,7 @@ dependencies = [
"phf_shared",
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -4020,7 +4025,7 @@ checksum = "266c042b60c9c76b8d53061e52b2e0d1116abc57cefc8c5cd671619a56ac3690"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -4128,9 +4133,9 @@ dependencies = [
[[package]]
name = "proc-macro2"
version = "1.0.81"
version = "1.0.79"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3d1597b0c024618f09a9c3b8655b7e430397a36d23fdafec26d6965e9eec3eba"
checksum = "e835ff2298f5721608eb1a980ecaee1aef2c132bf95ecc026a11b7bf3c01c02e"
dependencies = [
"unicode-ident",
]
@ -4171,6 +4176,23 @@ version = "2.28.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "106dd99e98437432fed6519dedecfade6a06a73bb7b2a1e019fdd2bee5778d94"
[[package]]
name = "puffin"
version = "0.16.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "76425abd4e1a0ad4bd6995dd974b52f414fca9974171df8e3708b3e660d05a21"
dependencies = [
"anyhow",
"bincode",
"byteorder",
"cfg-if",
"instant",
"lz4_flex",
"once_cell",
"parking_lot",
"serde",
]
[[package]]
name = "pulp"
version = "0.18.9"
@ -4185,9 +4207,9 @@ dependencies = [
[[package]]
name = "quote"
version = "1.0.36"
version = "1.0.35"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0fa76aaf39101c457836aec0ce2316dbdc3ab723cdda1c6bd4e6ad4208acaca7"
checksum = "291ec9ab5efd934aaf503a6466c5d5251535d108ee747472c3977cc5acc868ef"
dependencies = [
"proc-macro2",
]
@ -4369,7 +4391,7 @@ dependencies = [
"once_cell",
"percent-encoding",
"pin-project-lite",
"rustls 0.21.12",
"rustls 0.21.10",
"rustls-pemfile",
"serde",
"serde_json",
@ -4483,9 +4505,9 @@ dependencies = [
[[package]]
name = "rustls"
version = "0.21.12"
version = "0.21.10"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3f56a14d1f48b391359b22f731fd4bd7e43c97f3c50eee276f3aa09c94784d3e"
checksum = "f9d5a6813c0759e4609cd494e8e725babae6a2ca7b62a5536a13daaec6fcb7ba"
dependencies = [
"log",
"ring",
@ -4495,9 +4517,9 @@ dependencies = [
[[package]]
name = "rustls"
version = "0.22.4"
version = "0.22.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "bf4ef73721ac7bcd79b2b315da7779d8fc09718c6b3d2d1b2d94850eb8c18432"
checksum = "e87c9956bd9807afa1f77e0f7594af32566e830e088a5576d27c5b6f30f49d41"
dependencies = [
"log",
"ring",
@ -4518,9 +4540,9 @@ dependencies = [
[[package]]
name = "rustls-pki-types"
version = "1.4.1"
version = "1.3.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ecd36cc4259e3e4514335c4a138c6b43171a8d61d8f5c9348f9fc7529416f247"
checksum = "5ede67b28608b4c60685c7d54122d4400d90f62b40caee7700e700380a390fa8"
[[package]]
name = "rustls-webpki"
@ -4621,9 +4643,9 @@ checksum = "a3f0bf26fd526d2a95683cd0f87bf103b8539e2ca1ef48ce002d67aad59aa0b4"
[[package]]
name = "serde"
version = "1.0.198"
version = "1.0.197"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9846a40c979031340571da2545a4e5b7c4163bdae79b301d5f86d03979451fcc"
checksum = "3fb1c873e1b9b056a4dc4c0c198b24c3ffa059243875552b2bd0933b1aee4ce2"
dependencies = [
"serde_derive",
]
@ -4639,20 +4661,20 @@ dependencies = [
[[package]]
name = "serde_derive"
version = "1.0.198"
version = "1.0.197"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e88edab869b01783ba905e7d0153f9fc1a6505a96e4ad3018011eedb838566d9"
checksum = "7eb0b34b42edc17f6b7cac84a52a1c5f0e1bb2227e997ca9011ea3dd34e8610b"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
name = "serde_json"
version = "1.0.116"
version = "1.0.115"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3e17db7126d17feb94eb3fad46bf1a96b034e8aacbc2e775fe81505f8b0b2813"
checksum = "12dc5c46daa8e9fdf4f5e71b6cf9a53f2487da0e86e55808e2d35539666497dd"
dependencies = [
"indexmap",
"itoa",
@ -4919,7 +4941,7 @@ dependencies = [
"proc-macro2",
"quote",
"rustversion",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -4941,9 +4963,9 @@ dependencies = [
[[package]]
name = "syn"
version = "2.0.60"
version = "2.0.58"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "909518bc7b1c9b779f1bbf07f2929d35af9f0f37e47c6e9ef7f9dddc1e1821f3"
checksum = "44cfb93f38070beee36b3fef7d4f5a16f27751d94b187b666a5cc5e9b0d30687"
dependencies = [
"proc-macro2",
"quote",
@ -4967,7 +4989,7 @@ checksum = "c8af7666ab7b6390ab78131fb5b0fce11d6b7a6951602017c35fa82800708971"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -5078,7 +5100,7 @@ checksum = "c61f3ba182994efc43764a46c018c347bc492c79f024e705f46567b418f6d4f7"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -5221,7 +5243,7 @@ checksum = "5b8a1e28f2deaa14e508979454cb3a223b10b938b45af148bc0986de36f1923b"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -5230,7 +5252,7 @@ version = "0.24.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "c28327cf380ac148141087fbfb9de9d7bd4e84ab5d2c28fbc911d753de8a7081"
dependencies = [
"rustls 0.21.12",
"rustls 0.21.10",
"tokio",
]
@ -5332,7 +5354,7 @@ checksum = "34704c8d6ebcbc939824180af020566b01a7c01f80641264eba0999f6c2b6be7"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -5447,9 +5469,9 @@ dependencies = [
[[package]]
name = "unicode-bidi"
version = "0.3.15"
version = "0.3.13"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "08f95100a766bf4f8f28f90d77e0a5461bbdb219042e7679bebe79004fed8d75"
checksum = "92888ba5573ff080736b3648696b70cafad7d250551175acbaa4e0385b3e1460"
[[package]]
name = "unicode-blocks"
@ -5507,15 +5529,15 @@ checksum = "8ecb6da28b8a351d773b68d5825ac39017e680750f980f3a1a85cd8dd28a47c1"
[[package]]
name = "ureq"
version = "2.9.7"
version = "2.9.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d11a831e3c0b56e438a28308e7c810799e3c118417f342d30ecec080105395cd"
checksum = "11f214ce18d8b2cbe84ed3aa6486ed3f5b285cf8d8fbdbce9f3f767a724adc35"
dependencies = [
"base64 0.22.1",
"base64 0.21.7",
"flate2",
"log",
"once_cell",
"rustls 0.22.4",
"rustls 0.22.2",
"rustls-pki-types",
"rustls-webpki 0.102.2",
"serde",
@ -5681,7 +5703,7 @@ dependencies = [
"once_cell",
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
"wasm-bindgen-shared",
]
@ -5715,7 +5737,7 @@ checksum = "e94f17b526d0a461a191c78ea52bbce64071ed5c04c9ffe424dcb38f74171bb7"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
"wasm-bindgen-backend",
"wasm-bindgen-shared",
]
@ -5812,7 +5834,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e48a53791691ab099e5e2ad123536d0fff50652600abaf43bbf952894110d0be"
dependencies = [
"windows-core",
"windows-targets 0.52.4",
"windows-targets 0.52.0",
]
[[package]]
@ -5821,7 +5843,7 @@ version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "33ab640c8d7e35bf8ba19b884ba838ceb4fba93a4e8c65a9059d08afcfc683d9"
dependencies = [
"windows-targets 0.52.4",
"windows-targets 0.52.0",
]
[[package]]
@ -5848,7 +5870,7 @@ version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "282be5f36a8ce781fad8c8ae18fa3f9beff57ec1b52cb3de0789201425d9a33d"
dependencies = [
"windows-targets 0.52.4",
"windows-targets 0.52.0",
]
[[package]]
@ -5883,17 +5905,17 @@ dependencies = [
[[package]]
name = "windows-targets"
version = "0.52.4"
version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7dd37b7e5ab9018759f893a1952c9420d060016fc19a472b4bb20d1bdd694d1b"
checksum = "8a18201040b24831fbb9e4eb208f8892e1f50a37feb53cc7ff887feb8f50e7cd"
dependencies = [
"windows_aarch64_gnullvm 0.52.4",
"windows_aarch64_msvc 0.52.4",
"windows_i686_gnu 0.52.4",
"windows_i686_msvc 0.52.4",
"windows_x86_64_gnu 0.52.4",
"windows_x86_64_gnullvm 0.52.4",
"windows_x86_64_msvc 0.52.4",
"windows_aarch64_gnullvm 0.52.0",
"windows_aarch64_msvc 0.52.0",
"windows_i686_gnu 0.52.0",
"windows_i686_msvc 0.52.0",
"windows_x86_64_gnu 0.52.0",
"windows_x86_64_gnullvm 0.52.0",
"windows_x86_64_msvc 0.52.0",
]
[[package]]
@ -5910,9 +5932,9 @@ checksum = "91ae572e1b79dba883e0d315474df7305d12f569b400fcf90581b06062f7e1bc"
[[package]]
name = "windows_aarch64_gnullvm"
version = "0.52.4"
version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "bcf46cf4c365c6f2d1cc93ce535f2c8b244591df96ceee75d8e83deb70a9cac9"
checksum = "cb7764e35d4db8a7921e09562a0304bf2f93e0a51bfccee0bd0bb0b666b015ea"
[[package]]
name = "windows_aarch64_msvc"
@ -5928,9 +5950,9 @@ checksum = "b2ef27e0d7bdfcfc7b868b317c1d32c641a6fe4629c171b8928c7b08d98d7cf3"
[[package]]
name = "windows_aarch64_msvc"
version = "0.52.4"
version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "da9f259dd3bcf6990b55bffd094c4f7235817ba4ceebde8e6d11cd0c5633b675"
checksum = "bbaa0368d4f1d2aaefc55b6fcfee13f41544ddf36801e793edbbfd7d7df075ef"
[[package]]
name = "windows_i686_gnu"
@ -5946,9 +5968,9 @@ checksum = "622a1962a7db830d6fd0a69683c80a18fda201879f0f447f065a3b7467daa241"
[[package]]
name = "windows_i686_gnu"
version = "0.52.4"
version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b474d8268f99e0995f25b9f095bc7434632601028cf86590aea5c8a5cb7801d3"
checksum = "a28637cb1fa3560a16915793afb20081aba2c92ee8af57b4d5f28e4b3e7df313"
[[package]]
name = "windows_i686_msvc"
@ -5964,9 +5986,9 @@ checksum = "4542c6e364ce21bf45d69fdd2a8e455fa38d316158cfd43b3ac1c5b1b19f8e00"
[[package]]
name = "windows_i686_msvc"
version = "0.52.4"
version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1515e9a29e5bed743cb4415a9ecf5dfca648ce85ee42e15873c3cd8610ff8e02"
checksum = "ffe5e8e31046ce6230cc7215707b816e339ff4d4d67c65dffa206fd0f7aa7b9a"
[[package]]
name = "windows_x86_64_gnu"
@ -5982,9 +6004,9 @@ checksum = "ca2b8a661f7628cbd23440e50b05d705db3686f894fc9580820623656af974b1"
[[package]]
name = "windows_x86_64_gnu"
version = "0.52.4"
version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "5eee091590e89cc02ad514ffe3ead9eb6b660aedca2183455434b93546371a03"
checksum = "3d6fa32db2bc4a2f5abeacf2b69f7992cd09dca97498da74a151a3132c26befd"
[[package]]
name = "windows_x86_64_gnullvm"
@ -6000,9 +6022,9 @@ checksum = "7896dbc1f41e08872e9d5e8f8baa8fdd2677f29468c4e156210174edc7f7b953"
[[package]]
name = "windows_x86_64_gnullvm"
version = "0.52.4"
version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "77ca79f2451b49fa9e2af39f0747fe999fcda4f5e241b2898624dca97a1f2177"
checksum = "1a657e1e9d3f514745a572a6846d3c7aa7dbe1658c056ed9c3344c4109a6949e"
[[package]]
name = "windows_x86_64_msvc"
@ -6018,9 +6040,9 @@ checksum = "1a515f5799fe4961cb532f983ce2b23082366b898e52ffbce459c86f67c8378a"
[[package]]
name = "windows_x86_64_msvc"
version = "0.52.4"
version = "0.52.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "32b752e52a2da0ddfbdbcc6fceadfeede4c939ed16d13e648833a61dfb611ed8"
checksum = "dff9641d1cd4be8d1a070daf9e3773c5f67e78b4d9d42263020c057706765c04"
[[package]]
name = "winnow"
@ -6052,7 +6074,7 @@ dependencies = [
[[package]]
name = "xtask"
version = "1.9.0"
version = "1.8.0"
dependencies = [
"anyhow",
"build-info",
@ -6118,7 +6140,7 @@ checksum = "9e6936f0cce458098a201c245a11bef556c6a0181129c7034d10d76d1ec3a2b8"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
"synstructure",
]
@ -6139,7 +6161,7 @@ checksum = "9ce1b18ccd8e73a9321186f97e46f9f04b778851177567b1975109d26a08d2a6"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
]
[[package]]
@ -6159,7 +6181,7 @@ checksum = "e6a647510471d372f2e6c2e6b7219e44d8c574d24fdc11c610a61455782f18c3"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.60",
"syn 2.0.58",
"synstructure",
]

View File

@ -22,7 +22,7 @@ members = [
]
[workspace.package]
version = "1.9.0"
version = "1.8.0"
authors = [
"Quentin de Quelen <quentin@dequelen.me>",
"Clément Renault <clement@meilisearch.com>",

View File

@ -25,7 +25,7 @@
<p align="center">⚡ A lightning-fast search engine that fits effortlessly into your apps, websites, and workflow 🔍</p>
[Meilisearch](https://www.meilisearch.com) helps you shape a delightful search experience in a snap, offering features that work out of the box to speed up your workflow.
Meilisearch helps you shape a delightful search experience in a snap, offering features that work out-of-the-box to speed up your workflow.
<p align="center" name="demo">
<a href="https://where2watch.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demo-gif#gh-light-mode-only" target="_blank">
@ -39,8 +39,8 @@
🔥 [**Try it!**](https://where2watch.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demo-link) 🔥
## ✨ Features
- **Hybrid search:** Combine the best of both [semantic](https://www.meilisearch.com/docs/learn/experimental/vector_search) & full-text search to get the most relevant results
- **Search-as-you-type:** find & display results in less than 50 milliseconds to provide an intuitive experience
- **Search-as-you-type:** find search results in less than 50 milliseconds
- **[Typo tolerance](https://www.meilisearch.com/docs/learn/configuration/typo_tolerance?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** get relevant matches even when queries contain typos and misspellings
- **[Filtering](https://www.meilisearch.com/docs/learn/fine_tuning_results/filtering?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features) and [faceted search](https://www.meilisearch.com/docs/learn/fine_tuning_results/faceted_search?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** enhance your users' search experience with custom filters and build a faceted search interface in a few lines of code
- **[Sorting](https://www.meilisearch.com/docs/learn/fine_tuning_results/sorting?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** sort results based on price, date, or pretty much anything else your users need
@ -55,15 +55,15 @@
## đź“– Documentation
You can consult Meilisearch's documentation at [meilisearch.com/docs](https://www.meilisearch.com/docs/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=docs).
You can consult Meilisearch's documentation at [https://www.meilisearch.com/docs](https://www.meilisearch.com/docs/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=docs).
## 🚀 Getting started
For basic instructions on how to set up Meilisearch, add documents to an index, and search for documents, take a look at our [Quick Start](https://www.meilisearch.com/docs/learn/getting_started/quick_start?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=get-started) guide.
## 🌍 Supercharge your Meilisearch experience
## ⚡ Supercharge your Meilisearch experience
Say goodbye to server deployment and manual updates with [Meilisearch Cloud](https://www.meilisearch.com/cloud?utm_campaign=oss&utm_source=github&utm_medium=meilisearch). Additional features include analytics & monitoring in many regions around the world. No credit card is required.
Say goodbye to server deployment and manual updates with [Meilisearch Cloud](https://www.meilisearch.com/cloud?utm_campaign=oss&utm_source=github&utm_medium=meilisearch). No credit card required.
## đź§° SDKs & integration tools
@ -85,13 +85,13 @@ Finally, for more in-depth information, refer to our articles explaining fundame
Meilisearch collects **anonymized** data from users to help us improve our product. You can [deactivate this](https://www.meilisearch.com/docs/learn/what_is_meilisearch/telemetry?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=telemetry#how-to-disable-data-collection) whenever you want.
To request deletion of collected data, please write to us at [privacy@meilisearch.com](mailto:privacy@meilisearch.com). Remember to include your `Instance UID` in the message, as this helps us quickly find and delete your data.
To request deletion of collected data, please write to us at [privacy@meilisearch.com](mailto:privacy@meilisearch.com). Don't forget to include your `Instance UID` in the message, as this helps us quickly find and delete your data.
If you want to know more about the kind of data we collect and what we use it for, check the [telemetry section](https://www.meilisearch.com/docs/learn/what_is_meilisearch/telemetry?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=telemetry#how-to-disable-data-collection) of our documentation.
## đź“« Get in touch!
Meilisearch is a search engine created by [Meili]([https://www.welcometothejungle.com/en/companies/meilisearch](https://www.meilisearch.com/careers)), a software development company headquartered in France and with team members all over the world. Want to know more about us? [Check out our blog!](https://blog.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=contact)
Meilisearch is a search engine created by [Meili](https://www.welcometothejungle.com/en/companies/meilisearch), a software development company based in France and with team members all over the world. Want to know more about us? [Check out our blog!](https://blog.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=contact)
đź—ž [Subscribe to our newsletter](https://meilisearch.us2.list-manage.com/subscribe?u=27870f7b71c908a8b359599fb&id=79582d828e) if you don't want to miss any updates! We promise we won't clutter your mailbox: we only send one edition every two months.

View File

@ -197,140 +197,6 @@ pub(crate) mod test {
use super::*;
use crate::reader::v6::RuntimeTogglableFeatures;
#[test]
fn import_dump_v6_with_vectors() {
// dump containing two indexes
//
// "vector", configured with an embedder
// contains:
// - one document with an overriden vector,
// - one document with a natural vector
// - one document with a _vectors map containing one additional embedder name and a natural vector
// - one document with a _vectors map containing one additional embedder name and an overriden vector
//
// "novector", no embedder
// contains:
// - a document without vector
// - a document with a random _vectors field
let dump = File::open("tests/assets/v6-with-vectors.dump").unwrap();
let mut dump = DumpReader::open(dump).unwrap();
// top level infos
insta::assert_display_snapshot!(dump.date().unwrap(), @"2024-05-16 15:51:34.151044 +00:00:00");
insta::assert_debug_snapshot!(dump.instance_uid().unwrap(), @"None");
// tasks
let tasks = dump.tasks().unwrap().collect::<Result<Vec<_>>>().unwrap();
let (tasks, update_files): (Vec<_>, Vec<_>) = tasks.into_iter().unzip();
meili_snap::snapshot_hash!(meili_snap::json_string!(tasks), @"278f63325ef06ca04d01df98d8207b94");
assert_eq!(update_files.len(), 10);
assert!(update_files[0].is_none()); // the dump creation
assert!(update_files[1].is_none());
assert!(update_files[2].is_none());
assert!(update_files[3].is_none());
assert!(update_files[4].is_none());
assert!(update_files[5].is_none());
assert!(update_files[6].is_none());
assert!(update_files[7].is_none());
assert!(update_files[8].is_none());
assert!(update_files[9].is_none());
// indexes
let mut indexes = dump.indexes().unwrap().collect::<Result<Vec<_>>>().unwrap();
// the index are not ordered in any way by default
indexes.sort_by_key(|index| index.metadata().uid.to_string());
let mut vector_index = indexes.pop().unwrap();
let mut novector_index = indexes.pop().unwrap();
assert!(indexes.is_empty());
// vector
insta::assert_json_snapshot!(vector_index.metadata(), @r###"
{
"uid": "vector",
"primaryKey": "id",
"createdAt": "2024-05-16T15:33:17.240962Z",
"updatedAt": "2024-05-16T15:40:55.723052Z"
}
"###);
{
let documents: Result<Vec<_>> = vector_index.documents().unwrap().collect();
let mut documents = documents.unwrap();
assert_eq!(documents.len(), 4);
documents.sort_by_key(|doc| doc.get("id").unwrap().to_string());
{
let document = documents.pop().unwrap();
insta::assert_json_snapshot!(document);
}
{
let document = documents.pop().unwrap();
insta::assert_json_snapshot!(document);
}
{
let document = documents.pop().unwrap();
insta::assert_json_snapshot!(document);
}
{
let document = documents.pop().unwrap();
insta::assert_json_snapshot!(document);
}
}
// novector
insta::assert_json_snapshot!(novector_index.metadata(), @r###"
{
"uid": "novector",
"primaryKey": "id",
"createdAt": "2024-05-16T15:33:03.568055Z",
"updatedAt": "2024-05-16T15:33:07.530217Z"
}
"###);
insta::assert_json_snapshot!(novector_index.settings().unwrap().embedders, @"null");
{
let documents: Result<Vec<_>> = novector_index.documents().unwrap().collect();
let mut documents = documents.unwrap();
assert_eq!(documents.len(), 2);
documents.sort_by_key(|doc| doc.get("id").unwrap().to_string());
{
let document = documents.pop().unwrap();
insta::assert_json_snapshot!(document, @r###"
{
"id": "e1",
"other": "random1",
"_vectors": "toto"
}
"###);
}
{
let document = documents.pop().unwrap();
insta::assert_json_snapshot!(document, @r###"
{
"id": "e0",
"other": "random0"
}
"###);
}
}
assert_eq!(
dump.features().unwrap().unwrap(),
RuntimeTogglableFeatures { vector_store: true, ..Default::default() }
);
}
#[test]
fn import_dump_v6_experimental() {
let dump = File::open("tests/assets/v6-with-experimental.dump").unwrap();

View File

@ -1,783 +0,0 @@
---
source: dump/src/reader/mod.rs
expression: document
---
{
"id": "e3",
"desc": "overriden vector + map",
"_vectors": {
"default": [
0.2,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
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source: dump/src/reader/mod.rs
expression: document
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}
}

View File

@ -568,7 +568,7 @@ pub mod tests {
insta::assert_display_snapshot!(p(r"title = 'foo\\\\'"), @r#"{title} = {foo\\}"#);
insta::assert_display_snapshot!(p(r"title = 'foo\\\\\\'"), @r#"{title} = {foo\\\}"#);
insta::assert_display_snapshot!(p(r"title = 'foo\\\\\\\\'"), @r#"{title} = {foo\\\\}"#);
// but it also works with other sequences
// but it also works with other sequencies
insta::assert_display_snapshot!(p(r#"title = 'foo\x20\n\t\"\'"'"#), @"{title} = {foo \n\t\"\'\"}");
}

View File

@ -22,6 +22,7 @@ flate2 = "1.0.28"
meilisearch-auth = { path = "../meilisearch-auth" }
meilisearch-types = { path = "../meilisearch-types" }
page_size = "0.5.0"
puffin = { version = "0.16.0", features = ["serialization"] }
rayon = "1.8.1"
roaring = { version = "0.10.2", features = ["serde"] }
serde = { version = "1.0.195", features = ["derive"] }
@ -36,7 +37,7 @@ time = { version = "0.3.31", features = [
"macros",
] }
tracing = "0.1.40"
ureq = "2.9.7"
ureq = "2.9.1"
uuid = { version = "1.6.1", features = ["serde", "v4"] }
[dev-dependencies]

View File

@ -13,7 +13,7 @@ We can combine the two tasks in a single batch:
1. import documents X and Y
Processing this batch is functionally equivalent to processing the two
tasks individually, but should be much faster since we are only performing
tasks individally, but should be much faster since we are only performing
one indexing operation.
*/
@ -31,9 +31,6 @@ use meilisearch_types::milli::heed::CompactionOption;
use meilisearch_types::milli::update::{
IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig, Settings as MilliSettings,
};
use meilisearch_types::milli::vector::parsed_vectors::{
ExplicitVectors, VectorOrArrayOfVectors, RESERVED_VECTORS_FIELD_NAME,
};
use meilisearch_types::milli::{self, Filter};
use meilisearch_types::settings::{apply_settings_to_builder, Settings, Unchecked};
use meilisearch_types::tasks::{Details, IndexSwap, Kind, KindWithContent, Status, Task};
@ -529,6 +526,8 @@ impl IndexScheduler {
#[cfg(test)]
self.maybe_fail(crate::tests::FailureLocation::InsideCreateBatch)?;
puffin::profile_function!();
let enqueued = &self.get_status(rtxn, Status::Enqueued)?;
let to_cancel = self.get_kind(rtxn, Kind::TaskCancelation)? & enqueued;
@ -637,6 +636,8 @@ impl IndexScheduler {
self.breakpoint(crate::Breakpoint::InsideProcessBatch);
}
puffin::profile_function!(batch.to_string());
match batch {
Batch::TaskCancelation { mut task, previous_started_at, previous_processing_tasks } => {
// 1. Retrieve the tasks that matched the query at enqueue-time.
@ -784,12 +785,10 @@ impl IndexScheduler {
let dst = temp_snapshot_dir.path().join("auth");
fs::create_dir_all(&dst)?;
// TODO We can't use the open_auth_store_env function here but we should
let auth = unsafe {
milli::heed::EnvOpenOptions::new()
.map_size(1024 * 1024 * 1024) // 1 GiB
.max_dbs(2)
.open(&self.auth_path)
}?;
let auth = milli::heed::EnvOpenOptions::new()
.map_size(1024 * 1024 * 1024) // 1 GiB
.max_dbs(2)
.open(&self.auth_path)?;
auth.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)?;
// 5. Copy and tarball the flat snapshot
@ -915,55 +914,8 @@ impl IndexScheduler {
if self.must_stop_processing.get() {
return Err(Error::AbortedTask);
}
let (id, doc) = ret?;
let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, doc)?;
'inject_vectors: {
let embeddings = index.embeddings(&rtxn, id)?;
if embeddings.is_empty() {
break 'inject_vectors;
}
let vectors = document
.entry(RESERVED_VECTORS_FIELD_NAME.to_owned())
.or_insert(serde_json::Value::Object(Default::default()));
let serde_json::Value::Object(vectors) = vectors else {
return Err(milli::Error::UserError(
milli::UserError::InvalidVectorsMapType {
document_id: {
if let Ok(Some(Ok(index))) = index
.external_id_of(&rtxn, std::iter::once(id))
.map(|it| it.into_iter().next())
{
index
} else {
format!("internal docid={id}")
}
},
value: vectors.clone(),
},
)
.into());
};
for (embedder_name, embeddings) in embeddings {
// don't change the entry if it already exists, because it was user-provided
vectors.entry(embedder_name).or_insert_with(|| {
let embeddings = ExplicitVectors {
embeddings: VectorOrArrayOfVectors::from_array_of_vectors(
embeddings,
),
user_provided: false,
};
serde_json::to_value(embeddings).unwrap()
});
}
}
let (_id, doc) = ret?;
let document = milli::obkv_to_json(&all_fields, &fields_ids_map, doc)?;
index_dumper.push_document(&document)?;
}
@ -1222,6 +1174,8 @@ impl IndexScheduler {
index: &'i Index,
operation: IndexOperation,
) -> Result<Vec<Task>> {
puffin::profile_function!();
match operation {
IndexOperation::DocumentClear { mut tasks, .. } => {
let count = milli::update::ClearDocuments::new(index_wtxn, index).execute()?;

View File

@ -68,6 +68,19 @@ impl RoFeatures {
.into())
}
}
pub fn check_puffin(&self) -> Result<()> {
if self.runtime.export_puffin_reports {
Ok(())
} else {
Err(FeatureNotEnabledError {
disabled_action: "Outputting Puffin reports to disk",
feature: "export puffin reports",
issue_link: "https://github.com/meilisearch/product/discussions/693",
}
.into())
}
}
}
impl FeatureData {

View File

@ -32,6 +32,7 @@ pub fn snapshot_index_scheduler(scheduler: &IndexScheduler) -> String {
features: _,
max_number_of_tasks: _,
max_number_of_batched_tasks: _,
puffin_frame: _,
wake_up: _,
dumps_path: _,
snapshots_path: _,

View File

@ -33,6 +33,7 @@ pub type Result<T> = std::result::Result<T, Error>;
pub type TaskId = u32;
use std::collections::{BTreeMap, HashMap};
use std::fs::File;
use std::io::{self, BufReader, Read};
use std::ops::{Bound, RangeBounds};
use std::path::{Path, PathBuf};
@ -58,6 +59,7 @@ use meilisearch_types::milli::vector::{Embedder, EmbedderOptions, EmbeddingConfi
use meilisearch_types::milli::{self, CboRoaringBitmapCodec, Index, RoaringBitmapCodec, BEU32};
use meilisearch_types::task_view::TaskView;
use meilisearch_types::tasks::{Kind, KindWithContent, Status, Task};
use puffin::FrameView;
use rayon::current_num_threads;
use rayon::prelude::{IntoParallelIterator, ParallelIterator};
use roaring::RoaringBitmap;
@ -342,6 +344,9 @@ pub struct IndexScheduler {
/// The Authorization header to send to the webhook URL.
pub(crate) webhook_authorization_header: Option<String>,
/// A frame to output the indexation profiling files to disk.
pub(crate) puffin_frame: Arc<puffin::GlobalFrameView>,
/// The path used to create the dumps.
pub(crate) dumps_path: PathBuf,
@ -396,6 +401,7 @@ impl IndexScheduler {
cleanup_enabled: self.cleanup_enabled,
max_number_of_tasks: self.max_number_of_tasks,
max_number_of_batched_tasks: self.max_number_of_batched_tasks,
puffin_frame: self.puffin_frame.clone(),
snapshots_path: self.snapshots_path.clone(),
dumps_path: self.dumps_path.clone(),
auth_path: self.auth_path.clone(),
@ -447,12 +453,10 @@ impl IndexScheduler {
)
};
let env = unsafe {
heed::EnvOpenOptions::new()
.max_dbs(11)
.map_size(budget.task_db_size)
.open(options.tasks_path)
}?;
let env = heed::EnvOpenOptions::new()
.max_dbs(11)
.map_size(budget.task_db_size)
.open(options.tasks_path)?;
let features = features::FeatureData::new(&env, options.instance_features)?;
@ -494,6 +498,7 @@ impl IndexScheduler {
env,
// we want to start the loop right away in case meilisearch was ctrl+Ced while processing things
wake_up: Arc::new(SignalEvent::auto(true)),
puffin_frame: Arc::new(puffin::GlobalFrameView::default()),
autobatching_enabled: options.autobatching_enabled,
cleanup_enabled: options.cleanup_enabled,
max_number_of_tasks: options.max_number_of_tasks,
@ -580,9 +585,9 @@ impl IndexScheduler {
}
fn is_good_heed(tasks_path: &Path, map_size: usize) -> bool {
if let Ok(env) = unsafe {
if let Ok(env) =
heed::EnvOpenOptions::new().map_size(clamp_to_page_size(map_size)).open(tasks_path)
} {
{
env.prepare_for_closing().wait();
true
} else {
@ -614,6 +619,10 @@ impl IndexScheduler {
run.wake_up.wait();
loop {
let puffin_enabled = run.features().check_puffin().is_ok();
puffin::set_scopes_on(puffin_enabled);
puffin::GlobalProfiler::lock().new_frame();
match run.tick() {
Ok(TickOutcome::TickAgain(_)) => (),
Ok(TickOutcome::WaitForSignal) => run.wake_up.wait(),
@ -625,6 +634,31 @@ impl IndexScheduler {
}
}
}
// Let's write the previous frame to disk but only if
// the user wanted to profile with puffin.
if puffin_enabled {
let mut frame_view = run.puffin_frame.lock();
if !frame_view.is_empty() {
let now = OffsetDateTime::now_utc();
let mut file = match File::create(format!("{}.puffin", now)) {
Ok(file) => file,
Err(e) => {
tracing::error!("{e}");
continue;
}
};
if let Err(e) = frame_view.save_to_writer(&mut file) {
tracing::error!("{e}");
}
if let Err(e) = file.sync_all() {
tracing::error!("{e}");
}
// We erase this frame view as it is no more useful. We want to
// measure the new frames now that we exported the previous ones.
*frame_view = FrameView::default();
}
}
}
})
.unwrap();
@ -1738,7 +1772,6 @@ mod tests {
use big_s::S;
use crossbeam::channel::RecvTimeoutError;
use file_store::File;
use insta::assert_json_snapshot;
use meili_snap::{json_string, snapshot};
use meilisearch_auth::AuthFilter;
use meilisearch_types::document_formats::DocumentFormatError;
@ -1816,7 +1849,7 @@ mod tests {
// To be 100% consistent between all test we're going to start the scheduler right now
// and ensure it's in the expected starting state.
let breakpoint = match receiver.recv_timeout(std::time::Duration::from_secs(10)) {
let breakpoint = match receiver.recv_timeout(std::time::Duration::from_secs(1)) {
Ok(b) => b,
Err(RecvTimeoutError::Timeout) => {
panic!("The scheduler seems to be waiting for a new task while your test is waiting for a breakpoint.")
@ -1927,7 +1960,7 @@ mod tests {
fn advance(&mut self) -> Breakpoint {
let (breakpoint_1, b) = match self
.test_breakpoint_rcv
.recv_timeout(std::time::Duration::from_secs(50))
.recv_timeout(std::time::Duration::from_secs(5))
{
Ok(b) => b,
Err(RecvTimeoutError::Timeout) => {
@ -1948,7 +1981,7 @@ mod tests {
let (breakpoint_2, b) = match self
.test_breakpoint_rcv
.recv_timeout(std::time::Duration::from_secs(50))
.recv_timeout(std::time::Duration::from_secs(5))
{
Ok(b) => b,
Err(RecvTimeoutError::Timeout) => {
@ -4947,233 +4980,4 @@ mod tests {
----------------------------------------------------------------------
"###);
}
#[test]
fn import_vectors() {
use meilisearch_types::settings::{Settings, Unchecked};
use milli::update::Setting;
let (index_scheduler, mut handle) = IndexScheduler::test(true, vec![]);
let mut new_settings: Box<Settings<Unchecked>> = Box::default();
let mut embedders = BTreeMap::default();
let embedding_settings = milli::vector::settings::EmbeddingSettings {
source: Setting::Set(milli::vector::settings::EmbedderSource::Rest),
api_key: Setting::Set(S("My super secret")),
url: Setting::Set(S("http://localhost:7777")),
dimensions: Setting::Set(384),
..Default::default()
};
embedders.insert(S("A_fakerest"), Setting::Set(embedding_settings));
let embedding_settings = milli::vector::settings::EmbeddingSettings {
source: Setting::Set(milli::vector::settings::EmbedderSource::HuggingFace),
model: Setting::Set(S("sentence-transformers/all-MiniLM-L6-v2")),
revision: Setting::Set(S("e4ce9877abf3edfe10b0d82785e83bdcb973e22e")),
document_template: Setting::Set(S("{{doc.doggo}} the {{doc.breed}} best doggo")),
..Default::default()
};
embedders.insert(S("B_small_hf"), Setting::Set(embedding_settings));
new_settings.embedders = Setting::Set(embedders);
index_scheduler
.register(
KindWithContent::SettingsUpdate {
index_uid: S("doggos"),
new_settings,
is_deletion: false,
allow_index_creation: true,
},
None,
false,
)
.unwrap();
index_scheduler.assert_internally_consistent();
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "after_registering_settings_task_vectors");
{
let rtxn = index_scheduler.read_txn().unwrap();
let task = index_scheduler.get_task(&rtxn, 0).unwrap().unwrap();
let task = meilisearch_types::task_view::TaskView::from_task(&task);
insta::assert_json_snapshot!(task.details);
}
handle.advance_n_successful_batches(1);
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "settings_update_processed_vectors");
{
let rtxn = index_scheduler.read_txn().unwrap();
let task = index_scheduler.get_task(&rtxn, 0).unwrap().unwrap();
let task = meilisearch_types::task_view::TaskView::from_task(&task);
insta::assert_json_snapshot!(task.details);
}
let (fakerest_name, simple_hf_name, beagle_embed, lab_embed, patou_embed) = {
let index = index_scheduler.index("doggos").unwrap();
let rtxn = index.read_txn().unwrap();
let configs = index.embedding_configs(&rtxn).unwrap();
// for consistency with the below
#[allow(clippy::get_first)]
let (name, fakerest_config) = configs.get(0).unwrap();
insta::assert_json_snapshot!(name, @r###""A_fakerest""###);
insta::assert_json_snapshot!(fakerest_config.embedder_options);
let fakerest_name = name.clone();
let (name, simple_hf_config) = configs.get(1).unwrap();
insta::assert_json_snapshot!(name, @r###""B_small_hf""###);
insta::assert_json_snapshot!(simple_hf_config.embedder_options);
let simple_hf_name = name.clone();
let configs = index_scheduler.embedders(configs).unwrap();
let (hf_embedder, _) = configs.get(&simple_hf_name).unwrap();
let beagle_embed = hf_embedder.embed_one(S("Intel the beagle best doggo")).unwrap();
let lab_embed = hf_embedder.embed_one(S("Max the lab best doggo")).unwrap();
let patou_embed = hf_embedder.embed_one(S("kefir the patou best doggo")).unwrap();
(fakerest_name, simple_hf_name, beagle_embed, lab_embed, patou_embed)
};
// add one doc, specifying vectors
let doc = serde_json::json!(
{
"id": 0,
"doggo": "Intel",
"breed": "beagle",
"_vectors": {
&fakerest_name: {
// this will never trigger regeneration, which is good because we can't actually generate with
// this embedder
"userProvided": true,
"embeddings": beagle_embed,
},
&simple_hf_name: {
// this will be regenerated on updates
"userProvided": false,
"embeddings": lab_embed,
},
"noise": [0.1, 0.2, 0.3]
}
}
);
let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(0u128).unwrap();
let documents_count = read_json(doc.to_string().as_bytes(), &mut file).unwrap();
assert_eq!(documents_count, 1);
file.persist().unwrap();
index_scheduler
.register(
KindWithContent::DocumentAdditionOrUpdate {
index_uid: S("doggos"),
primary_key: Some(S("id")),
method: UpdateDocuments,
content_file: uuid,
documents_count,
allow_index_creation: true,
},
None,
false,
)
.unwrap();
index_scheduler.assert_internally_consistent();
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "after adding Intel");
handle.advance_one_successful_batch();
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "adding Intel succeeds");
// check embeddings
{
let index = index_scheduler.index("doggos").unwrap();
let rtxn = index.read_txn().unwrap();
let embeddings = index.embeddings(&rtxn, 0).unwrap();
assert_json_snapshot!(embeddings[&simple_hf_name][0] == lab_embed, @"true");
assert_json_snapshot!(embeddings[&fakerest_name][0] == beagle_embed, @"true");
let doc = index.documents(&rtxn, std::iter::once(0)).unwrap()[0].1;
let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
let doc = obkv_to_json(
&[
fields_ids_map.id("doggo").unwrap(),
fields_ids_map.id("breed").unwrap(),
fields_ids_map.id("_vectors").unwrap(),
],
&fields_ids_map,
doc,
)
.unwrap();
assert_json_snapshot!(doc, {"._vectors.A_fakerest.embeddings" => "[vector]"});
}
// update the doc, specifying vectors
let doc = serde_json::json!(
{
"id": 0,
"doggo": "kefir",
"breed": "patou",
}
);
let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(1u128).unwrap();
let documents_count = read_json(doc.to_string().as_bytes(), &mut file).unwrap();
assert_eq!(documents_count, 1);
file.persist().unwrap();
index_scheduler
.register(
KindWithContent::DocumentAdditionOrUpdate {
index_uid: S("doggos"),
primary_key: None,
method: UpdateDocuments,
content_file: uuid,
documents_count,
allow_index_creation: true,
},
None,
false,
)
.unwrap();
index_scheduler.assert_internally_consistent();
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "Intel to kefir");
handle.advance_one_successful_batch();
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "Intel to kefir succeeds");
{
// check embeddings
{
let index = index_scheduler.index("doggos").unwrap();
let rtxn = index.read_txn().unwrap();
let embeddings = index.embeddings(&rtxn, 0).unwrap();
// automatically changed to patou
assert_json_snapshot!(embeddings[&simple_hf_name][0] == patou_embed, @"true");
// remained beagle because set to userProvided
assert_json_snapshot!(embeddings[&fakerest_name][0] == beagle_embed, @"true");
let doc = index.documents(&rtxn, std::iter::once(0)).unwrap()[0].1;
let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
let doc = obkv_to_json(
&[
fields_ids_map.id("doggo").unwrap(),
fields_ids_map.id("breed").unwrap(),
fields_ids_map.id("_vectors").unwrap(),
],
&fields_ids_map,
doc,
)
.unwrap();
assert_json_snapshot!(doc, {"._vectors.A_fakerest.embeddings" => "[vector]"});
}
}
}
}

View File

@ -1,19 +0,0 @@
---
source: index-scheduler/src/lib.rs
expression: doc
---
{
"doggo": "kefir",
"breed": "patou",
"_vectors": {
"A_fakerest": {
"embeddings": "[vector]",
"userProvided": true
},
"noise": [
0.1,
0.2,
0.3
]
}
}

View File

@ -1,20 +0,0 @@
---
source: index-scheduler/src/lib.rs
expression: task.details
---
{
"embedders": {
"A_fakerest": {
"source": "rest",
"apiKey": "MyXXXX...",
"dimensions": 384,
"url": "http://localhost:7777"
},
"B_small_hf": {
"source": "huggingFace",
"model": "sentence-transformers/all-MiniLM-L6-v2",
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
"documentTemplate": "{{doc.doggo}} the {{doc.breed}} best doggo"
}
}
}

View File

@ -1,23 +0,0 @@
---
source: index-scheduler/src/lib.rs
expression: fakerest_config.embedder_options
---
{
"Rest": {
"api_key": "My super secret",
"distribution": null,
"dimensions": 384,
"url": "http://localhost:7777",
"query": null,
"input_field": [
"input"
],
"path_to_embeddings": [
"data"
],
"embedding_object": [
"embedding"
],
"input_type": "text"
}
}

View File

@ -1,11 +0,0 @@
---
source: index-scheduler/src/lib.rs
expression: simple_hf_config.embedder_options
---
{
"HuggingFace": {
"model": "sentence-transformers/all-MiniLM-L6-v2",
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
"distribution": null
}
}

View File

@ -1,19 +0,0 @@
---
source: index-scheduler/src/lib.rs
expression: doc
---
{
"doggo": "Intel",
"breed": "beagle",
"_vectors": {
"A_fakerest": {
"embeddings": "[vector]",
"userProvided": true
},
"noise": [
0.1,
0.2,
0.3
]
}
}

View File

@ -1,20 +0,0 @@
---
source: index-scheduler/src/lib.rs
expression: task.details
---
{
"embedders": {
"A_fakerest": {
"source": "rest",
"apiKey": "MyXXXX...",
"dimensions": 384,
"url": "http://localhost:7777"
},
"B_small_hf": {
"source": "huggingFace",
"model": "sentence-transformers/all-MiniLM-L6-v2",
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
"documentTemplate": "{{doc.doggo}} the {{doc.breed}} best doggo"
}
}
}

View File

@ -1,49 +0,0 @@
---
source: index-scheduler/src/lib.rs
---
### Autobatching Enabled = true
### Processing Tasks:
[]
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: 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: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:
enqueued []
succeeded [0,1,2,]
----------------------------------------------------------------------
### Kind:
"documentAdditionOrUpdate" [1,2,]
"settingsUpdate" [0,]
----------------------------------------------------------------------
### Index Tasks:
doggos [0,1,2,]
----------------------------------------------------------------------
### Index Mapper:
doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
----------------------------------------------------------------------
### Canceled By:
----------------------------------------------------------------------
### Enqueued At:
[timestamp] [0,]
[timestamp] [1,]
[timestamp] [2,]
----------------------------------------------------------------------
### Started At:
[timestamp] [0,]
[timestamp] [1,]
[timestamp] [2,]
----------------------------------------------------------------------
### Finished At:
[timestamp] [0,]
[timestamp] [1,]
[timestamp] [2,]
----------------------------------------------------------------------
### File Store:
----------------------------------------------------------------------

View File

@ -1,48 +0,0 @@
---
source: index-scheduler/src/lib.rs
---
### Autobatching Enabled = true
### Processing Tasks:
[]
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: 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: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:
enqueued [2,]
succeeded [0,1,]
----------------------------------------------------------------------
### Kind:
"documentAdditionOrUpdate" [1,2,]
"settingsUpdate" [0,]
----------------------------------------------------------------------
### Index Tasks:
doggos [0,1,2,]
----------------------------------------------------------------------
### Index Mapper:
doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
----------------------------------------------------------------------
### Canceled By:
----------------------------------------------------------------------
### Enqueued At:
[timestamp] [0,]
[timestamp] [1,]
[timestamp] [2,]
----------------------------------------------------------------------
### Started At:
[timestamp] [0,]
[timestamp] [1,]
----------------------------------------------------------------------
### Finished At:
[timestamp] [0,]
[timestamp] [1,]
----------------------------------------------------------------------
### File Store:
00000000-0000-0000-0000-000000000001
----------------------------------------------------------------------

View File

@ -1,45 +0,0 @@
---
source: index-scheduler/src/lib.rs
---
### Autobatching Enabled = true
### Processing Tasks:
[]
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: 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: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:
enqueued []
succeeded [0,1,]
----------------------------------------------------------------------
### Kind:
"documentAdditionOrUpdate" [1,]
"settingsUpdate" [0,]
----------------------------------------------------------------------
### Index Tasks:
doggos [0,1,]
----------------------------------------------------------------------
### Index Mapper:
doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
----------------------------------------------------------------------
### Canceled By:
----------------------------------------------------------------------
### Enqueued At:
[timestamp] [0,]
[timestamp] [1,]
----------------------------------------------------------------------
### Started At:
[timestamp] [0,]
[timestamp] [1,]
----------------------------------------------------------------------
### Finished At:
[timestamp] [0,]
[timestamp] [1,]
----------------------------------------------------------------------
### File Store:
----------------------------------------------------------------------

View File

@ -1,44 +0,0 @@
---
source: index-scheduler/src/lib.rs
---
### Autobatching Enabled = true
### Processing Tasks:
[]
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: 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: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
1 {uid: 1, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:
enqueued [1,]
succeeded [0,]
----------------------------------------------------------------------
### Kind:
"documentAdditionOrUpdate" [1,]
"settingsUpdate" [0,]
----------------------------------------------------------------------
### Index Tasks:
doggos [0,1,]
----------------------------------------------------------------------
### Index Mapper:
doggos: { number_of_documents: 0, field_distribution: {} }
----------------------------------------------------------------------
### Canceled By:
----------------------------------------------------------------------
### Enqueued At:
[timestamp] [0,]
[timestamp] [1,]
----------------------------------------------------------------------
### Started At:
[timestamp] [0,]
----------------------------------------------------------------------
### Finished At:
[timestamp] [0,]
----------------------------------------------------------------------
### File Store:
00000000-0000-0000-0000-000000000000
----------------------------------------------------------------------

View File

@ -1,36 +0,0 @@
---
source: index-scheduler/src/lib.rs
---
### Autobatching Enabled = true
### Processing Tasks:
[]
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: enqueued, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: 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: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:
enqueued [0,]
----------------------------------------------------------------------
### Kind:
"settingsUpdate" [0,]
----------------------------------------------------------------------
### Index Tasks:
doggos [0,]
----------------------------------------------------------------------
### Index Mapper:
----------------------------------------------------------------------
### Canceled By:
----------------------------------------------------------------------
### Enqueued At:
[timestamp] [0,]
----------------------------------------------------------------------
### Started At:
----------------------------------------------------------------------
### Finished At:
----------------------------------------------------------------------
### File Store:
----------------------------------------------------------------------

View File

@ -1,40 +0,0 @@
---
source: index-scheduler/src/lib.rs
---
### Autobatching Enabled = true
### Processing Tasks:
[]
----------------------------------------------------------------------
### All Tasks:
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: 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: NotSet, 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: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
----------------------------------------------------------------------
### Status:
enqueued []
succeeded [0,]
----------------------------------------------------------------------
### Kind:
"settingsUpdate" [0,]
----------------------------------------------------------------------
### Index Tasks:
doggos [0,]
----------------------------------------------------------------------
### Index Mapper:
doggos: { number_of_documents: 0, field_distribution: {} }
----------------------------------------------------------------------
### Canceled By:
----------------------------------------------------------------------
### Enqueued At:
[timestamp] [0,]
----------------------------------------------------------------------
### Started At:
[timestamp] [0,]
----------------------------------------------------------------------
### Finished At:
[timestamp] [0,]
----------------------------------------------------------------------
### File Store:
----------------------------------------------------------------------

View File

@ -272,9 +272,9 @@ pub fn swap_index_uid_in_task(task: &mut Task, swap: (&str, &str)) {
}
for index_uid in index_uids {
if index_uid == swap.0 {
swap.1.clone_into(index_uid);
*index_uid = swap.1.to_owned();
} else if index_uid == swap.1 {
swap.0.clone_into(index_uid);
*index_uid = swap.0.to_owned();
}
}
}

View File

@ -49,7 +49,7 @@ pub fn open_auth_store_env(path: &Path) -> milli::heed::Result<milli::heed::Env>
let mut options = EnvOpenOptions::new();
options.map_size(AUTH_STORE_SIZE); // 1GB
options.max_dbs(2);
unsafe { options.open(path) }
options.open(path)
}
impl HeedAuthStore {

View File

@ -26,7 +26,7 @@ pub type DeserrQueryParamError<C = BadRequest> = DeserrError<DeserrQueryParam, C
/// A request deserialization error.
///
/// The first generic parameter is a marker type describing the format of the request: either json (e.g. [`DeserrJson`] or [`DeserrQueryParam`]).
/// The first generic paramater is a marker type describing the format of the request: either json (e.g. [`DeserrJson`] or [`DeserrQueryParam`]).
/// The second generic parameter is the default error code for the deserialization error, in case it is not given.
pub struct DeserrError<Format, C: Default + ErrorCode> {
pub msg: String,
@ -189,4 +189,3 @@ merge_with_error_impl_take_error_message!(ParseTaskKindError);
merge_with_error_impl_take_error_message!(ParseTaskStatusError);
merge_with_error_impl_take_error_message!(IndexUidFormatError);
merge_with_error_impl_take_error_message!(InvalidSearchSemanticRatio);
merge_with_error_impl_take_error_message!(InvalidSimilarId);

View File

@ -239,23 +239,18 @@ InvalidIndexUid , InvalidRequest , BAD_REQUEST ;
InvalidSearchAttributesToSearchOn , InvalidRequest , BAD_REQUEST ;
InvalidSearchAttributesToCrop , InvalidRequest , BAD_REQUEST ;
InvalidSearchAttributesToHighlight , InvalidRequest , BAD_REQUEST ;
InvalidSimilarAttributesToRetrieve , InvalidRequest , BAD_REQUEST ;
InvalidSearchAttributesToRetrieve , InvalidRequest , BAD_REQUEST ;
InvalidSearchCropLength , InvalidRequest , BAD_REQUEST ;
InvalidSearchCropMarker , InvalidRequest , BAD_REQUEST ;
InvalidSearchFacets , InvalidRequest , BAD_REQUEST ;
InvalidSearchSemanticRatio , InvalidRequest , BAD_REQUEST ;
InvalidFacetSearchFacetName , InvalidRequest , BAD_REQUEST ;
InvalidSimilarId , InvalidRequest , BAD_REQUEST ;
InvalidSearchFilter , InvalidRequest , BAD_REQUEST ;
InvalidSimilarFilter , InvalidRequest , BAD_REQUEST ;
InvalidSearchHighlightPostTag , InvalidRequest , BAD_REQUEST ;
InvalidSearchHighlightPreTag , InvalidRequest , BAD_REQUEST ;
InvalidSearchHitsPerPage , InvalidRequest , BAD_REQUEST ;
InvalidSimilarLimit , InvalidRequest , BAD_REQUEST ;
InvalidSearchLimit , InvalidRequest , BAD_REQUEST ;
InvalidSearchMatchingStrategy , InvalidRequest , BAD_REQUEST ;
InvalidSimilarOffset , InvalidRequest , BAD_REQUEST ;
InvalidSearchOffset , InvalidRequest , BAD_REQUEST ;
InvalidSearchPage , InvalidRequest , BAD_REQUEST ;
InvalidSearchQ , InvalidRequest , BAD_REQUEST ;
@ -264,9 +259,7 @@ InvalidFacetSearchName , InvalidRequest , BAD_REQUEST ;
InvalidSearchVector , InvalidRequest , BAD_REQUEST ;
InvalidSearchShowMatchesPosition , InvalidRequest , BAD_REQUEST ;
InvalidSearchShowRankingScore , InvalidRequest , BAD_REQUEST ;
InvalidSimilarShowRankingScore , InvalidRequest , BAD_REQUEST ;
InvalidSearchShowRankingScoreDetails , InvalidRequest , BAD_REQUEST ;
InvalidSimilarShowRankingScoreDetails , InvalidRequest , BAD_REQUEST ;
InvalidSearchSort , InvalidRequest , BAD_REQUEST ;
InvalidSettingsDisplayedAttributes , InvalidRequest , BAD_REQUEST ;
InvalidSettingsDistinctAttribute , InvalidRequest , BAD_REQUEST ;
@ -329,8 +322,7 @@ UnretrievableErrorCode , InvalidRequest , BAD_REQUEST ;
UnsupportedMediaType , InvalidRequest , UNSUPPORTED_MEDIA_TYPE ;
// Experimental features
VectorEmbeddingError , InvalidRequest , BAD_REQUEST ;
NotFoundSimilarId , InvalidRequest , BAD_REQUEST
VectorEmbeddingError , InvalidRequest , BAD_REQUEST
}
impl ErrorCode for JoinError {
@ -392,6 +384,7 @@ impl ErrorCode for milli::Error {
UserError::InvalidGeoField { .. } => Code::InvalidDocumentGeoField,
UserError::InvalidVectorDimensions { .. } => Code::InvalidVectorDimensions,
UserError::InvalidVectorsMapType { .. } => Code::InvalidVectorsType,
UserError::InvalidVectorsType { .. } => Code::InvalidVectorsType,
UserError::TooManyVectors(_, _) => Code::TooManyVectors,
UserError::SortError(_) => Code::InvalidSearchSort,
UserError::InvalidMinTypoWordLenSetting(_, _) => {
@ -430,6 +423,7 @@ impl ErrorCode for HeedError {
HeedError::Mdb(_)
| HeedError::Encoding(_)
| HeedError::Decoding(_)
| HeedError::InvalidDatabaseTyping
| HeedError::DatabaseClosing
| HeedError::BadOpenOptions { .. } => Code::Internal,
}
@ -494,17 +488,6 @@ impl fmt::Display for deserr_codes::InvalidSearchSemanticRatio {
}
}
impl fmt::Display for deserr_codes::InvalidSimilarId {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(
f,
"the value of `id` is invalid. \
A document identifier can be of type integer or string, \
only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_)."
)
}
}
#[macro_export]
macro_rules! internal_error {
($target:ty : $($other:path), *) => {

View File

@ -6,6 +6,7 @@ pub struct RuntimeTogglableFeatures {
pub vector_store: bool,
pub metrics: bool,
pub logs_route: bool,
pub export_puffin_reports: bool,
}
#[derive(Default, Debug, Clone, Copy)]

View File

@ -67,6 +67,7 @@ permissive-json-pointer = { path = "../permissive-json-pointer" }
pin-project-lite = "0.2.13"
platform-dirs = "0.3.0"
prometheus = { version = "0.13.3", features = ["process"] }
puffin = { version = "0.16.0", features = ["serialization"] }
rand = "0.8.5"
rayon = "1.8.0"
regex = "1.10.2"
@ -74,7 +75,7 @@ reqwest = { version = "0.11.23", features = [
"rustls-tls",
"json",
], default-features = false }
rustls = "0.21.12"
rustls = "0.21.6"
rustls-pemfile = "1.0.2"
segment = { version = "0.2.3", optional = true }
serde = { version = "1.0.195", features = ["derive"] }

View File

@ -25,18 +25,6 @@ impl SearchAggregator {
pub fn succeed(&mut self, _: &dyn Any) {}
}
#[derive(Default)]
pub struct SimilarAggregator;
#[allow(dead_code)]
impl SimilarAggregator {
pub fn from_query(_: &dyn Any, _: &dyn Any) -> Self {
Self
}
pub fn succeed(&mut self, _: &dyn Any) {}
}
#[derive(Default)]
pub struct MultiSearchAggregator;
@ -78,8 +66,6 @@ impl Analytics for MockAnalytics {
fn publish(&self, _event_name: String, _send: Value, _request: Option<&HttpRequest>) {}
fn get_search(&self, _aggregate: super::SearchAggregator) {}
fn post_search(&self, _aggregate: super::SearchAggregator) {}
fn get_similar(&self, _aggregate: super::SimilarAggregator) {}
fn post_similar(&self, _aggregate: super::SimilarAggregator) {}
fn post_multi_search(&self, _aggregate: super::MultiSearchAggregator) {}
fn post_facet_search(&self, _aggregate: super::FacetSearchAggregator) {}
fn add_documents(

View File

@ -22,8 +22,6 @@ pub type SegmentAnalytics = mock_analytics::MockAnalytics;
#[cfg(not(feature = "analytics"))]
pub type SearchAggregator = mock_analytics::SearchAggregator;
#[cfg(not(feature = "analytics"))]
pub type SimilarAggregator = mock_analytics::SimilarAggregator;
#[cfg(not(feature = "analytics"))]
pub type MultiSearchAggregator = mock_analytics::MultiSearchAggregator;
#[cfg(not(feature = "analytics"))]
pub type FacetSearchAggregator = mock_analytics::FacetSearchAggregator;
@ -34,8 +32,6 @@ pub type SegmentAnalytics = segment_analytics::SegmentAnalytics;
#[cfg(feature = "analytics")]
pub type SearchAggregator = segment_analytics::SearchAggregator;
#[cfg(feature = "analytics")]
pub type SimilarAggregator = segment_analytics::SimilarAggregator;
#[cfg(feature = "analytics")]
pub type MultiSearchAggregator = segment_analytics::MultiSearchAggregator;
#[cfg(feature = "analytics")]
pub type FacetSearchAggregator = segment_analytics::FacetSearchAggregator;
@ -90,12 +86,6 @@ pub trait Analytics: Sync + Send {
/// This method should be called to aggregate a post search
fn post_search(&self, aggregate: SearchAggregator);
/// This method should be called to aggregate a get similar request
fn get_similar(&self, aggregate: SimilarAggregator);
/// This method should be called to aggregate a post similar request
fn post_similar(&self, aggregate: SimilarAggregator);
/// This method should be called to aggregate a post array of searches
fn post_multi_search(&self, aggregate: MultiSearchAggregator);

View File

@ -36,9 +36,8 @@ use crate::routes::indexes::facet_search::FacetSearchQuery;
use crate::routes::{create_all_stats, Stats};
use crate::search::{
FacetSearchResult, MatchingStrategy, SearchQuery, SearchQueryWithIndex, SearchResult,
SimilarQuery, SimilarResult, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER,
DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
DEFAULT_SEMANTIC_RATIO,
DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEMANTIC_RATIO,
};
use crate::Opt;
@ -74,8 +73,6 @@ pub enum AnalyticsMsg {
BatchMessage(Track),
AggregateGetSearch(SearchAggregator),
AggregatePostSearch(SearchAggregator),
AggregateGetSimilar(SimilarAggregator),
AggregatePostSimilar(SimilarAggregator),
AggregatePostMultiSearch(MultiSearchAggregator),
AggregatePostFacetSearch(FacetSearchAggregator),
AggregateAddDocuments(DocumentsAggregator),
@ -152,8 +149,6 @@ impl SegmentAnalytics {
update_documents_aggregator: DocumentsAggregator::default(),
get_fetch_documents_aggregator: DocumentsFetchAggregator::default(),
post_fetch_documents_aggregator: DocumentsFetchAggregator::default(),
get_similar_aggregator: SimilarAggregator::default(),
post_similar_aggregator: SimilarAggregator::default(),
});
tokio::spawn(segment.run(index_scheduler.clone(), auth_controller.clone()));
@ -189,14 +184,6 @@ impl super::Analytics for SegmentAnalytics {
let _ = self.sender.try_send(AnalyticsMsg::AggregatePostSearch(aggregate));
}
fn get_similar(&self, aggregate: SimilarAggregator) {
let _ = self.sender.try_send(AnalyticsMsg::AggregateGetSimilar(aggregate));
}
fn post_similar(&self, aggregate: SimilarAggregator) {
let _ = self.sender.try_send(AnalyticsMsg::AggregatePostSimilar(aggregate));
}
fn post_facet_search(&self, aggregate: FacetSearchAggregator) {
let _ = self.sender.try_send(AnalyticsMsg::AggregatePostFacetSearch(aggregate));
}
@ -392,8 +379,6 @@ pub struct Segment {
update_documents_aggregator: DocumentsAggregator,
get_fetch_documents_aggregator: DocumentsFetchAggregator,
post_fetch_documents_aggregator: DocumentsFetchAggregator,
get_similar_aggregator: SimilarAggregator,
post_similar_aggregator: SimilarAggregator,
}
impl Segment {
@ -456,8 +441,6 @@ impl Segment {
Some(AnalyticsMsg::AggregateUpdateDocuments(agreg)) => self.update_documents_aggregator.aggregate(agreg),
Some(AnalyticsMsg::AggregateGetFetchDocuments(agreg)) => self.get_fetch_documents_aggregator.aggregate(agreg),
Some(AnalyticsMsg::AggregatePostFetchDocuments(agreg)) => self.post_fetch_documents_aggregator.aggregate(agreg),
Some(AnalyticsMsg::AggregateGetSimilar(agreg)) => self.get_similar_aggregator.aggregate(agreg),
Some(AnalyticsMsg::AggregatePostSimilar(agreg)) => self.post_similar_aggregator.aggregate(agreg),
None => (),
}
}
@ -511,8 +494,6 @@ impl Segment {
update_documents_aggregator,
get_fetch_documents_aggregator,
post_fetch_documents_aggregator,
get_similar_aggregator,
post_similar_aggregator,
} = self;
if let Some(get_search) =
@ -560,18 +541,6 @@ impl Segment {
{
let _ = self.batcher.push(post_fetch_documents).await;
}
if let Some(get_similar_documents) =
take(get_similar_aggregator).into_event(user, "Similar GET")
{
let _ = self.batcher.push(get_similar_documents).await;
}
if let Some(post_similar_documents) =
take(post_similar_aggregator).into_event(user, "Similar POST")
{
let _ = self.batcher.push(post_similar_documents).await;
}
let _ = self.batcher.flush().await;
}
}
@ -1589,235 +1558,3 @@ impl DocumentsFetchAggregator {
})
}
}
#[derive(Default)]
pub struct SimilarAggregator {
timestamp: Option<OffsetDateTime>,
// context
user_agents: HashSet<String>,
// requests
total_received: usize,
total_succeeded: usize,
time_spent: BinaryHeap<usize>,
// filter
filter_with_geo_radius: bool,
filter_with_geo_bounding_box: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
filter_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
filter_total_number_of_criteria: usize,
used_syntax: HashMap<String, usize>,
// Whether a non-default embedder was specified
embedder: bool,
// pagination
max_limit: usize,
max_offset: usize,
// formatting
max_attributes_to_retrieve: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
}
impl SimilarAggregator {
#[allow(clippy::field_reassign_with_default)]
pub fn from_query(query: &SimilarQuery, request: &HttpRequest) -> Self {
let SimilarQuery {
id: _,
embedder,
offset,
limit,
attributes_to_retrieve: _,
show_ranking_score,
show_ranking_score_details,
filter,
} = query;
let mut ret = Self::default();
ret.timestamp = Some(OffsetDateTime::now_utc());
ret.total_received = 1;
ret.user_agents = extract_user_agents(request).into_iter().collect();
if let Some(ref filter) = filter {
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
ret.filter_total_number_of_criteria = 1;
let syntax = match filter {
Value::String(_) => "string".to_string(),
Value::Array(values) => {
if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
"mixed".to_string()
} else {
"array".to_string()
}
}
_ => "none".to_string(),
};
// convert the string to a HashMap
ret.used_syntax.insert(syntax, 1);
let stringified_filters = filter.to_string();
ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
}
ret.max_limit = *limit;
ret.max_offset = *offset;
ret.show_ranking_score = *show_ranking_score;
ret.show_ranking_score_details = *show_ranking_score_details;
ret.embedder = embedder.is_some();
ret
}
pub fn succeed(&mut self, result: &SimilarResult) {
let SimilarResult { id: _, hits: _, processing_time_ms, hits_info: _ } = result;
self.total_succeeded = self.total_succeeded.saturating_add(1);
self.time_spent.push(*processing_time_ms as usize);
}
/// Aggregate one [SimilarAggregator] into another.
pub fn aggregate(&mut self, mut other: Self) {
let Self {
timestamp,
user_agents,
total_received,
total_succeeded,
ref mut time_spent,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
max_limit,
max_offset,
max_attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
embedder,
} = other;
if self.timestamp.is_none() {
self.timestamp = timestamp;
}
// context
for user_agent in user_agents.into_iter() {
self.user_agents.insert(user_agent);
}
// request
self.total_received = self.total_received.saturating_add(total_received);
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
self.time_spent.append(time_spent);
// filter
self.filter_with_geo_radius |= filter_with_geo_radius;
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
self.filter_sum_of_criteria_terms =
self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
self.filter_total_number_of_criteria =
self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
for (key, value) in used_syntax.into_iter() {
let used_syntax = self.used_syntax.entry(key).or_insert(0);
*used_syntax = used_syntax.saturating_add(value);
}
self.embedder |= embedder;
// pagination
self.max_limit = self.max_limit.max(max_limit);
self.max_offset = self.max_offset.max(max_offset);
// formatting
self.max_attributes_to_retrieve =
self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
// scoring
self.show_ranking_score |= show_ranking_score;
self.show_ranking_score_details |= show_ranking_score_details;
}
pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
let Self {
timestamp,
user_agents,
total_received,
total_succeeded,
time_spent,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
max_limit,
max_offset,
max_attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
embedder,
} = self;
if total_received == 0 {
None
} else {
// we get all the values in a sorted manner
let time_spent = time_spent.into_sorted_vec();
// the index of the 99th percentage of value
let percentile_99th = time_spent.len() * 99 / 100;
// We are only interested by the slowest value of the 99th fastest results
let time_spent = time_spent.get(percentile_99th);
let properties = json!({
"user-agent": user_agents,
"requests": {
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
},
"filter": {
"with_geoRadius": filter_with_geo_radius,
"with_geoBoundingBox": filter_with_geo_bounding_box,
"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"hybrid": {
"embedder": embedder,
},
"pagination": {
"max_limit": max_limit,
"max_offset": max_offset,
},
"formatting": {
"max_attributes_to_retrieve": max_attributes_to_retrieve,
},
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
},
});
Some(Track {
timestamp,
user: user.clone(),
event: event_name.to_string(),
properties,
..Default::default()
})
}
}
}

View File

@ -59,12 +59,10 @@ where
let request_path = req.path();
let is_registered_resource = req.resource_map().has_resource(request_path);
if is_registered_resource {
let request_pattern = req.match_pattern();
let metric_path = request_pattern.as_ref().map_or(request_path, String::as_str);
let request_method = req.method().to_string();
histogram_timer = Some(
crate::metrics::MEILISEARCH_HTTP_RESPONSE_TIME_SECONDS
.with_label_values(&[&request_method, metric_path])
.with_label_values(&[&request_method, request_path])
.start_timer(),
);
}

View File

@ -47,6 +47,8 @@ pub struct RuntimeTogglableFeatures {
pub metrics: Option<bool>,
#[deserr(default)]
pub logs_route: Option<bool>,
#[deserr(default)]
pub export_puffin_reports: Option<bool>,
}
async fn patch_features(
@ -66,13 +68,21 @@ async fn patch_features(
vector_store: new_features.0.vector_store.unwrap_or(old_features.vector_store),
metrics: new_features.0.metrics.unwrap_or(old_features.metrics),
logs_route: new_features.0.logs_route.unwrap_or(old_features.logs_route),
export_puffin_reports: new_features
.0
.export_puffin_reports
.unwrap_or(old_features.export_puffin_reports),
};
// explicitly destructure for analytics rather than using the `Serialize` implementation, because
// the it renames to camelCase, which we don't want for analytics.
// **Do not** ignore fields with `..` or `_` here, because we want to add them in the future.
let meilisearch_types::features::RuntimeTogglableFeatures { vector_store, metrics, logs_route } =
new_features;
let meilisearch_types::features::RuntimeTogglableFeatures {
vector_store,
metrics,
logs_route,
export_puffin_reports,
} = new_features;
analytics.publish(
"Experimental features Updated".to_string(),
@ -80,6 +90,7 @@ async fn patch_features(
"vector_store": vector_store,
"metrics": metrics,
"logs_route": logs_route,
"export_puffin_reports": export_puffin_reports,
}),
Some(&req),
);

View File

@ -69,7 +69,7 @@ pub async fn search(
// Tenant token search_rules.
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
add_search_rules(&mut search_query.filter, search_rules);
add_search_rules(&mut search_query, search_rules);
}
let index = index_scheduler.index(&index_uid)?;

View File

@ -29,7 +29,6 @@ pub mod documents;
pub mod facet_search;
pub mod search;
pub mod settings;
pub mod similar;
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(
@ -46,14 +45,9 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
.route(web::delete().to(SeqHandler(delete_index))),
)
.service(web::resource("/stats").route(web::get().to(SeqHandler(get_index_stats))))
.service(
web::resource("/advanced-stats")
.route(web::get().to(SeqHandler(get_advanced_index_stats))),
)
.service(web::scope("/documents").configure(documents::configure))
.service(web::scope("/search").configure(search::configure))
.service(web::scope("/facet-search").configure(facet_search::configure))
.service(web::scope("/similar").configure(similar::configure))
.service(web::scope("/settings").configure(settings::configure)),
);
}
@ -282,16 +276,3 @@ pub async fn get_index_stats(
debug!(returns = ?stats, "Get index stats");
Ok(HttpResponse::Ok().json(stats))
}
pub async fn get_advanced_index_stats(
index_scheduler: GuardedData<ActionPolicy<{ actions::STATS_GET }>, Data<IndexScheduler>>,
index_uid: web::Path<String>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let index = index_scheduler.index(&index_uid)?;
let rtxn = index.read_txn()?;
let advanced_stats = index.advanced_stats(&rtxn)?;
debug!(returns = ?advanced_stats, "Get advanced index stats");
Ok(HttpResponse::Ok().json(advanced_stats))
}

View File

@ -196,7 +196,7 @@ pub async fn search_with_url_query(
// Tenant token search_rules.
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
add_search_rules(&mut query.filter, search_rules);
add_search_rules(&mut query, search_rules);
}
let mut aggregate = SearchAggregator::from_query(&query, &req);
@ -235,7 +235,7 @@ pub async fn search_with_post(
// Tenant token search_rules.
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
add_search_rules(&mut query.filter, search_rules);
add_search_rules(&mut query, search_rules);
}
let mut aggregate = SearchAggregator::from_query(&query, &req);

View File

@ -1,171 +0,0 @@
use actix_web::web::{self, Data};
use actix_web::{HttpRequest, HttpResponse};
use deserr::actix_web::{AwebJson, AwebQueryParameter};
use index_scheduler::IndexScheduler;
use meilisearch_types::deserr::query_params::Param;
use meilisearch_types::deserr::{DeserrJsonError, DeserrQueryParamError};
use meilisearch_types::error::deserr_codes::{
InvalidEmbedder, InvalidSimilarAttributesToRetrieve, InvalidSimilarFilter, InvalidSimilarId,
InvalidSimilarLimit, InvalidSimilarOffset, InvalidSimilarShowRankingScore,
InvalidSimilarShowRankingScoreDetails,
};
use meilisearch_types::error::{ErrorCode as _, ResponseError};
use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::keys::actions;
use meilisearch_types::serde_cs::vec::CS;
use serde_json::Value;
use tracing::debug;
use super::ActionPolicy;
use crate::analytics::{Analytics, SimilarAggregator};
use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::search::{
add_search_rules, perform_similar, SearchKind, SimilarQuery, SimilarResult,
DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
};
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(
web::resource("")
.route(web::get().to(SeqHandler(similar_get)))
.route(web::post().to(SeqHandler(similar_post))),
);
}
pub async fn similar_get(
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
index_uid: web::Path<String>,
params: AwebQueryParameter<SimilarQueryGet, DeserrQueryParamError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let query = params.0.try_into().map_err(|code: InvalidSimilarId| {
ResponseError::from_msg(code.to_string(), code.error_code())
})?;
let mut aggregate = SimilarAggregator::from_query(&query, &req);
debug!(parameters = ?query, "Similar get");
let similar = similar(index_scheduler, index_uid, query).await;
if let Ok(similar) = &similar {
aggregate.succeed(similar);
}
analytics.get_similar(aggregate);
let similar = similar?;
debug!(returns = ?similar, "Similar get");
Ok(HttpResponse::Ok().json(similar))
}
pub async fn similar_post(
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
index_uid: web::Path<String>,
params: AwebJson<SimilarQuery, DeserrJsonError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let query = params.into_inner();
debug!(parameters = ?query, "Similar post");
let mut aggregate = SimilarAggregator::from_query(&query, &req);
let similar = similar(index_scheduler, index_uid, query).await;
if let Ok(similar) = &similar {
aggregate.succeed(similar);
}
analytics.post_similar(aggregate);
let similar = similar?;
debug!(returns = ?similar, "Similar post");
Ok(HttpResponse::Ok().json(similar))
}
async fn similar(
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
index_uid: IndexUid,
mut query: SimilarQuery,
) -> Result<SimilarResult, ResponseError> {
let features = index_scheduler.features();
features.check_vector("Using the similar API")?;
// Tenant token search_rules.
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
add_search_rules(&mut query.filter, search_rules);
}
let index = index_scheduler.index(&index_uid)?;
let (embedder_name, embedder) =
SearchKind::embedder(&index_scheduler, &index, query.embedder.as_deref(), None)?;
tokio::task::spawn_blocking(move || perform_similar(&index, query, embedder_name, embedder))
.await?
}
#[derive(Debug, deserr::Deserr)]
#[deserr(error = DeserrQueryParamError, rename_all = camelCase, deny_unknown_fields)]
pub struct SimilarQueryGet {
#[deserr(error = DeserrQueryParamError<InvalidSimilarId>)]
id: Param<String>,
#[deserr(default = Param(DEFAULT_SEARCH_OFFSET()), error = DeserrQueryParamError<InvalidSimilarOffset>)]
offset: Param<usize>,
#[deserr(default = Param(DEFAULT_SEARCH_LIMIT()), error = DeserrQueryParamError<InvalidSimilarLimit>)]
limit: Param<usize>,
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarAttributesToRetrieve>)]
attributes_to_retrieve: Option<CS<String>>,
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarFilter>)]
filter: Option<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarShowRankingScore>)]
show_ranking_score: Param<bool>,
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarShowRankingScoreDetails>)]
show_ranking_score_details: Param<bool>,
#[deserr(default, error = DeserrQueryParamError<InvalidEmbedder>)]
pub embedder: Option<String>,
}
impl TryFrom<SimilarQueryGet> for SimilarQuery {
type Error = InvalidSimilarId;
fn try_from(
SimilarQueryGet {
id,
offset,
limit,
attributes_to_retrieve,
filter,
show_ranking_score,
show_ranking_score_details,
embedder,
}: SimilarQueryGet,
) -> Result<Self, Self::Error> {
let filter = match filter {
Some(f) => match serde_json::from_str(&f) {
Ok(v) => Some(v),
_ => Some(Value::String(f)),
},
None => None,
};
Ok(SimilarQuery {
id: id.0.try_into()?,
offset: offset.0,
limit: limit.0,
filter,
embedder,
attributes_to_retrieve: attributes_to_retrieve.map(|o| o.into_iter().collect()),
show_ranking_score: show_ranking_score.0,
show_ranking_score_details: show_ranking_score_details.0,
})
}
}

View File

@ -67,7 +67,7 @@ pub async fn multi_search_with_post(
// Apply search rules from tenant token
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid)
{
add_search_rules(&mut query.filter, search_rules);
add_search_rules(&mut query, search_rules);
}
let index = index_scheduler

View File

@ -11,7 +11,7 @@ use indexmap::IndexMap;
use meilisearch_auth::IndexSearchRules;
use meilisearch_types::deserr::DeserrJsonError;
use meilisearch_types::error::deserr_codes::*;
use meilisearch_types::error::{Code, ResponseError};
use meilisearch_types::error::ResponseError;
use meilisearch_types::heed::RoTxn;
use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy};
@ -231,7 +231,7 @@ impl SearchKind {
Ok(Self::Hybrid { embedder_name, embedder, semantic_ratio })
}
pub(crate) fn embedder(
fn embedder(
index_scheduler: &index_scheduler::IndexScheduler,
index: &Index,
embedder_name: Option<&str>,
@ -417,59 +417,6 @@ impl SearchQueryWithIndex {
}
}
#[derive(Debug, Clone, PartialEq, Deserr)]
#[deserr(error = DeserrJsonError, rename_all = camelCase, deny_unknown_fields)]
pub struct SimilarQuery {
#[deserr(error = DeserrJsonError<InvalidSimilarId>)]
pub id: ExternalDocumentId,
#[deserr(default = DEFAULT_SEARCH_OFFSET(), error = DeserrJsonError<InvalidSimilarOffset>)]
pub offset: usize,
#[deserr(default = DEFAULT_SEARCH_LIMIT(), error = DeserrJsonError<InvalidSimilarLimit>)]
pub limit: usize,
#[deserr(default, error = DeserrJsonError<InvalidSimilarFilter>)]
pub filter: Option<Value>,
#[deserr(default, error = DeserrJsonError<InvalidEmbedder>, default)]
pub embedder: Option<String>,
#[deserr(default, error = DeserrJsonError<InvalidSimilarAttributesToRetrieve>)]
pub attributes_to_retrieve: Option<BTreeSet<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScore>, default)]
pub show_ranking_score: bool,
#[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScoreDetails>, default)]
pub show_ranking_score_details: bool,
}
#[derive(Debug, Clone, PartialEq, Deserr)]
#[deserr(try_from(Value) = TryFrom::try_from -> InvalidSimilarId)]
pub struct ExternalDocumentId(String);
impl AsRef<str> for ExternalDocumentId {
fn as_ref(&self) -> &str {
&self.0
}
}
impl ExternalDocumentId {
pub fn into_inner(self) -> String {
self.0
}
}
impl TryFrom<String> for ExternalDocumentId {
type Error = InvalidSimilarId;
fn try_from(value: String) -> Result<Self, Self::Error> {
serde_json::Value::String(value).try_into()
}
}
impl TryFrom<Value> for ExternalDocumentId {
type Error = InvalidSimilarId;
fn try_from(value: Value) -> Result<Self, Self::Error> {
Ok(Self(milli::documents::validate_document_id_value(value).map_err(|_| InvalidSimilarId)?))
}
}
#[derive(Debug, Copy, Clone, PartialEq, Eq, Deserr)]
#[deserr(rename_all = camelCase)]
pub enum MatchingStrategy {
@ -477,8 +424,6 @@ pub enum MatchingStrategy {
Last,
/// All query words are mandatory
All,
/// Remove query words from the most frequent to the least
Frequency,
}
impl Default for MatchingStrategy {
@ -492,7 +437,6 @@ impl From<MatchingStrategy> for TermsMatchingStrategy {
match other {
MatchingStrategy::Last => Self::Last,
MatchingStrategy::All => Self::All,
MatchingStrategy::Frequency => Self::Frequency,
}
}
}
@ -594,16 +538,6 @@ impl fmt::Debug for SearchResult {
}
}
#[derive(Serialize, Debug, Clone, PartialEq)]
#[serde(rename_all = "camelCase")]
pub struct SimilarResult {
pub hits: Vec<SearchHit>,
pub id: String,
pub processing_time_ms: u128,
#[serde(flatten)]
pub hits_info: HitsInfo,
}
#[derive(Serialize, Debug, Clone, PartialEq)]
#[serde(rename_all = "camelCase")]
pub struct SearchResultWithIndex {
@ -636,8 +570,8 @@ pub struct FacetSearchResult {
}
/// Incorporate search rules in search query
pub fn add_search_rules(filter: &mut Option<Value>, rules: IndexSearchRules) {
*filter = match (filter.take(), rules.filter) {
pub fn add_search_rules(query: &mut SearchQuery, rules: IndexSearchRules) {
query.filter = match (query.filter.take(), rules.filter) {
(None, rules_filter) => rules_filter,
(filter, None) => filter,
(Some(filter), Some(rules_filter)) => {
@ -785,52 +719,131 @@ pub fn perform_search(
SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?,
};
let SearchQuery {
q,
vector: _,
hybrid: _,
// already computed from prepare_search
offset: _,
limit,
page,
hits_per_page,
attributes_to_retrieve,
attributes_to_crop,
crop_length,
attributes_to_highlight,
show_matches_position,
show_ranking_score,
show_ranking_score_details,
filter: _,
sort,
facets,
highlight_pre_tag,
highlight_post_tag,
crop_marker,
matching_strategy: _,
attributes_to_search_on: _,
} = query;
let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
let format = AttributesFormat {
attributes_to_retrieve,
attributes_to_highlight,
attributes_to_crop,
crop_length,
crop_marker,
highlight_pre_tag,
highlight_post_tag,
show_matches_position,
sort,
show_ranking_score,
show_ranking_score_details,
let displayed_ids = index
.displayed_fields_ids(&rtxn)?
.map(|fields| fields.into_iter().collect::<BTreeSet<_>>())
.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
let fids = |attrs: &BTreeSet<String>| {
let mut ids = BTreeSet::new();
for attr in attrs {
if attr == "*" {
ids = displayed_ids.clone();
break;
}
if let Some(id) = fields_ids_map.id(attr) {
ids.insert(id);
}
}
ids
};
let documents =
make_hits(index, &rtxn, format, matching_words, documents_ids, document_scores)?;
// The attributes to retrieve are the ones explicitly marked as to retrieve (all by default),
// but these attributes must be also be present
// - in the fields_ids_map
// - in the displayed attributes
let to_retrieve_ids: BTreeSet<_> = query
.attributes_to_retrieve
.as_ref()
.map(fids)
.unwrap_or_else(|| displayed_ids.clone())
.intersection(&displayed_ids)
.cloned()
.collect();
let attr_to_highlight = query.attributes_to_highlight.unwrap_or_default();
let attr_to_crop = query.attributes_to_crop.unwrap_or_default();
// Attributes in `formatted_options` correspond to the attributes that will be in `_formatted`
// These attributes are:
// - the attributes asked to be highlighted or cropped (with `attributesToCrop` or `attributesToHighlight`)
// - the attributes asked to be retrieved: these attributes will not be highlighted/cropped
// But these attributes must be also present in displayed attributes
let formatted_options = compute_formatted_options(
&attr_to_highlight,
&attr_to_crop,
query.crop_length,
&to_retrieve_ids,
&fields_ids_map,
&displayed_ids,
);
let mut tokenizer_builder = TokenizerBuilder::default();
tokenizer_builder.create_char_map(true);
let script_lang_map = index.script_language(&rtxn)?;
if !script_lang_map.is_empty() {
tokenizer_builder.allow_list(&script_lang_map);
}
let separators = index.allowed_separators(&rtxn)?;
let separators: Option<Vec<_>> =
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
if let Some(ref separators) = separators {
tokenizer_builder.separators(separators);
}
let dictionary = index.dictionary(&rtxn)?;
let dictionary: Option<Vec<_>> =
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
if let Some(ref dictionary) = dictionary {
tokenizer_builder.words_dict(dictionary);
}
let mut formatter_builder = MatcherBuilder::new(matching_words, tokenizer_builder.build());
formatter_builder.crop_marker(query.crop_marker);
formatter_builder.highlight_prefix(query.highlight_pre_tag);
formatter_builder.highlight_suffix(query.highlight_post_tag);
let mut documents = Vec::new();
let documents_iter = index.documents(&rtxn, documents_ids)?;
for ((_id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
// First generate a document with all the displayed fields
let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
// select the attributes to retrieve
let attributes_to_retrieve = to_retrieve_ids
.iter()
.map(|&fid| fields_ids_map.name(fid).expect("Missing field name"));
let mut document =
permissive_json_pointer::select_values(&displayed_document, attributes_to_retrieve);
let (matches_position, formatted) = format_fields(
&displayed_document,
&fields_ids_map,
&formatter_builder,
&formatted_options,
query.show_matches_position,
&displayed_ids,
)?;
if let Some(sort) = query.sort.as_ref() {
insert_geo_distance(sort, &mut document);
}
let ranking_score =
query.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
let ranking_score_details =
query.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
let hit = SearchHit {
document,
formatted,
matches_position,
ranking_score_details,
ranking_score,
};
documents.push(hit);
}
let number_of_hits = min(candidates.len() as usize, max_total_hits);
let hits_info = if is_finite_pagination {
let hits_per_page = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
let hits_per_page = query.hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
// If hit_per_page is 0, then pages can't be computed and so we respond 0.
let total_pages = (number_of_hits + hits_per_page.saturating_sub(1))
.checked_div(hits_per_page)
@ -838,15 +851,15 @@ pub fn perform_search(
HitsInfo::Pagination {
hits_per_page,
page: page.unwrap_or(1),
page: query.page.unwrap_or(1),
total_pages,
total_hits: number_of_hits,
}
} else {
HitsInfo::OffsetLimit { limit, offset, estimated_total_hits: number_of_hits }
HitsInfo::OffsetLimit { limit: query.limit, offset, estimated_total_hits: number_of_hits }
};
let (facet_distribution, facet_stats) = match facets {
let (facet_distribution, facet_stats) = match query.facets {
Some(ref fields) => {
let mut facet_distribution = index.facets_distribution(&rtxn);
@ -883,7 +896,7 @@ pub fn perform_search(
let result = SearchResult {
hits: documents,
hits_info,
query: q.unwrap_or_default(),
query: query.q.unwrap_or_default(),
processing_time_ms: before_search.elapsed().as_millis(),
facet_distribution,
facet_stats,
@ -894,130 +907,6 @@ pub fn perform_search(
Ok(result)
}
struct AttributesFormat {
attributes_to_retrieve: Option<BTreeSet<String>>,
attributes_to_highlight: Option<HashSet<String>>,
attributes_to_crop: Option<Vec<String>>,
crop_length: usize,
crop_marker: String,
highlight_pre_tag: String,
highlight_post_tag: String,
show_matches_position: bool,
sort: Option<Vec<String>>,
show_ranking_score: bool,
show_ranking_score_details: bool,
}
fn make_hits(
index: &Index,
rtxn: &RoTxn<'_>,
format: AttributesFormat,
matching_words: milli::MatchingWords,
documents_ids: Vec<u32>,
document_scores: Vec<Vec<ScoreDetails>>,
) -> Result<Vec<SearchHit>, MeilisearchHttpError> {
let fields_ids_map = index.fields_ids_map(rtxn).unwrap();
let displayed_ids = index
.displayed_fields_ids(rtxn)?
.map(|fields| fields.into_iter().collect::<BTreeSet<_>>())
.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
let fids = |attrs: &BTreeSet<String>| {
let mut ids = BTreeSet::new();
for attr in attrs {
if attr == "*" {
ids.clone_from(&displayed_ids);
break;
}
if let Some(id) = fields_ids_map.id(attr) {
ids.insert(id);
}
}
ids
};
let to_retrieve_ids: BTreeSet<_> = format
.attributes_to_retrieve
.as_ref()
.map(fids)
.unwrap_or_else(|| displayed_ids.clone())
.intersection(&displayed_ids)
.cloned()
.collect();
let attr_to_highlight = format.attributes_to_highlight.unwrap_or_default();
let attr_to_crop = format.attributes_to_crop.unwrap_or_default();
let formatted_options = compute_formatted_options(
&attr_to_highlight,
&attr_to_crop,
format.crop_length,
&to_retrieve_ids,
&fields_ids_map,
&displayed_ids,
);
let mut tokenizer_builder = TokenizerBuilder::default();
tokenizer_builder.create_char_map(true);
let script_lang_map = index.script_language(rtxn)?;
if !script_lang_map.is_empty() {
tokenizer_builder.allow_list(&script_lang_map);
}
let separators = index.allowed_separators(rtxn)?;
let separators: Option<Vec<_>> =
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
if let Some(ref separators) = separators {
tokenizer_builder.separators(separators);
}
let dictionary = index.dictionary(rtxn)?;
let dictionary: Option<Vec<_>> =
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
if let Some(ref dictionary) = dictionary {
tokenizer_builder.words_dict(dictionary);
}
let mut formatter_builder = MatcherBuilder::new(matching_words, tokenizer_builder.build());
formatter_builder.crop_marker(format.crop_marker);
formatter_builder.highlight_prefix(format.highlight_pre_tag);
formatter_builder.highlight_suffix(format.highlight_post_tag);
let mut documents = Vec::new();
let documents_iter = index.documents(rtxn, documents_ids)?;
for ((_id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
// First generate a document with all the displayed fields
let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
// select the attributes to retrieve
let attributes_to_retrieve = to_retrieve_ids
.iter()
.map(|&fid| fields_ids_map.name(fid).expect("Missing field name"));
let mut document =
permissive_json_pointer::select_values(&displayed_document, attributes_to_retrieve);
let (matches_position, formatted) = format_fields(
&displayed_document,
&fields_ids_map,
&formatter_builder,
&formatted_options,
format.show_matches_position,
&displayed_ids,
)?;
if let Some(sort) = format.sort.as_ref() {
insert_geo_distance(sort, &mut document);
}
let ranking_score =
format.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
let ranking_score_details =
format.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
let hit = SearchHit {
document,
formatted,
matches_position,
ranking_score_details,
ranking_score,
};
documents.push(hit);
}
Ok(documents)
}
pub fn perform_facet_search(
index: &Index,
search_query: SearchQuery,
@ -1052,95 +941,6 @@ pub fn perform_facet_search(
})
}
pub fn perform_similar(
index: &Index,
query: SimilarQuery,
embedder_name: String,
embedder: Arc<Embedder>,
) -> Result<SimilarResult, ResponseError> {
let before_search = Instant::now();
let rtxn = index.read_txn()?;
let SimilarQuery {
id,
offset,
limit,
filter: _,
embedder: _,
attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
} = query;
// using let-else rather than `?` so that the borrow checker identifies we're always returning here,
// preventing a use-after-move
let Some(internal_id) = index.external_documents_ids().get(&rtxn, &id)? else {
return Err(ResponseError::from_msg(
MeilisearchHttpError::DocumentNotFound(id.into_inner()).to_string(),
Code::NotFoundSimilarId,
));
};
let mut similar =
milli::Similar::new(internal_id, offset, limit, index, &rtxn, embedder_name, embedder);
if let Some(ref filter) = query.filter {
if let Some(facets) = parse_filter(filter)
// inject InvalidSimilarFilter code
.map_err(|e| ResponseError::from_msg(e.to_string(), Code::InvalidSimilarFilter))?
{
similar.filter(facets);
}
}
let milli::SearchResult {
documents_ids,
matching_words: _,
candidates,
document_scores,
degraded: _,
used_negative_operator: _,
} = similar.execute().map_err(|err| match err {
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
ResponseError::from_msg(err.to_string(), Code::InvalidSimilarFilter)
}
err => err.into(),
})?;
let format = AttributesFormat {
attributes_to_retrieve,
attributes_to_highlight: None,
attributes_to_crop: None,
crop_length: DEFAULT_CROP_LENGTH(),
crop_marker: DEFAULT_CROP_MARKER(),
highlight_pre_tag: DEFAULT_HIGHLIGHT_PRE_TAG(),
highlight_post_tag: DEFAULT_HIGHLIGHT_POST_TAG(),
show_matches_position: false,
sort: None,
show_ranking_score,
show_ranking_score_details,
};
let hits = make_hits(index, &rtxn, format, Default::default(), documents_ids, document_scores)?;
let max_total_hits = index
.pagination_max_total_hits(&rtxn)
.map_err(milli::Error::from)?
.map(|x| x as usize)
.unwrap_or(DEFAULT_PAGINATION_MAX_TOTAL_HITS);
let number_of_hits = min(candidates.len() as usize, max_total_hits);
let hits_info = HitsInfo::OffsetLimit { limit, offset, estimated_total_hits: number_of_hits };
let result = SimilarResult {
hits,
hits_info,
id: id.into_inner(),
processing_time_ms: before_search.elapsed().as_millis(),
};
Ok(result)
}
fn insert_geo_distance(sorts: &[String], document: &mut Document) {
lazy_static::lazy_static! {
static ref GEO_REGEX: Regex =

View File

@ -85,13 +85,8 @@ impl SearchQueue {
},
search_request = receive_new_searches.recv() => {
let search_request = match search_request {
Some(search_request) => search_request,
// This should never happen while actix-web is running, but it's not a reason to crash
// and it can generate a lot of noise in the tests.
None => continue,
};
// this unwrap is safe because we're sure the `SearchQueue` still lives somewhere in actix-web
let search_request = search_request.unwrap();
if searches_running < usize::from(parallelism) && queue.is_empty() {
searches_running += 1;
// if the search requests die it's not a hard error on our side

View File

@ -380,43 +380,6 @@ impl Index<'_> {
self.service.get(url).await
}
/// Performs both GET and POST similar queries
pub async fn similar(
&self,
query: Value,
test: impl Fn(Value, StatusCode) + UnwindSafe + Clone,
) {
let post = self.similar_post(query.clone()).await;
let query = yaup::to_string(&query).unwrap();
let get = self.similar_get(&query).await;
insta::allow_duplicates! {
let (response, code) = post;
let t = test.clone();
if let Err(e) = catch_unwind(move || t(response, code)) {
eprintln!("Error with post search");
resume_unwind(e);
}
let (response, code) = get;
if let Err(e) = catch_unwind(move || test(response, code)) {
eprintln!("Error with get search");
resume_unwind(e);
}
}
}
pub async fn similar_post(&self, query: Value) -> (Value, StatusCode) {
let url = format!("/indexes/{}/similar", urlencode(self.uid.as_ref()));
self.service.post_encoded(url, query, self.encoder).await
}
pub async fn similar_get(&self, query: &str) -> (Value, StatusCode) {
let url = format!("/indexes/{}/similar?{}", urlencode(self.uid.as_ref()), query);
self.service.get(url).await
}
pub async fn facet_search(&self, query: Value) -> (Value, StatusCode) {
let url = format!("/indexes/{}/facet-search", urlencode(self.uid.as_ref()));
self.service.post_encoded(url, query, self.encoder).await

View File

@ -1859,7 +1859,8 @@ async fn import_dump_v6_containing_experimental_features() {
{
"vectorStore": false,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);

View File

@ -20,7 +20,8 @@ async fn experimental_features() {
{
"vectorStore": false,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);
@ -31,7 +32,8 @@ async fn experimental_features() {
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);
@ -42,7 +44,8 @@ async fn experimental_features() {
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);
@ -54,7 +57,8 @@ async fn experimental_features() {
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);
@ -66,7 +70,8 @@ async fn experimental_features() {
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);
}
@ -85,7 +90,8 @@ async fn experimental_feature_metrics() {
{
"vectorStore": false,
"metrics": true,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);
@ -140,7 +146,7 @@ async fn errors() {
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Unknown field `NotAFeature`: expected one of `vectorStore`, `metrics`, `logsRoute`",
"message": "Unknown field `NotAFeature`: expected one of `vectorStore`, `metrics`, `logsRoute`, `exportPuffinReports`",
"code": "bad_request",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#bad_request"

View File

@ -8,7 +8,6 @@ mod index;
mod logs;
mod search;
mod settings;
mod similar;
mod snapshot;
mod stats;
mod swap_indexes;

View File

@ -505,7 +505,7 @@ async fn search_bad_matching_strategy() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Unknown value `doggo` at `.matchingStrategy`: expected one of `last`, `all`, `frequency`",
"message": "Unknown value `doggo` at `.matchingStrategy`: expected one of `last`, `all`",
"code": "invalid_search_matching_strategy",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_matching_strategy"
@ -527,7 +527,7 @@ async fn search_bad_matching_strategy() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Unknown value `doggo` for parameter `matchingStrategy`: expected one of `last`, `all`, `frequency`",
"message": "Unknown value `doggo` for parameter `matchingStrategy`: expected one of `last`, `all`",
"code": "invalid_search_matching_strategy",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_matching_strategy"

View File

@ -117,69 +117,3 @@ async fn geo_bounding_box_with_string_and_number() {
)
.await;
}
#[actix_rt::test]
async fn bug_4640() {
// https://github.com/meilisearch/meilisearch/issues/4640
let server = Server::new().await;
let index = server.index("test");
let documents = DOCUMENTS.clone();
index.add_documents(documents, None).await;
index.update_settings_filterable_attributes(json!(["_geo"])).await;
let (ret, _code) = index.update_settings_sortable_attributes(json!(["_geo"])).await;
index.wait_task(ret.uid()).await;
// Sort the document with the second one first
index
.search(
json!({
"sort": ["_geoPoint(45.4777599, 9.1967508):asc"],
}),
|response, code| {
assert_eq!(code, 200, "{}", response);
snapshot!(json_string!(response, { ".processingTimeMs" => "[time]" }), @r###"
{
"hits": [
{
"id": 2,
"name": "La Bella Italia",
"address": "456 Elm Street, Townsville",
"type": "Italian",
"rating": 9,
"_geo": {
"lat": "45.4777599",
"lng": "9.1967508"
}
},
{
"id": 1,
"name": "Taco Truck",
"address": "444 Salsa Street, Burritoville",
"type": "Mexican",
"rating": 9,
"_geo": {
"lat": 34.0522,
"lng": -118.2437
},
"_geoDistance": 9714063
},
{
"id": 3,
"name": "CrĂŞpe Truck",
"address": "2 Billig Avenue, Rouenville",
"type": "French",
"rating": 10
}
],
"query": "",
"processingTimeMs": "[time]",
"limit": 20,
"offset": 0,
"estimatedTotalHits": 3
}
"###);
},
)
.await;
}

View File

@ -5,10 +5,7 @@ use crate::common::index::Index;
use crate::common::{Server, Value};
use crate::json;
async fn index_with_documents_user_provided<'a>(
server: &'a Server,
documents: &Value,
) -> Index<'a> {
async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
let index = server.index("test");
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
@ -18,7 +15,8 @@ async fn index_with_documents_user_provided<'a>(
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);
@ -36,38 +34,7 @@ async fn index_with_documents_user_provided<'a>(
index
}
async fn index_with_documents_hf<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
let index = server.index("test");
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
}
"###);
let (response, code) = index
.update_settings(json!({ "embedders": {"default": {
"source": "huggingFace",
"model": "sentence-transformers/all-MiniLM-L6-v2",
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
"documentTemplate": "{{doc.title}}, {{doc.desc}}"
}}} ))
.await;
assert_eq!(202, code, "{:?}", response);
index.wait_task(response.uid()).await;
let (response, code) = index.add_documents(documents.clone(), None).await;
assert_eq!(202, code, "{:?}", response);
index.wait_task(response.uid()).await;
index
}
static SIMPLE_SEARCH_DOCUMENTS_VEC: Lazy<Value> = Lazy::new(|| {
static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
json!([
{
"title": "Shazam!",
@ -89,7 +56,7 @@ static SIMPLE_SEARCH_DOCUMENTS_VEC: Lazy<Value> = Lazy::new(|| {
}])
});
static SINGLE_DOCUMENT_VEC: Lazy<Value> = Lazy::new(|| {
static SINGLE_DOCUMENT: Lazy<Value> = Lazy::new(|| {
json!([{
"title": "Shazam!",
"desc": "a Captain Marvel ersatz",
@ -98,29 +65,10 @@ static SINGLE_DOCUMENT_VEC: Lazy<Value> = Lazy::new(|| {
}])
});
static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
json!([
{
"title": "Shazam!",
"desc": "a Captain Marvel ersatz",
"id": "1",
},
{
"title": "Captain Planet",
"desc": "He's not part of the Marvel Cinematic Universe",
"id": "2",
},
{
"title": "Captain Marvel",
"desc": "a Shazam ersatz",
"id": "3",
}])
});
#[actix_rt::test]
async fn simple_search() {
let server = Server::new().await;
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
let (response, code) = index
.search_post(
@ -137,8 +85,8 @@ async fn simple_search() {
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
snapshot!(response["semanticHitCount"], @"2");
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.996969696969697},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.996969696969697},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
snapshot!(response["semanticHitCount"], @"1");
let (response, code) = index
.search_post(
@ -150,59 +98,10 @@ async fn simple_search() {
snapshot!(response["semanticHitCount"], @"3");
}
#[actix_rt::test]
async fn simple_search_hf() {
let server = Server::new().await;
let index = index_with_documents_hf(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
let (response, code) =
index.search_post(json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2}})).await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"}]"###);
snapshot!(response["semanticHitCount"], @"0");
let (response, code) = index
.search_post(
// disable ranking score as the vectors between architectures are not equal
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.55}, "showRankingScore": false}),
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"}]"###);
snapshot!(response["semanticHitCount"], @"1");
let (response, code) = index
.search_post(
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.8}, "showRankingScore": false}),
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"}]"###);
snapshot!(response["semanticHitCount"], @"3");
let (response, code) = index
.search_post(
json!({"q": "Movie World", "hybrid": {"semanticRatio": 0.2}, "showRankingScore": false}),
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"}]"###);
snapshot!(response["semanticHitCount"], @"3");
let (response, code) = index
.search_post(
json!({"q": "Wonder replacement", "hybrid": {"semanticRatio": 0.2}, "showRankingScore": false}),
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"}]"###);
snapshot!(response["semanticHitCount"], @"3");
}
#[actix_rt::test]
async fn distribution_shift() {
let server = Server::new().await;
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
let search = json!({"q": "Captain", "vector": [1.0, 1.0], "showRankingScore": true, "hybrid": {"semanticRatio": 1.0}});
let (response, code) = index.search_post(search.clone()).await;
@ -234,7 +133,7 @@ async fn distribution_shift() {
#[actix_rt::test]
async fn highlighter() {
let server = Server::new().await;
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).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],
@ -285,7 +184,7 @@ async fn highlighter() {
#[actix_rt::test]
async fn invalid_semantic_ratio() {
let server = Server::new().await;
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
let (response, code) = index
.search_post(
@ -357,7 +256,7 @@ async fn invalid_semantic_ratio() {
#[actix_rt::test]
async fn single_document() {
let server = Server::new().await;
let index = index_with_documents_user_provided(&server, &SINGLE_DOCUMENT_VEC).await;
let index = index_with_documents(&server, &SINGLE_DOCUMENT).await;
let (response, code) = index
.search_post(
@ -373,7 +272,7 @@ async fn single_document() {
#[actix_rt::test]
async fn query_combination() {
let server = Server::new().await;
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
// search without query and vector, but with hybrid => still placeholder
let (response, code) = index
@ -432,7 +331,7 @@ async fn query_combination() {
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9848484848484848},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9242424242424242}]"###);
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.996969696969697},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.996969696969697},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.8848484848484849}]"###);
snapshot!(response["semanticHitCount"], @"null");
// query + vector, no hybrid keyword =>
@ -475,6 +374,6 @@ async fn query_combination() {
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9242424242424242}]"###);
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9848484848484848}]"###);
snapshot!(response["semanticHitCount"], @"0");
}

View File

@ -1,128 +0,0 @@
use meili_snap::snapshot;
use once_cell::sync::Lazy;
use crate::common::index::Index;
use crate::common::{Server, Value};
use crate::json;
async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
let index = server.index("test");
index.add_documents(documents.clone(), None).await;
index.wait_task(0).await;
index
}
static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
json!([
{
"title": "Shazam!",
"id": "1",
},
{
"title": "Captain Planet",
"id": "2",
},
{
"title": "Captain Marvel",
"id": "3",
},
{
"title": "a Captain Marvel ersatz",
"id": "4"
},
{
"title": "He's not part of the Marvel Cinematic Universe",
"id": "5"
},
{
"title": "a Shazam ersatz, but better than Captain Planet",
"id": "6"
},
{
"title": "Capitain CAAAAAVEEERNE!!!!",
"id": "7"
}
])
});
#[actix_rt::test]
async fn simple_search() {
let server = Server::new().await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
index
.search(json!({"q": "Captain Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"2"},{"id":"6"},{"id":"7"}]"###);
})
.await;
index
.search(json!({"q": "Captain Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"}]"###);
})
.await;
index
.search(json!({"q": "Captain Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
})
.await;
}
#[actix_rt::test]
async fn search_with_typo() {
let server = Server::new().await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
index
.search(json!({"q": "Capitain Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"7"},{"id":"2"},{"id":"6"}]"###);
})
.await;
index
.search(json!({"q": "Capitain Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"}]"###);
})
.await;
index
.search(json!({"q": "Capitain Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
})
.await;
}
#[actix_rt::test]
async fn search_with_unknown_word() {
let server = Server::new().await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
index
.search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"2"},{"id":"3"},{"id":"4"},{"id":"6"},{"id":"7"}]"###);
})
.await;
index
.search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @"[]");
})
.await;
index
.search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
})
.await;
}

View File

@ -7,7 +7,6 @@ mod facet_search;
mod formatted;
mod geo;
mod hybrid;
mod matching_strategy;
mod multi;
mod pagination;
mod restrict_searchable;
@ -681,26 +680,6 @@ async fn search_facet_distribution() {
},
)
.await;
index.update_settings(json!({"filterableAttributes": ["doggos.name"]})).await;
index.wait_task(5).await;
index
.search(
json!({
"facets": ["doggos.name"]
}),
|response, code| {
assert_eq!(code, 200, "{}", response);
let dist = response["facetDistribution"].as_object().unwrap();
assert_eq!(dist.len(), 1);
assert_eq!(
dist["doggos.name"],
json!({ "bobby": 1, "buddy": 1, "gros bill": 1, "turbo": 1, "fast": 1})
);
},
)
.await;
}
#[actix_rt::test]
@ -916,9 +895,9 @@ async fn test_score_details() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
},
"_rankingScoreDetails": {
@ -942,7 +921,7 @@ async fn test_score_details() {
"order": 3,
"attributeRankingOrderScore": 1.0,
"queryWordDistanceScore": 0.8095238095238095,
"score": 0.8095238095238095
"score": 0.9727891156462584
},
"exactness": {
"order": 4,
@ -1117,9 +1096,9 @@ async fn experimental_feature_vector_store() {
"id": "287947",
"_vectors": {
"manual": [
1.0,
2.0,
3.0
1,
2,
3
]
},
"_rankingScore": 1.0
@ -1129,9 +1108,9 @@ async fn experimental_feature_vector_store() {
"id": "299537",
"_vectors": {
"manual": [
1.0,
2.0,
54.0
1,
2,
54
]
},
"_rankingScore": 0.9129111766815186
@ -1141,9 +1120,9 @@ async fn experimental_feature_vector_store() {
"id": "450465",
"_vectors": {
"manual": [
-100.0,
340.0,
90.0
-100,
340,
90
]
},
"_rankingScore": 0.8106412887573242
@ -1153,9 +1132,9 @@ async fn experimental_feature_vector_store() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
},
"_rankingScore": 0.7412010431289673
@ -1165,9 +1144,9 @@ async fn experimental_feature_vector_store() {
"id": "522681",
"_vectors": {
"manual": [
10.0,
-23.0,
32.0
10,
-23,
32
]
},
"_rankingScore": 0.6972063183784485
@ -1426,9 +1405,9 @@ async fn simple_search_with_strange_synonyms() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
}
}
@ -1447,9 +1426,9 @@ async fn simple_search_with_strange_synonyms() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
}
}
@ -1468,9 +1447,9 @@ async fn simple_search_with_strange_synonyms() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
}
}

View File

@ -75,9 +75,9 @@ async fn simple_search_single_index() {
"id": "450465",
"_vectors": {
"manual": [
-100.0,
340.0,
90.0
-100,
340,
90
]
}
}
@ -96,9 +96,9 @@ async fn simple_search_single_index() {
"id": "299537",
"_vectors": {
"manual": [
1.0,
2.0,
54.0
1,
2,
54
]
}
}
@ -194,9 +194,9 @@ async fn simple_search_two_indexes() {
"id": "450465",
"_vectors": {
"manual": [
-100.0,
340.0,
90.0
-100,
340,
90
]
}
}
@ -227,9 +227,9 @@ async fn simple_search_two_indexes() {
"cattos": "pésti",
"_vectors": {
"manual": [
1.0,
2.0,
3.0
1,
2,
3
]
}
},
@ -249,9 +249,9 @@ async fn simple_search_two_indexes() {
],
"_vectors": {
"manual": [
1.0,
2.0,
54.0
1,
2,
54
]
}
}

View File

@ -285,10 +285,10 @@ async fn attributes_ranking_rule_order() {
@r###"
[
{
"id": "1"
"id": "2"
},
{
"id": "2"
"id": "1"
}
]
"###

View File

@ -98,7 +98,8 @@ async fn secrets_are_hidden_in_settings() {
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);

View File

@ -1,696 +0,0 @@
use meili_snap::*;
use super::DOCUMENTS;
use crate::common::Server;
use crate::json;
#[actix_rt::test]
async fn similar_unexisting_index() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let expected_response = json!({
"message": "Index `test` not found.",
"code": "index_not_found",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#index_not_found"
});
index
.similar(json!({"id": 287947}), |response, code| {
assert_eq!(code, 404);
assert_eq!(response, expected_response);
})
.await;
}
#[actix_rt::test]
async fn similar_unexisting_parameter() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
index
.similar(json!({"id": 287947, "marin": "hello"}), |response, code| {
assert_eq!(code, 400, "{}", response);
assert_eq!(response["code"], "bad_request");
})
.await;
}
#[actix_rt::test]
async fn similar_feature_not_enabled() {
let server = Server::new().await;
let index = server.index("test");
let (response, code) = index.similar_post(json!({"id": 287947})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Using the similar API requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
"code": "feature_not_enabled",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
}
"###);
}
#[actix_rt::test]
async fn similar_bad_id() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let (response, code) = index.similar_post(json!({"id": ["doggo"]})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value at `.id`: the value of `id` is invalid. A document identifier can be of type integer or string, only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_).",
"code": "invalid_similar_id",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_id"
}
"###);
}
#[actix_rt::test]
async fn similar_invalid_id() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let (response, code) = index.similar_post(json!({"id": "http://invalid-docid/"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value at `.id`: the value of `id` is invalid. A document identifier can be of type integer or string, only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_).",
"code": "invalid_similar_id",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_id"
}
"###);
}
#[actix_rt::test]
async fn similar_not_found_id() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let (response, code) = index.similar_post(json!({"id": "definitely-doesnt-exist"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Document `definitely-doesnt-exist` not found.",
"code": "not_found_similar_id",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#not_found_similar_id"
}
"###);
}
#[actix_rt::test]
async fn similar_bad_offset() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let (response, code) = index.similar_post(json!({"id": 287947, "offset": "doggo"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.offset`: expected a positive integer, but found a string: `\"doggo\"`",
"code": "invalid_similar_offset",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_offset"
}
"###);
let (response, code) = index.similar_get("id=287947&offset=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value in parameter `offset`: could not parse `doggo` as a positive integer",
"code": "invalid_similar_offset",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_offset"
}
"###);
}
#[actix_rt::test]
async fn similar_bad_limit() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let (response, code) = index.similar_post(json!({"id": 287947, "limit": "doggo"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.limit`: expected a positive integer, but found a string: `\"doggo\"`",
"code": "invalid_similar_limit",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_limit"
}
"###);
let (response, code) = index.similar_get("id=287946&limit=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value in parameter `limit`: could not parse `doggo` as a positive integer",
"code": "invalid_similar_limit",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_limit"
}
"###);
}
#[actix_rt::test]
async fn similar_bad_filter() {
// Since a filter is deserialized as a json Value it will never fail to deserialize.
// Thus the error message is not generated by deserr but written by us.
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
snapshot!(code, @"202 Accepted");
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let (response, code) = index.similar_post(json!({ "id": 287947, "filter": true })).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid syntax for the filter parameter: `expected String, Array, found: true`.",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
}
"###);
// Can't make the `filter` fail with a get search since it'll accept anything as a strings.
}
#[actix_rt::test]
async fn filter_invalid_syntax_object() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "Was expecting an operation `=`, `!=`, `>=`, `>`, `<=`, `<`, `IN`, `NOT IN`, `TO`, `EXISTS`, `NOT EXISTS`, `IS NULL`, `IS NOT NULL`, `IS EMPTY`, `IS NOT EMPTY`, `_geoRadius`, or `_geoBoundingBox` at `title & Glass`.\n1:14 title & Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": "title & Glass"}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_invalid_syntax_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "Was expecting an operation `=`, `!=`, `>=`, `>`, `<=`, `<`, `IN`, `NOT IN`, `TO`, `EXISTS`, `NOT EXISTS`, `IS NULL`, `IS NOT NULL`, `IS EMPTY`, `IS NOT EMPTY`, `_geoRadius`, or `_geoBoundingBox` at `title & Glass`.\n1:14 title & Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": ["title & Glass"]}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_invalid_syntax_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "Found unexpected characters at the end of the filter: `XOR title = Glass`. You probably forgot an `OR` or an `AND` rule.\n15:32 title = Glass XOR title = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(
json!({"id": 287947, "filter": "title = Glass XOR title = Glass"}),
|response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
},
)
.await;
}
#[actix_rt::test]
async fn filter_invalid_attribute_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": ["many = Glass"]}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_invalid_attribute_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": "many = Glass"}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_reserved_geo_attribute_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "`_geo` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:13 _geo = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": ["_geo = Glass"]}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_reserved_geo_attribute_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "`_geo` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:13 _geo = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": "_geo = Glass"}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_reserved_attribute_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "`_geoDistance` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:21 _geoDistance = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": ["_geoDistance = Glass"]}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_reserved_attribute_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "`_geoDistance` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:21 _geoDistance = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": "_geoDistance = Glass"}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_reserved_geo_point_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "`_geoPoint` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:18 _geoPoint = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": ["_geoPoint = Glass"]}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}
#[actix_rt::test]
async fn filter_reserved_geo_point_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "`_geoPoint` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:18 _geoPoint = Glass",
"code": "invalid_similar_filter",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
});
index
.similar(json!({"id": 287947, "filter": "_geoPoint = Glass"}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
}

View File

@ -1,373 +0,0 @@
mod errors;
use meili_snap::{json_string, snapshot};
use once_cell::sync::Lazy;
use crate::common::{Server, Value};
use crate::json;
static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
json!([
{
"title": "Shazam!",
"release_year": 2019,
"id": "287947",
// Three semantic properties:
// 1. magic, anything that reminds you of magic
// 2. authority, anything that inspires command
// 3. horror, anything that inspires fear or dread
"_vectors": { "manual": [0.8, 0.4, -0.5]},
},
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": { "manual": [0.6, 0.8, -0.2] },
},
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": { "manual": [0.1, 0.6, 0.8] },
},
{
"title": "How to Train Your Dragon: The Hidden World",
"release_year": 2019,
"id": "166428",
"_vectors": { "manual": [0.7, 0.7, -0.4] },
},
{
"title": "All Quiet on the Western Front",
"release_year": 1930,
"id": "143",
"_vectors": { "manual": [-0.5, 0.3, 0.85] },
}
])
});
#[actix_rt::test]
async fn basic() {
let server = Server::new().await;
let index = server.index("test");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
index
.similar(json!({"id": 143}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": [
0.1,
0.6,
0.8
]
}
},
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": [
0.6,
0.8,
-0.2
]
}
},
{
"title": "How to Train Your Dragon: The Hidden World",
"release_year": 2019,
"id": "166428",
"_vectors": {
"manual": [
0.7,
0.7,
-0.4
]
}
},
{
"title": "Shazam!",
"release_year": 2019,
"id": "287947",
"_vectors": {
"manual": [
0.8,
0.4,
-0.5
]
}
}
]
"###);
})
.await;
index
.similar(json!({"id": "299537"}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "How to Train Your Dragon: The Hidden World",
"release_year": 2019,
"id": "166428",
"_vectors": {
"manual": [
0.7,
0.7,
-0.4
]
}
},
{
"title": "Shazam!",
"release_year": 2019,
"id": "287947",
"_vectors": {
"manual": [
0.8,
0.4,
-0.5
]
}
},
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": [
0.1,
0.6,
0.8
]
}
},
{
"title": "All Quiet on the Western Front",
"release_year": 1930,
"id": "143",
"_vectors": {
"manual": [
-0.5,
0.3,
0.85
]
}
}
]
"###);
})
.await;
}
#[actix_rt::test]
async fn filter() {
let server = Server::new().await;
let index = server.index("test");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title", "release_year"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
index
.similar(json!({"id": 522681, "filter": "release_year = 2019"}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": [
0.6,
0.8,
-0.2
]
}
},
{
"title": "How to Train Your Dragon: The Hidden World",
"release_year": 2019,
"id": "166428",
"_vectors": {
"manual": [
0.7,
0.7,
-0.4
]
}
},
{
"title": "Shazam!",
"release_year": 2019,
"id": "287947",
"_vectors": {
"manual": [
0.8,
0.4,
-0.5
]
}
}
]
"###);
})
.await;
index
.similar(json!({"id": 522681, "filter": "release_year < 2000"}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "All Quiet on the Western Front",
"release_year": 1930,
"id": "143",
"_vectors": {
"manual": [
-0.5,
0.3,
0.85
]
}
}
]
"###);
})
.await;
}
#[actix_rt::test]
async fn limit_and_offset() {
let server = Server::new().await;
let index = server.index("test");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
index
.similar(json!({"id": 143, "limit": 1}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": [
0.1,
0.6,
0.8
]
}
}
]
"###);
})
.await;
index
.similar(json!({"id": 143, "limit": 1, "offset": 1}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": [
0.6,
0.8,
-0.2
]
}
}
]
"###);
})
.await;
}

View File

@ -1,5 +1,6 @@
use std::time::Duration;
use actix_rt::time::sleep;
use meili_snap::{json_string, snapshot};
use meilisearch::option::ScheduleSnapshot;
use meilisearch::Opt;
@ -31,7 +32,6 @@ macro_rules! verify_snapshot {
}
#[actix_rt::test]
#[cfg_attr(target_os = "windows", ignore)]
async fn perform_snapshot() {
let temp = tempfile::tempdir().unwrap();
let snapshot_dir = tempfile::tempdir().unwrap();
@ -53,29 +53,11 @@ async fn perform_snapshot() {
index.load_test_set().await;
let (task, code) = server.index("test1").create(Some("prim")).await;
meili_snap::snapshot!(code, @"202 Accepted");
server.index("test1").create(Some("prim")).await;
index.wait_task(task.uid()).await;
index.wait_task(2).await;
// wait for the _next task_ to process, aka the snapshot that should be enqueued at some point
println!("waited for the next task to finish");
let now = std::time::Instant::now();
let next_task = task.uid() + 1;
loop {
let (value, code) = index.get_task(next_task).await;
dbg!(&value);
if code != 404 && value["status"].as_str() == Some("succeeded") {
break;
}
if now.elapsed() > Duration::from_secs(30) {
panic!("The snapshot didn't schedule in 30s even though it was supposed to be scheduled every 2s: {}",
serde_json::to_string_pretty(&value).unwrap()
);
}
}
sleep(Duration::from_secs(2)).await;
let temp = tempfile::tempdir().unwrap();

View File

@ -80,7 +80,9 @@ fn main() -> anyhow::Result<()> {
/// Clears the task queue located at `db_path`.
fn clear_task_queue(db_path: PathBuf) -> anyhow::Result<()> {
let path = db_path.join("tasks");
let env = unsafe { EnvOpenOptions::new().max_dbs(100).open(&path) }
let env = EnvOpenOptions::new()
.max_dbs(100)
.open(&path)
.with_context(|| format!("While trying to open {:?}", path.display()))?;
eprintln!("Deleting tasks from the database...");
@ -127,7 +129,7 @@ fn clear_task_queue(db_path: PathBuf) -> anyhow::Result<()> {
}
}
eprintln!("Successfully deleted {count} content files from disk!");
eprintln!("Sucessfully deleted {count} content files from disk!");
Ok(())
}
@ -191,7 +193,9 @@ fn export_a_dump(
FileStore::new(db_path.join("update_files")).context("While opening the FileStore")?;
let index_scheduler_path = db_path.join("tasks");
let env = unsafe { EnvOpenOptions::new().max_dbs(100).open(&index_scheduler_path) }
let env = EnvOpenOptions::new()
.max_dbs(100)
.open(&index_scheduler_path)
.with_context(|| format!("While trying to open {:?}", index_scheduler_path.display()))?;
eprintln!("Dumping the keys...");

View File

@ -30,7 +30,7 @@ grenad = { version = "0.4.6", default-features = false, features = [
"rayon",
"tempfile",
] }
heed = { version = "0.20.1", default-features = false, features = [
heed = { version = "0.20.0-alpha.9", default-features = false, features = [
"serde-json",
"serde-bincode",
"read-txn-no-tls",
@ -67,6 +67,9 @@ filter-parser = { path = "../filter-parser" }
# documents words self-join
itertools = "0.11.0"
# profiling
puffin = "0.16.0"
csv = "1.3.0"
candle-core = { version = "0.4.1" }
candle-transformers = { version = "0.4.1" }
@ -79,10 +82,10 @@ hf-hub = { git = "https://github.com/dureuill/hf-hub.git", branch = "rust_tls",
] }
tiktoken-rs = "0.5.8"
liquid = "0.26.4"
arroy = "0.3.1"
arroy = "0.2.0"
rand = "0.8.5"
tracing = "0.1.40"
ureq = { version = "2.9.7", features = ["json"] }
ureq = { version = "2.9.6", features = ["json"] }
url = "2.5.0"
[dev-dependencies]

View File

@ -48,8 +48,8 @@ fn main() -> Result<(), Box<dyn Error>> {
let start = Instant::now();
let mut ctx = SearchContext::new(&index, &txn)?;
let universe = filtered_universe(ctx.index, ctx.txn, &None)?;
let mut ctx = SearchContext::new(&index, &txn);
let universe = filtered_universe(&ctx, &None)?;
let docs = execute_search(
&mut ctx,

View File

@ -1,3 +0,0 @@
target
corpus
artifacts

View File

@ -203,7 +203,7 @@ fn parse_csv_header(header: &str) -> (&str, AllowedType) {
"string" => (field_name, AllowedType::String),
"boolean" => (field_name, AllowedType::Boolean),
"number" => (field_name, AllowedType::Number),
// if the pattern isn't recognized, we keep the whole field.
// if the pattern isn't reconized, we keep the whole field.
_otherwise => (header, AllowedType::String),
},
None => (header, AllowedType::String),

View File

@ -12,10 +12,7 @@ use bimap::BiHashMap;
pub use builder::DocumentsBatchBuilder;
pub use enriched::{EnrichedDocument, EnrichedDocumentsBatchCursor, EnrichedDocumentsBatchReader};
use obkv::KvReader;
pub use primary_key::{
validate_document_id_value, DocumentIdExtractionError, FieldIdMapper, PrimaryKey,
DEFAULT_PRIMARY_KEY,
};
pub use primary_key::{DocumentIdExtractionError, FieldIdMapper, PrimaryKey, DEFAULT_PRIMARY_KEY};
pub use reader::{DocumentsBatchCursor, DocumentsBatchCursorError, DocumentsBatchReader};
use serde::{Deserialize, Serialize};

View File

@ -60,7 +60,7 @@ impl<'a> PrimaryKey<'a> {
Some(document_id_bytes) => {
let document_id = serde_json::from_slice(document_id_bytes)
.map_err(InternalError::SerdeJson)?;
match validate_document_id_value(document_id) {
match validate_document_id_value(document_id)? {
Ok(document_id) => Ok(Ok(document_id)),
Err(user_error) => {
Ok(Err(DocumentIdExtractionError::InvalidDocumentId(user_error)))
@ -88,7 +88,7 @@ impl<'a> PrimaryKey<'a> {
}
match matching_documents_ids.pop() {
Some(document_id) => match validate_document_id_value(document_id) {
Some(document_id) => match validate_document_id_value(document_id)? {
Ok(document_id) => Ok(Ok(document_id)),
Err(user_error) => {
Ok(Err(DocumentIdExtractionError::InvalidDocumentId(user_error)))
@ -159,14 +159,14 @@ fn validate_document_id(document_id: &str) -> Option<&str> {
}
}
pub fn validate_document_id_value(document_id: Value) -> StdResult<String, UserError> {
pub fn validate_document_id_value(document_id: Value) -> Result<StdResult<String, UserError>> {
match document_id {
Value::String(string) => match validate_document_id(&string) {
Some(s) if s.len() == string.len() => Ok(string),
Some(s) => Ok(s.to_string()),
None => Err(UserError::InvalidDocumentId { document_id: Value::String(string) }),
Some(s) if s.len() == string.len() => Ok(Ok(string)),
Some(s) => Ok(Ok(s.to_string())),
None => Ok(Err(UserError::InvalidDocumentId { document_id: Value::String(string) })),
},
Value::Number(number) if number.is_i64() => Ok(number.to_string()),
content => Err(UserError::InvalidDocumentId { document_id: content }),
Value::Number(number) if number.is_i64() => Ok(Ok(number.to_string())),
content => Ok(Err(UserError::InvalidDocumentId { document_id: content })),
}
}

View File

@ -32,8 +32,6 @@ pub enum InternalError {
DatabaseClosing,
#[error("Missing {} in the {db_name} database.", key.unwrap_or("key"))]
DatabaseMissingEntry { db_name: &'static str, key: Option<&'static str> },
#[error("Missing {key} in the fieldids weights mapping.")]
FieldidsWeightsMapMissingEntry { key: FieldId },
#[error(transparent)]
FieldIdMapMissingEntry(#[from] FieldIdMapMissingEntry),
#[error("Missing {key} in the field id mapping.")]
@ -48,6 +46,8 @@ pub enum InternalError {
GrenadInvalidFormatVersion,
#[error("Invalid merge while processing {process}")]
IndexingMergingKeys { process: &'static str },
#[error("{}", HeedError::InvalidDatabaseTyping)]
InvalidDatabaseTyping,
#[error(transparent)]
RayonThreadPool(#[from] ThreadPoolBuildError),
#[error(transparent)]
@ -117,8 +117,10 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
InvalidGeoField(#[from] GeoError),
#[error("Invalid vector dimensions: expected: `{}`, found: `{}`.", .expected, .found)]
InvalidVectorDimensions { expected: usize, found: usize },
#[error("The `_vectors.{subfield}` field in the document with id: `{document_id}` is not an array. Was expecting an array of floats or an array of arrays of floats but instead got `{value}`.")]
InvalidVectorsType { document_id: Value, value: Value, subfield: String },
#[error("The `_vectors` field in the document with id: `{document_id}` is not an object. Was expecting an object with a key for each embedder with manually provided vectors, but instead got `{value}`")]
InvalidVectorsMapType { document_id: String, value: Value },
InvalidVectorsMapType { document_id: Value, value: Value },
#[error("{0}")]
InvalidFilter(String),
#[error("Invalid type for filter subexpression: expected: {}, found: {1}.", .0.join(", "))]
@ -425,6 +427,7 @@ impl From<HeedError> for Error {
// TODO use the encoding
HeedError::Encoding(_) => InternalError(Serialization(Encoding { db_name: None })),
HeedError::Decoding(_) => InternalError(Serialization(Decoding { db_name: None })),
HeedError::InvalidDatabaseTyping => InternalError(InvalidDatabaseTyping),
HeedError::DatabaseClosing => InternalError(DatabaseClosing),
HeedError::BadOpenOptions { .. } => UserError(InvalidLmdbOpenOptions),
}

View File

@ -1,48 +0,0 @@
//! The fieldids weights map is in charge of storing linking the searchable fields with their weights.
use std::collections::HashMap;
use serde::{Deserialize, Serialize};
use crate::{FieldId, FieldsIdsMap, Weight};
#[derive(Debug, Default, Serialize, Deserialize)]
pub struct FieldidsWeightsMap {
map: HashMap<FieldId, Weight>,
}
impl FieldidsWeightsMap {
/// Insert a field id -> weigth into the map.
/// If the map did not have this key present, `None` is returned.
/// If the map did have this key present, the value is updated, and the old value is returned.
pub fn insert(&mut self, fid: FieldId, weight: Weight) -> Option<Weight> {
self.map.insert(fid, weight)
}
/// Create the map from the fields ids maps.
/// Should only be called in the case there are NO searchable attributes.
/// All the fields will be inserted in the order of the fields ids map with a weight of 0.
pub fn from_field_id_map_without_searchable(fid_map: &FieldsIdsMap) -> Self {
FieldidsWeightsMap { map: fid_map.ids().map(|fid| (fid, 0)).collect() }
}
/// Removes a field id from the map, returning the associated weight previously in the map.
pub fn remove(&mut self, fid: FieldId) -> Option<Weight> {
self.map.remove(&fid)
}
/// Returns weight corresponding to the key.
pub fn weight(&self, fid: FieldId) -> Option<Weight> {
self.map.get(&fid).copied()
}
/// Returns highest weight contained in the map if any.
pub fn max_weight(&self) -> Option<Weight> {
self.map.values().copied().max()
}
/// Return an iterator visiting all field ids in arbitrary order.
pub fn ids(&self) -> impl Iterator<Item = FieldId> + '_ {
self.map.keys().copied()
}
}

View File

@ -195,7 +195,7 @@ mod tests {
fn merge_cbo_roaring_bitmaps() {
let mut buffer = Vec::new();
let small_data = [
let small_data = vec![
RoaringBitmap::from_sorted_iter(1..4).unwrap(),
RoaringBitmap::from_sorted_iter(2..5).unwrap(),
RoaringBitmap::from_sorted_iter(4..6).unwrap(),
@ -209,7 +209,7 @@ mod tests {
let expected = RoaringBitmap::from_sorted_iter(1..6).unwrap();
assert_eq!(bitmap, expected);
let medium_data = [
let medium_data = vec![
RoaringBitmap::from_sorted_iter(1..4).unwrap(),
RoaringBitmap::from_sorted_iter(2..5).unwrap(),
RoaringBitmap::from_sorted_iter(4..8).unwrap(),

View File

@ -1,6 +1,5 @@
use std::borrow::Cow;
use std::collections::{BTreeMap, BTreeSet, HashMap, HashSet};
use std::convert::TryInto;
use std::fs::File;
use std::path::Path;
@ -9,7 +8,6 @@ use heed::types::*;
use heed::{CompactionOption, Database, RoTxn, RwTxn, Unspecified};
use roaring::RoaringBitmap;
use rstar::RTree;
use serde::Serialize;
use time::OffsetDateTime;
use crate::documents::PrimaryKey;
@ -24,12 +22,11 @@ use crate::heed_codec::{
};
use crate::order_by_map::OrderByMap;
use crate::proximity::ProximityPrecision;
use crate::vector::{Embedding, EmbeddingConfig};
use crate::vector::EmbeddingConfig;
use crate::{
default_criteria, CboRoaringBitmapCodec, Criterion, DocumentId, ExternalDocumentsIds,
FacetDistribution, FieldDistribution, FieldId, FieldIdMapMissingEntry, FieldIdWordCountCodec,
FieldidsWeightsMap, GeoPoint, ObkvCodec, Result, RoaringBitmapCodec, RoaringBitmapLenCodec,
Search, U8StrStrCodec, Weight, BEU16, BEU32, BEU64,
FacetDistribution, FieldDistribution, FieldId, FieldIdWordCountCodec, GeoPoint, ObkvCodec,
Result, RoaringBitmapCodec, RoaringBitmapLenCodec, Search, U8StrStrCodec, BEU16, BEU32, BEU64,
};
pub const DEFAULT_MIN_WORD_LEN_ONE_TYPO: u8 = 5;
@ -45,7 +42,6 @@ pub mod main_key {
pub const SORTABLE_FIELDS_KEY: &str = "sortable-fields";
pub const FIELD_DISTRIBUTION_KEY: &str = "fields-distribution";
pub const FIELDS_IDS_MAP_KEY: &str = "fields-ids-map";
pub const FIELDIDS_WEIGHTS_MAP_KEY: &str = "fieldids-weights-map";
pub const GEO_FACETED_DOCUMENTS_IDS_KEY: &str = "geo-faceted-documents-ids";
pub const GEO_RTREE_KEY: &str = "geo-rtree";
pub const PRIMARY_KEY_KEY: &str = "primary-key";
@ -185,7 +181,7 @@ impl Index {
options.max_dbs(25);
let env = unsafe { options.open(path) }?;
let env = options.open(path)?;
let mut wtxn = env.write_txn()?;
let main = env.database_options().name(MAIN).create(&mut wtxn)?;
let word_docids = env.create_database(&mut wtxn, Some(WORD_DOCIDS))?;
@ -295,11 +291,6 @@ impl Index {
self.env.read_txn()
}
/// Create a static read transaction to be able to read the index without keeping a reference to it.
pub fn static_read_txn(&self) -> heed::Result<RoTxn<'static>> {
self.env.clone().static_read_txn()
}
/// Returns the canonicalized path where the heed `Env` of this `Index` lives.
pub fn path(&self) -> &Path {
self.env.path()
@ -325,87 +316,6 @@ impl Index {
self.env.info().map_size
}
pub fn advanced_stats(&self, rtxn: &heed::RoTxn) -> Result<AdvancedStats> {
use db_name::*;
let mut dbs = BTreeMap::new();
dbs.insert(WORD_DOCIDS, advanced_database_stats(rtxn, self.word_docids)?);
dbs.insert(
WORD_PAIR_PROXIMITY_DOCIDS,
advanced_database_stats(rtxn, self.word_pair_proximity_docids)?,
);
dbs.insert(WORD_PREFIX_DOCIDS, advanced_database_stats(rtxn, self.word_prefix_docids)?);
dbs.insert(WORD_FIELD_ID_DOCIDS, advanced_database_stats(rtxn, self.word_fid_docids)?);
dbs.insert(WORD_POSITION_DOCIDS, advanced_database_stats(rtxn, self.word_position_docids)?);
dbs.insert(DOCUMENTS, advanced_database_stats_no_bitmap(rtxn, self.documents)?);
fn advanced_database_stats<KC>(
rtxn: &heed::RoTxn,
db: Database<KC, CboRoaringBitmapCodec>,
) -> Result<AdvancedDatabaseStats> {
let db = db.remap_key_type::<Bytes>().lazily_decode_data();
let mut entries_count = 0;
let mut total_bitmap_size = 0;
let mut total_bitmap_len = 0;
let mut total_key_size = 0;
for result in db.iter(rtxn)? {
let (bytes_key, lazy_value) = result?;
entries_count += 1;
total_bitmap_size += lazy_value.remap::<Bytes>().decode().unwrap().len();
let bitmap = lazy_value.decode().map_err(heed::Error::Decoding)?;
total_bitmap_len += bitmap.len();
total_key_size += bytes_key.len();
}
Ok(AdvancedDatabaseStats {
entries_count,
average_bitmap_len: Some(total_bitmap_len as f64 / entries_count as f64),
median_bitmap_len: None,
average_value_size: Some(total_bitmap_size as f64 / entries_count as f64),
median_value_size: None,
average_key_size: Some(total_key_size as f64 / entries_count as f64),
median_key_size: None,
})
}
fn advanced_database_stats_no_bitmap<KC, DC>(
rtxn: &heed::RoTxn,
db: Database<KC, DC>,
) -> Result<AdvancedDatabaseStats> {
let db = db.remap_types::<Bytes, Bytes>();
let mut entries_count = 0;
let mut total_value_size = 0;
let mut total_key_size = 0;
for result in db.iter(rtxn)? {
let (bytes_key, bytes_value) = result?;
entries_count += 1;
total_value_size += bytes_value.len();
total_key_size += bytes_key.len();
}
Ok(AdvancedDatabaseStats {
entries_count,
average_bitmap_len: None,
median_bitmap_len: None,
average_value_size: Some(total_value_size as f64 / entries_count as f64),
median_value_size: None,
average_key_size: Some(total_key_size as f64 / entries_count as f64),
median_key_size: None,
})
}
Ok(AdvancedStats {
map_size: self.map_size(),
non_free_pages_size: self.on_disk_size()?,
on_disk_size: self.on_disk_size()?,
databases: dbs,
})
}
pub fn copy_to_file<P: AsRef<Path>>(&self, path: P, option: CompactionOption) -> Result<File> {
self.env.copy_to_file(path, option).map_err(Into::into)
}
@ -504,65 +414,6 @@ impl Index {
.unwrap_or_default())
}
/* fieldids weights map */
// This maps the fields ids to their weights.
// Their weights is defined by the ordering of the searchable attributes.
/// Writes the fieldids weights map which associates the field ids to their weights
pub(crate) fn put_fieldids_weights_map(
&self,
wtxn: &mut RwTxn,
map: &FieldidsWeightsMap,
) -> heed::Result<()> {
self.main.remap_types::<Str, SerdeJson<_>>().put(
wtxn,
main_key::FIELDIDS_WEIGHTS_MAP_KEY,
map,
)
}
/// Get the fieldids weights map which associates the field ids to their weights
pub fn fieldids_weights_map(&self, rtxn: &RoTxn) -> heed::Result<FieldidsWeightsMap> {
self.main
.remap_types::<Str, SerdeJson<_>>()
.get(rtxn, main_key::FIELDIDS_WEIGHTS_MAP_KEY)?
.map(Ok)
.unwrap_or_else(|| {
Ok(FieldidsWeightsMap::from_field_id_map_without_searchable(
&self.fields_ids_map(rtxn)?,
))
})
}
/// Delete the fieldsids weights map
pub fn delete_fieldids_weights_map(&self, wtxn: &mut RwTxn) -> heed::Result<bool> {
self.main.remap_key_type::<Str>().delete(wtxn, main_key::FIELDIDS_WEIGHTS_MAP_KEY)
}
pub fn searchable_fields_and_weights<'a>(
&self,
rtxn: &'a RoTxn,
) -> Result<Vec<(Cow<'a, str>, FieldId, Weight)>> {
let fid_map = self.fields_ids_map(rtxn)?;
let weight_map = self.fieldids_weights_map(rtxn)?;
let searchable = self.searchable_fields(rtxn)?;
searchable
.into_iter()
.map(|field| -> Result<_> {
let fid = fid_map.id(&field).ok_or_else(|| FieldIdMapMissingEntry::FieldName {
field_name: field.to_string(),
process: "searchable_fields_and_weights",
})?;
let weight = weight_map
.weight(fid)
.ok_or(InternalError::FieldidsWeightsMapMissingEntry { key: fid })?;
Ok((field, fid, weight))
})
.collect()
}
/* geo rtree */
/// Writes the provided `rtree` which associates coordinates to documents ids.
@ -727,42 +578,33 @@ impl Index {
wtxn: &mut RwTxn,
user_fields: &[&str],
fields_ids_map: &FieldsIdsMap,
) -> Result<()> {
) -> heed::Result<()> {
// We can write the user defined searchable fields as-is.
self.put_user_defined_searchable_fields(wtxn, user_fields)?;
let mut weights = FieldidsWeightsMap::default();
// Now we generate the real searchable fields:
// 1. Take the user defined searchable fields as-is to keep the priority defined by the attributes criterion.
// 2. Iterate over the user defined searchable fields.
// 3. If a user defined field is a subset of a field defined in the fields_ids_map
// (ie doggo.name is a subset of doggo) right after doggo and with the same weight.
let mut real_fields = Vec::new();
// (ie doggo.name is a subset of doggo) then we push it at the end of the fields.
let mut real_fields = user_fields.to_vec();
for (id, field_from_map) in fields_ids_map.iter() {
for (weight, user_field) in user_fields.iter().enumerate() {
for field_from_map in fields_ids_map.names() {
for user_field in user_fields {
if crate::is_faceted_by(field_from_map, user_field)
&& !real_fields.contains(&field_from_map)
&& !user_fields.contains(&field_from_map)
{
real_fields.push(field_from_map);
let weight: u16 =
weight.try_into().map_err(|_| UserError::AttributeLimitReached)?;
weights.insert(id, weight);
}
}
}
self.put_searchable_fields(wtxn, &real_fields)?;
self.put_fieldids_weights_map(wtxn, &weights)?;
Ok(())
self.put_searchable_fields(wtxn, &real_fields)
}
pub(crate) fn delete_all_searchable_fields(&self, wtxn: &mut RwTxn) -> heed::Result<bool> {
let did_delete_searchable = self.delete_searchable_fields(wtxn)?;
let did_delete_user_defined = self.delete_user_defined_searchable_fields(wtxn)?;
self.delete_fieldids_weights_map(wtxn)?;
Ok(did_delete_searchable || did_delete_user_defined)
}
@ -781,31 +623,28 @@ impl Index {
}
/// Returns the searchable fields, those are the fields that are indexed,
pub fn searchable_fields<'t>(&self, rtxn: &'t RoTxn) -> heed::Result<Vec<Cow<'t, str>>> {
/// if the searchable fields aren't there it means that **all** the fields are indexed.
pub fn searchable_fields<'t>(&self, rtxn: &'t RoTxn) -> heed::Result<Option<Vec<&'t str>>> {
self.main
.remap_types::<Str, SerdeBincode<Vec<&'t str>>>()
.get(rtxn, main_key::SEARCHABLE_FIELDS_KEY)?
.map(|fields| Ok(fields.into_iter().map(Cow::Borrowed).collect()))
.unwrap_or_else(|| {
Ok(self
.fields_ids_map(rtxn)?
.names()
.map(|field| Cow::Owned(field.to_string()))
.collect())
})
.get(rtxn, main_key::SEARCHABLE_FIELDS_KEY)
}
/// Identical to `searchable_fields`, but returns the ids instead.
pub fn searchable_fields_ids(&self, rtxn: &RoTxn) -> Result<Vec<FieldId>> {
let fields = self.searchable_fields(rtxn)?;
let fields_ids_map = self.fields_ids_map(rtxn)?;
let mut fields_ids = Vec::new();
for name in fields {
if let Some(field_id) = fields_ids_map.id(&name) {
fields_ids.push(field_id);
pub fn searchable_fields_ids(&self, rtxn: &RoTxn) -> Result<Option<Vec<FieldId>>> {
match self.searchable_fields(rtxn)? {
Some(fields) => {
let fields_ids_map = self.fields_ids_map(rtxn)?;
let mut fields_ids = Vec::new();
for name in fields {
if let Some(field_id) = fields_ids_map.id(name) {
fields_ids.push(field_id);
}
}
Ok(Some(fields_ids))
}
None => Ok(None),
}
Ok(fields_ids)
}
/// Writes the searchable fields, when this list is specified, only these are indexed.
@ -1677,22 +1516,6 @@ impl Index {
.unwrap_or_default())
}
pub fn arroy_readers<'a>(
&'a self,
rtxn: &'a RoTxn<'a>,
embedder_id: u8,
) -> impl Iterator<Item = Result<arroy::Reader<arroy::distances::Angular>>> + 'a {
crate::vector::arroy_db_range_for_embedder(embedder_id).map_while(move |k| {
arroy::Reader::open(rtxn, k, self.vector_arroy)
.map(Some)
.or_else(|e| match e {
arroy::Error::MissingMetadata => Ok(None),
e => Err(e.into()),
})
.transpose()
})
}
pub(crate) fn put_search_cutoff(&self, wtxn: &mut RwTxn<'_>, cutoff: u64) -> heed::Result<()> {
self.main.remap_types::<Str, BEU64>().put(wtxn, main_key::SEARCH_CUTOFF, &cutoff)
}
@ -1704,74 +1527,6 @@ impl Index {
pub(crate) fn delete_search_cutoff(&self, wtxn: &mut RwTxn<'_>) -> heed::Result<bool> {
self.main.remap_key_type::<Str>().delete(wtxn, main_key::SEARCH_CUTOFF)
}
pub fn embeddings(
&self,
rtxn: &RoTxn<'_>,
docid: DocumentId,
) -> Result<BTreeMap<String, Vec<Embedding>>> {
let mut res = BTreeMap::new();
for row in self.embedder_category_id.iter(rtxn)? {
let (embedder_name, embedder_id) = row?;
let embedder_id = (embedder_id as u16) << 8;
let mut embeddings = Vec::new();
'vectors: for i in 0..=u8::MAX {
let reader = arroy::Reader::open(rtxn, embedder_id | (i as u16), self.vector_arroy)
.map(Some)
.or_else(|e| match e {
arroy::Error::MissingMetadata => Ok(None),
e => Err(e),
})
.transpose();
let Some(reader) = reader else {
break 'vectors;
};
let embedding = reader?.item_vector(rtxn, docid)?;
if let Some(embedding) = embedding {
embeddings.push(embedding)
} else {
break 'vectors;
}
}
if !embeddings.is_empty() {
res.insert(embedder_name.to_owned(), embeddings);
}
}
Ok(res)
}
}
#[derive(Clone, Debug, Serialize)]
pub struct AdvancedStats {
/// Size of the data memory map.
map_size: usize,
/// Returns the size used by all the databases in the environment without the free pages.
non_free_pages_size: u64,
/// The size of the data file on disk.
on_disk_size: u64,
/// Databases advanced stats.
databases: BTreeMap<&'static str, AdvancedDatabaseStats>,
}
#[derive(Clone, Debug, Serialize)]
pub struct AdvancedDatabaseStats {
/// The number of entries in this database.
entries_count: usize,
/// The average number of entries in the bitmaps of this database.
average_bitmap_len: Option<f64>,
/// The median number of entries in the bitmaps of this database.
median_bitmap_len: Option<f64>,
/// The average size of values of this database.
average_value_size: Option<f64>,
/// The median size of values of this database.
median_value_size: Option<f64>,
/// The average size of keys of this database.
average_key_size: Option<f64>,
/// The mediane size of keys of this database.
median_key_size: Option<f64>,
}
#[cfg(test)]
@ -1955,14 +1710,10 @@ pub(crate) mod tests {
]))
.unwrap();
db_snap!(index, field_distribution, @r###"
age 1 |
id 2 |
name 2 |
"###);
db_snap!(index, field_distribution, 1);
db_snap!(index, word_docids,
@r###"
@r###"
1 [0, ]
2 [1, ]
20 [1, ]
@ -1971,6 +1722,18 @@ pub(crate) mod tests {
"###
);
db_snap!(index, field_distribution);
db_snap!(index, field_distribution,
@r###"
age 1 |
id 2 |
name 2 |
"###
);
// snapshot_index!(&index, "1", include: "^field_distribution$");
// we add all the documents a second time. we are supposed to get the same
// field_distribution in the end
index
@ -2057,7 +1820,7 @@ pub(crate) mod tests {
// ensure we get the right real searchable fields + user defined searchable fields
let rtxn = index.read_txn().unwrap();
let real = index.searchable_fields(&rtxn).unwrap();
let real = index.searchable_fields(&rtxn).unwrap().unwrap();
assert_eq!(real, &["doggo", "name", "doggo.name", "doggo.age"]);
let user_defined = index.user_defined_searchable_fields(&rtxn).unwrap().unwrap();
@ -2077,7 +1840,7 @@ pub(crate) mod tests {
// ensure we get the right real searchable fields + user defined searchable fields
let rtxn = index.read_txn().unwrap();
let real = index.searchable_fields(&rtxn).unwrap();
let real = index.searchable_fields(&rtxn).unwrap().unwrap();
assert_eq!(real, &["doggo", "name"]);
let user_defined = index.user_defined_searchable_fields(&rtxn).unwrap().unwrap();
assert_eq!(user_defined, &["doggo", "name"]);
@ -2093,7 +1856,7 @@ pub(crate) mod tests {
// ensure we get the right real searchable fields + user defined searchable fields
let rtxn = index.read_txn().unwrap();
let real = index.searchable_fields(&rtxn).unwrap();
let real = index.searchable_fields(&rtxn).unwrap().unwrap();
assert_eq!(real, &["doggo", "name", "doggo.name", "doggo.age"]);
let user_defined = index.user_defined_searchable_fields(&rtxn).unwrap().unwrap();
@ -2632,14 +2395,6 @@ pub(crate) mod tests {
11 0
4 1
"###);
db_snap!(index, fields_ids_map, @r###"
0 primary_key |
"###);
db_snap!(index, searchable_fields, @r###"["primary_key"]"###);
db_snap!(index, fieldids_weights_map, @r###"
fid weight
0 0 |
"###);
index
.add_documents(documents!([
@ -2655,16 +2410,6 @@ pub(crate) mod tests {
11 0
4 1
"###);
db_snap!(index, fields_ids_map, @r###"
0 primary_key |
1 a |
"###);
db_snap!(index, searchable_fields, @r###"["primary_key", "a"]"###);
db_snap!(index, fieldids_weights_map, @r###"
fid weight
0 0 |
1 0 |
"###);
index.delete_documents(Default::default());
@ -2675,16 +2420,6 @@ pub(crate) mod tests {
11 0
4 1
"###);
db_snap!(index, fields_ids_map, @r###"
0 primary_key |
1 a |
"###);
db_snap!(index, searchable_fields, @r###"["primary_key", "a"]"###);
db_snap!(index, fieldids_weights_map, @r###"
fid weight
0 0 |
1 0 |
"###);
index
.add_documents(documents!([
@ -2700,16 +2435,6 @@ pub(crate) mod tests {
11 0
4 1
"###);
db_snap!(index, fields_ids_map, @r###"
0 primary_key |
1 a |
"###);
db_snap!(index, searchable_fields, @r###"["primary_key", "a"]"###);
db_snap!(index, fieldids_weights_map, @r###"
fid weight
0 0 |
1 0 |
"###);
let rtxn = index.read_txn().unwrap();
let search = Search::new(&rtxn, &index);
@ -2795,104 +2520,4 @@ pub(crate) mod tests {
db_snap!(index, geo_faceted_documents_ids); // ensure that no documents were inserted
}
#[test]
fn swapping_searchable_attributes() {
// See https://github.com/meilisearch/meilisearch/issues/4484
let index = TempIndex::new();
index
.update_settings(|settings| {
settings.set_searchable_fields(vec![S("name")]);
settings.set_filterable_fields(HashSet::from([S("age")]));
})
.unwrap();
index
.add_documents(documents!({ "id": 1, "name": "Many", "age": 28, "realName": "Maxime" }))
.unwrap();
db_snap!(index, fields_ids_map, @r###"
0 name |
1 id |
2 age |
3 realName |
"###);
db_snap!(index, searchable_fields, @r###"["name"]"###);
db_snap!(index, fieldids_weights_map, @r###"
fid weight
0 0 |
"###);
index
.update_settings(|settings| {
settings.set_searchable_fields(vec![S("name"), S("realName")]);
settings.set_filterable_fields(HashSet::from([S("age")]));
})
.unwrap();
// The order of the field id map shouldn't change
db_snap!(index, fields_ids_map, @r###"
0 name |
1 id |
2 age |
3 realName |
"###);
db_snap!(index, searchable_fields, @r###"["name", "realName"]"###);
db_snap!(index, fieldids_weights_map, @r###"
fid weight
0 0 |
3 1 |
"###);
}
#[test]
fn attribute_weights_after_swapping_searchable_attributes() {
// See https://github.com/meilisearch/meilisearch/issues/4484
let index = TempIndex::new();
index
.update_settings(|settings| {
settings.set_searchable_fields(vec![S("name"), S("beverage")]);
})
.unwrap();
index
.add_documents(documents!([
{ "id": 0, "name": "kefir", "beverage": "water" },
{ "id": 1, "name": "tamo", "beverage": "kefir" }
]))
.unwrap();
let rtxn = index.read_txn().unwrap();
let mut search = index.search(&rtxn);
let results = search.query("kefir").execute().unwrap();
// We should find kefir the dog first
insta::assert_debug_snapshot!(results.documents_ids, @r###"
[
0,
1,
]
"###);
index
.update_settings(|settings| {
settings.set_searchable_fields(vec![S("beverage"), S("name")]);
})
.unwrap();
let rtxn = index.read_txn().unwrap();
let mut search = index.search(&rtxn);
let results = search.query("kefir").execute().unwrap();
// We should find tamo first
insta::assert_debug_snapshot!(results.documents_ids, @r###"
[
1,
0,
]
"###);
}
}

View File

@ -28,7 +28,6 @@ pub mod vector;
#[cfg(test)]
#[macro_use]
pub mod snapshot_tests;
mod fieldids_weights_map;
use std::collections::{BTreeMap, HashMap};
use std::convert::{TryFrom, TryInto};
@ -53,7 +52,6 @@ pub use self::error::{
Error, FieldIdMapMissingEntry, InternalError, SerializationError, UserError,
};
pub use self::external_documents_ids::ExternalDocumentsIds;
pub use self::fieldids_weights_map::FieldidsWeightsMap;
pub use self::fields_ids_map::FieldsIdsMap;
pub use self::heed_codec::{
BEU16StrCodec, BEU32StrCodec, BoRoaringBitmapCodec, BoRoaringBitmapLenCodec,
@ -63,7 +61,6 @@ pub use self::heed_codec::{
};
pub use self::index::Index;
pub use self::search::facet::{FacetValueHit, SearchForFacetValues};
pub use self::search::similar::Similar;
pub use self::search::{
FacetDistribution, Filter, FormatOptions, MatchBounds, MatcherBuilder, MatchingWords, OrderBy,
Search, SearchResult, SemanticSearch, TermsMatchingStrategy, DEFAULT_VALUES_PER_FACET,
@ -80,7 +77,6 @@ pub type FastMap4<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher32>>;
pub type FastMap8<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher64>>;
pub type FieldDistribution = BTreeMap<String, u64>;
pub type FieldId = u16;
pub type Weight = u16;
pub type Object = serde_json::Map<String, serde_json::Value>;
pub type Position = u32;
pub type RelativePosition = u16;
@ -355,13 +351,43 @@ pub fn is_faceted(field: &str, faceted_fields: impl IntoIterator<Item = impl AsR
/// assert!(!is_faceted_by("animaux.chien", "animaux.chie"));
/// ```
pub fn is_faceted_by(field: &str, facet: &str) -> bool {
field.starts_with(facet) && field[facet.len()..].chars().next().map_or(true, |c| c == '.')
field.starts_with(facet)
&& field[facet.len()..].chars().next().map(|c| c == '.').unwrap_or(true)
}
pub fn normalize_facet(original: &str) -> String {
CompatibilityDecompositionNormalizer.normalize_str(original.trim()).to_lowercase()
}
/// Represents either a vector or an array of multiple vectors.
#[derive(serde::Serialize, serde::Deserialize, Debug)]
#[serde(transparent)]
pub struct VectorOrArrayOfVectors {
#[serde(with = "either::serde_untagged_optional")]
inner: Option<either::Either<Vec<f32>, Vec<Vec<f32>>>>,
}
impl VectorOrArrayOfVectors {
pub fn into_array_of_vectors(self) -> Option<Vec<Vec<f32>>> {
match self.inner? {
either::Either::Left(vector) => Some(vec![vector]),
either::Either::Right(vectors) => Some(vectors),
}
}
}
/// Normalize a vector by dividing the dimensions by the length of it.
pub fn normalize_vector(mut vector: Vec<f32>) -> Vec<f32> {
let squared: f32 = vector.iter().map(|x| x * x).sum();
let length = squared.sqrt();
if length <= f32::EPSILON {
vector
} else {
vector.iter_mut().for_each(|x| *x /= length);
vector
}
}
#[cfg(test)]
mod tests {
use serde_json::json;

View File

@ -24,7 +24,6 @@ pub mod facet;
mod fst_utils;
pub mod hybrid;
pub mod new;
pub mod similar;
#[derive(Debug, Clone)]
pub struct SemanticSearch {
@ -148,21 +147,21 @@ impl<'a> Search<'a> {
pub fn execute_for_candidates(&self, has_vector_search: bool) -> Result<RoaringBitmap> {
if has_vector_search {
let ctx = SearchContext::new(self.index, self.rtxn)?;
filtered_universe(ctx.index, ctx.txn, &self.filter)
let ctx = SearchContext::new(self.index, self.rtxn);
filtered_universe(&ctx, &self.filter)
} else {
Ok(self.execute()?.candidates)
}
}
pub fn execute(&self) -> Result<SearchResult> {
let mut ctx = SearchContext::new(self.index, self.rtxn)?;
let mut ctx = SearchContext::new(self.index, self.rtxn);
if let Some(searchable_attributes) = self.searchable_attributes {
ctx.attributes_to_search_on(searchable_attributes)?;
ctx.searchable_attributes(searchable_attributes)?;
}
let universe = filtered_universe(ctx.index, ctx.txn, &self.filter)?;
let universe = filtered_universe(&ctx, &self.filter)?;
let PartialSearchResult {
located_query_terms,
candidates,
@ -277,8 +276,6 @@ pub enum TermsMatchingStrategy {
Last,
// all words are mandatory
All,
// remove more frequent word first
Frequency,
}
impl Default for TermsMatchingStrategy {

View File

@ -101,7 +101,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
let mut ranking_rule_universes: Vec<RoaringBitmap> =
vec![RoaringBitmap::default(); ranking_rules_len];
ranking_rule_universes[0].clone_from(universe);
ranking_rule_universes[0] = universe.clone();
let mut cur_ranking_rule_index = 0;
/// Finish iterating over the current ranking rule, yielding
@ -232,7 +232,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
}
cur_ranking_rule_index += 1;
ranking_rule_universes[cur_ranking_rule_index].clone_from(&next_bucket.candidates);
ranking_rule_universes[cur_ranking_rule_index] = next_bucket.candidates.clone();
logger.start_iteration_ranking_rule(
cur_ranking_rule_index,
ranking_rules[cur_ranking_rule_index].as_ref(),

View File

@ -163,7 +163,7 @@ impl<'ctx> SearchContext<'ctx> {
Some(restricted_fids) => {
let interned = self.word_interner.get(word).as_str();
let keys: Vec<_> =
restricted_fids.tolerant.iter().map(|(fid, _)| (interned, *fid)).collect();
restricted_fids.tolerant.iter().map(|fid| (interned, *fid)).collect();
DatabaseCache::get_value_from_keys::<_, _, CboRoaringBitmapCodec>(
self.txn,
@ -192,7 +192,7 @@ impl<'ctx> SearchContext<'ctx> {
Some(restricted_fids) => {
let interned = self.word_interner.get(word).as_str();
let keys: Vec<_> =
restricted_fids.exact.iter().map(|(fid, _)| (interned, *fid)).collect();
restricted_fids.exact.iter().map(|fid| (interned, *fid)).collect();
DatabaseCache::get_value_from_keys::<_, _, CboRoaringBitmapCodec>(
self.txn,
@ -242,7 +242,7 @@ impl<'ctx> SearchContext<'ctx> {
Some(restricted_fids) => {
let interned = self.word_interner.get(prefix).as_str();
let keys: Vec<_> =
restricted_fids.tolerant.iter().map(|(fid, _)| (interned, *fid)).collect();
restricted_fids.tolerant.iter().map(|fid| (interned, *fid)).collect();
DatabaseCache::get_value_from_keys::<_, _, CboRoaringBitmapCodec>(
self.txn,
@ -271,7 +271,7 @@ impl<'ctx> SearchContext<'ctx> {
Some(restricted_fids) => {
let interned = self.word_interner.get(prefix).as_str();
let keys: Vec<_> =
restricted_fids.exact.iter().map(|(fid, _)| (interned, *fid)).collect();
restricted_fids.exact.iter().map(|fid| (interned, *fid)).collect();
DatabaseCache::get_value_from_keys::<_, _, CboRoaringBitmapCodec>(
self.txn,
@ -315,7 +315,11 @@ impl<'ctx> SearchContext<'ctx> {
.map_err(heed::Error::Decoding)?
} else {
// Compute the distance at the attribute level and store it in the cache.
let fids = self.index.searchable_fields_ids(self.txn)?;
let fids = if let Some(fids) = self.index.searchable_fields_ids(self.txn)? {
fids
} else {
self.index.fields_ids_map(self.txn)?.ids().collect()
};
let mut docids = RoaringBitmap::new();
for fid in fids {
// for each field, intersect left word bitmap and right word bitmap,
@ -404,7 +408,11 @@ impl<'ctx> SearchContext<'ctx> {
let prefix_docids = match proximity_precision {
ProximityPrecision::ByAttribute => {
// Compute the distance at the attribute level and store it in the cache.
let fids = self.index.searchable_fields_ids(self.txn)?;
let fids = if let Some(fids) = self.index.searchable_fields_ids(self.txn)? {
fids
} else {
self.index.fields_ids_map(self.txn)?.ids().collect()
};
let mut prefix_docids = RoaringBitmap::new();
// for each field, intersect left word bitmap and right word bitmap,
// then merge the result in a global bitmap before storing it in the cache.

View File

@ -184,7 +184,13 @@ impl State {
return Ok(State::Empty(query_graph.clone()));
}
let searchable_fields_ids = ctx.index.searchable_fields_ids(ctx.txn)?;
let searchable_fields_ids = {
if let Some(fids) = ctx.index.searchable_fields_ids(ctx.txn)? {
fids
} else {
ctx.index.fields_ids_map(ctx.txn)?.ids().collect()
}
};
let mut candidates_per_attribute = Vec::with_capacity(searchable_fields_ids.len());
// then check that there exists at least one attribute that has all of the terms

View File

@ -42,7 +42,7 @@ fn facet_number_values<'a>(
}
/// Define the strategy used by the geo sort.
/// The parameter represents the cache size, and, in the case of the Dynamic strategy,
/// The paramater represents the cache size, and, in the case of the Dynamic strategy,
/// the point where we move from using the iterative strategy to the rtree.
#[derive(Debug, Clone, Copy)]
pub enum Strategy {

View File

@ -164,21 +164,6 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
}
costs
}
TermsMatchingStrategy::Frequency => {
let removal_order =
query_graph.removal_order_for_terms_matching_strategy_frequency(ctx)?;
let mut forbidden_nodes =
SmallBitmap::for_interned_values_in(&query_graph.nodes);
let mut costs = query_graph.nodes.map(|_| None);
// FIXME: this works because only words uses termsmatchingstrategy at the moment.
for ns in removal_order {
for n in ns.iter() {
*costs.get_mut(n) = Some((1, forbidden_nodes.clone()));
}
forbidden_nodes.union(&ns);
}
costs
}
TermsMatchingStrategy::All => query_graph.nodes.map(|_| None),
}
} else {

View File

@ -258,7 +258,7 @@ pub(crate) mod tests {
fn matching_words() {
let temp_index = temp_index_with_documents();
let rtxn = temp_index.read_txn().unwrap();
let mut ctx = SearchContext::new(&temp_index, &rtxn).unwrap();
let mut ctx = SearchContext::new(&temp_index, &rtxn);
let mut builder = TokenizerBuilder::default();
let tokenizer = builder.build();
let tokens = tokenizer.tokenize("split this world");

View File

@ -134,7 +134,7 @@ impl<'t> Matcher<'t, '_> {
for (token_position, word_position, word) in words_positions {
partial = match partial.match_token(word) {
// token matches the partial match, but the match is not full,
// we temporarily save the current token then we try to match the next one.
// we temporarly save the current token then we try to match the next one.
Some(MatchType::Partial(partial)) => {
potential_matches.push((token_position, word_position, partial.char_len()));
partial
@ -506,8 +506,8 @@ mod tests {
impl<'a> MatcherBuilder<'a> {
fn new_test(rtxn: &'a heed::RoTxn, index: &'a TempIndex, query: &str) -> Self {
let mut ctx = SearchContext::new(index, rtxn).unwrap();
let universe = filtered_universe(ctx.index, ctx.txn, &None).unwrap();
let mut ctx = SearchContext::new(index, rtxn);
let universe = filtered_universe(&ctx, &None).unwrap();
let crate::search::PartialSearchResult { located_query_terms, .. } = execute_search(
&mut ctx,
Some(query),
@ -722,7 +722,7 @@ mod tests {
@"…void void void void void split the world void void"
);
// Text containing matches with different density.
// Text containing matches with diferent density.
let text = "split void the void void world void void void void void void void void void void split the world void void";
let mut matcher = builder.build(text);
// crop should return 10 last words with a marker at the start.

View File

@ -49,12 +49,13 @@ pub use self::geo_sort::Strategy as GeoSortStrategy;
use self::graph_based_ranking_rule::Words;
use self::interner::Interned;
use self::vector_sort::VectorSort;
use crate::error::FieldIdMapMissingEntry;
use crate::score_details::{ScoreDetails, ScoringStrategy};
use crate::search::new::distinct::apply_distinct_rule;
use crate::vector::Embedder;
use crate::{
AscDesc, DocumentId, FieldId, Filter, Index, Member, Result, TermsMatchingStrategy, TimeBudget,
UserError, Weight,
UserError,
};
/// A structure used throughout the execution of a search query.
@ -70,21 +71,8 @@ pub struct SearchContext<'ctx> {
}
impl<'ctx> SearchContext<'ctx> {
pub fn new(index: &'ctx Index, txn: &'ctx RoTxn<'ctx>) -> Result<Self> {
let searchable_fids = index.searchable_fields_and_weights(txn)?;
let exact_attributes_ids = index.exact_attributes_ids(txn)?;
let mut exact = Vec::new();
let mut tolerant = Vec::new();
for (_name, fid, weight) in searchable_fids {
if exact_attributes_ids.contains(&fid) {
exact.push((fid, weight));
} else {
tolerant.push((fid, weight));
}
}
Ok(Self {
pub fn new(index: &'ctx Index, txn: &'ctx RoTxn<'ctx>) -> Self {
Self {
index,
txn,
db_cache: <_>::default(),
@ -93,39 +81,42 @@ impl<'ctx> SearchContext<'ctx> {
term_interner: <_>::default(),
phrase_docids: <_>::default(),
restricted_fids: None,
})
}
}
pub fn attributes_to_search_on(
&mut self,
attributes_to_search_on: &'ctx [String],
) -> Result<()> {
let user_defined_searchable = self.index.user_defined_searchable_fields(self.txn)?;
let searchable_fields_weights = self.index.searchable_fields_and_weights(self.txn)?;
pub fn searchable_attributes(&mut self, searchable_attributes: &'ctx [String]) -> Result<()> {
let fids_map = self.index.fields_ids_map(self.txn)?;
let searchable_names = self.index.searchable_fields(self.txn)?;
let exact_attributes_ids = self.index.exact_attributes_ids(self.txn)?;
let mut wildcard = false;
let mut restricted_fids = RestrictedFids::default();
for field_name in attributes_to_search_on {
let mut contains_wildcard = false;
for field_name in searchable_attributes {
if field_name == "*" {
wildcard = true;
// we cannot early exit as we want to returns error in case of unknown fields
contains_wildcard = true;
continue;
}
let searchable_weight =
searchable_fields_weights.iter().find(|(name, _, _)| name == field_name);
let (fid, weight) = match searchable_weight {
let searchable_contains_name =
searchable_names.as_ref().map(|sn| sn.iter().any(|name| name == field_name));
let fid = match (fids_map.id(field_name), searchable_contains_name) {
// The Field id exist and the field is searchable
Some((_name, fid, weight)) => (*fid, *weight),
// The field is not searchable but the user didn't define any searchable attributes
None if user_defined_searchable.is_none() => continue,
(Some(fid), Some(true)) | (Some(fid), None) => fid,
// The field is searchable but the Field id doesn't exist => Internal Error
(None, Some(true)) => {
return Err(FieldIdMapMissingEntry::FieldName {
field_name: field_name.to_string(),
process: "search",
}
.into())
}
// The field is not searchable, but the searchableAttributes are set to * => ignore field
(None, None) => continue,
// The field is not searchable => User error
None => {
let (valid_fields, hidden_fields) = self.index.remove_hidden_fields(
self.txn,
searchable_fields_weights.iter().map(|(name, _, _)| name),
)?;
(_fid, Some(false)) => {
let (valid_fields, hidden_fields) = match searchable_names {
Some(sn) => self.index.remove_hidden_fields(self.txn, sn)?,
None => self.index.remove_hidden_fields(self.txn, fids_map.names())?,
};
let field = field_name.to_string();
return Err(UserError::InvalidSearchableAttribute {
@ -138,17 +129,13 @@ impl<'ctx> SearchContext<'ctx> {
};
if exact_attributes_ids.contains(&fid) {
restricted_fids.exact.push((fid, weight));
restricted_fids.exact.push(fid);
} else {
restricted_fids.tolerant.push((fid, weight));
restricted_fids.tolerant.push(fid);
};
}
if wildcard {
self.restricted_fids = None;
} else {
self.restricted_fids = Some(restricted_fids);
}
self.restricted_fids = (!contains_wildcard).then_some(restricted_fids);
Ok(())
}
@ -171,13 +158,13 @@ impl Word {
#[derive(Debug, Clone, Default)]
pub struct RestrictedFids {
pub tolerant: Vec<(FieldId, Weight)>,
pub exact: Vec<(FieldId, Weight)>,
pub tolerant: Vec<FieldId>,
pub exact: Vec<FieldId>,
}
impl RestrictedFids {
pub fn contains(&self, fid: &FieldId) -> bool {
self.tolerant.iter().any(|(id, _)| id == fid) || self.exact.iter().any(|(id, _)| id == fid)
self.tolerant.contains(fid) || self.exact.contains(fid)
}
}
@ -197,11 +184,6 @@ fn resolve_maximally_reduced_query_graph(
.iter()
.flat_map(|x| x.iter())
.collect(),
TermsMatchingStrategy::Frequency => query_graph
.removal_order_for_terms_matching_strategy_frequency(ctx)?
.iter()
.flat_map(|x| x.iter())
.collect(),
TermsMatchingStrategy::All => vec![],
};
graph.remove_nodes_keep_edges(&nodes_to_remove);
@ -548,15 +530,11 @@ fn resolve_sort_criteria<'ctx, Query: RankingRuleQueryTrait>(
Ok(())
}
pub fn filtered_universe(
index: &Index,
txn: &RoTxn<'_>,
filters: &Option<Filter>,
) -> Result<RoaringBitmap> {
pub fn filtered_universe(ctx: &SearchContext, filters: &Option<Filter>) -> Result<RoaringBitmap> {
Ok(if let Some(filters) = filters {
filters.evaluate(txn, index)?
filters.evaluate(ctx.txn, ctx.index)?
} else {
index.documents_ids(txn)?
ctx.index.documents_ids(ctx.txn)?
})
}

View File

@ -1,9 +1,8 @@
use std::cmp::{Ordering, Reverse};
use std::cmp::Ordering;
use std::collections::BTreeMap;
use std::hash::{Hash, Hasher};
use fxhash::{FxHashMap, FxHasher};
use roaring::RoaringBitmap;
use super::interner::{FixedSizeInterner, Interned};
use super::query_term::{
@ -12,7 +11,6 @@ use super::query_term::{
use super::small_bitmap::SmallBitmap;
use super::SearchContext;
use crate::search::new::interner::Interner;
use crate::search::new::resolve_query_graph::compute_query_term_subset_docids;
use crate::Result;
/// A node of the [`QueryGraph`].
@ -292,49 +290,6 @@ impl QueryGraph {
}
}
pub fn removal_order_for_terms_matching_strategy_frequency(
&self,
ctx: &mut SearchContext,
) -> Result<Vec<SmallBitmap<QueryNode>>> {
// lookup frequency for each term
let mut term_with_frequency: Vec<(u8, u64)> = {
let mut term_docids: BTreeMap<u8, RoaringBitmap> = Default::default();
for (_, node) in self.nodes.iter() {
match &node.data {
QueryNodeData::Term(t) => {
let docids = compute_query_term_subset_docids(ctx, &t.term_subset)?;
for id in t.term_ids.clone() {
term_docids
.entry(id)
.and_modify(|curr| *curr |= &docids)
.or_insert_with(|| docids.clone());
}
}
QueryNodeData::Deleted | QueryNodeData::Start | QueryNodeData::End => continue,
}
}
term_docids
.into_iter()
.map(|(idx, docids)| match docids.len() {
0 => (idx, u64::max_value()),
frequency => (idx, frequency),
})
.collect()
};
term_with_frequency.sort_by_key(|(_, frequency)| Reverse(*frequency));
let mut term_weight = BTreeMap::new();
let mut weight: u16 = 1;
let mut peekable = term_with_frequency.into_iter().peekable();
while let Some((idx, frequency)) = peekable.next() {
term_weight.insert(idx, weight);
if peekable.peek().map_or(false, |(_, f)| frequency != *f) {
weight += 1;
}
}
let cost_of_term_idx = move |term_idx: u8| *term_weight.get(&term_idx).unwrap();
Ok(self.removal_order_for_terms_matching_strategy(ctx, cost_of_term_idx))
}
pub fn removal_order_for_terms_matching_strategy_last(
&self,
ctx: &SearchContext,
@ -360,19 +315,10 @@ impl QueryGraph {
if first_term_idx >= last_term_idx {
return vec![];
}
let cost_of_term_idx = |term_idx: u8| {
let rank = 1 + last_term_idx - term_idx;
rank as u16
};
self.removal_order_for_terms_matching_strategy(ctx, cost_of_term_idx)
}
pub fn removal_order_for_terms_matching_strategy(
&self,
ctx: &SearchContext,
order: impl Fn(u8) -> u16,
) -> Vec<SmallBitmap<QueryNode>> {
let mut nodes_to_remove = BTreeMap::<u16, SmallBitmap<QueryNode>>::new();
let mut at_least_one_mandatory_term = false;
for (node_id, node) in self.nodes.iter() {
@ -383,7 +329,7 @@ impl QueryGraph {
}
let mut cost = 0;
for id in t.term_ids.clone() {
cost = std::cmp::max(cost, order(id));
cost = std::cmp::max(cost, cost_of_term_idx(id));
}
nodes_to_remove
.entry(cost)

View File

@ -119,7 +119,7 @@ pub fn located_query_terms_from_tokens(
if let Some(located_query_term) = phrase.build(ctx) {
// as we are evaluating a negative operator we put the phrase
// in the negative one *but* we don't reset the negative operator
// as we are immediately starting a new negative phrase.
// as we are immediatly starting a new negative phrase.
if negative_phrase {
negative_phrases.push(located_query_term);
} else {
@ -366,7 +366,7 @@ mod tests {
let tokens = tokenizer.tokenize(".");
let index = temp_index_with_documents();
let rtxn = index.read_txn()?;
let mut ctx = SearchContext::new(&index, &rtxn)?;
let mut ctx = SearchContext::new(&index, &rtxn);
// panics with `attempt to add with overflow` before <https://github.com/meilisearch/meilisearch/issues/3785>
let ExtractedTokens { query_terms, .. } =
located_query_terms_from_tokens(&mut ctx, tokens, None)?;

View File

@ -7,12 +7,12 @@ use crate::search::new::interner::{DedupInterner, Interned};
use crate::search::new::query_term::LocatedQueryTermSubset;
use crate::search::new::resolve_query_graph::compute_query_term_subset_docids_within_field_id;
use crate::search::new::SearchContext;
use crate::{FieldId, InternalError, Result};
use crate::Result;
#[derive(Clone, PartialEq, Eq, Hash)]
pub struct FidCondition {
term: LocatedQueryTermSubset,
fid: Option<FieldId>,
fid: u16,
}
pub enum FidGraph {}
@ -26,15 +26,13 @@ impl RankingRuleGraphTrait for FidGraph {
universe: &RoaringBitmap,
) -> Result<ComputedCondition> {
let FidCondition { term, .. } = condition;
let docids = if let Some(fid) = condition.fid {
// maybe compute_query_term_subset_docids_within_field_id should accept a universe as argument
let docids =
compute_query_term_subset_docids_within_field_id(ctx, &term.term_subset, fid)?;
docids & universe
} else {
RoaringBitmap::new()
};
// maybe compute_query_term_subset_docids_within_field_id should accept a universe as argument
let mut docids = compute_query_term_subset_docids_within_field_id(
ctx,
&term.term_subset,
condition.fid,
)?;
docids &= universe;
Ok(ComputedCondition {
docids,
@ -70,29 +68,34 @@ impl RankingRuleGraphTrait for FidGraph {
all_fields.extend(fields);
}
let weights_map = ctx.index.fieldids_weights_map(ctx.txn)?;
let mut edges = vec![];
for fid in all_fields.iter().copied() {
let weight = weights_map
.weight(fid)
.ok_or(InternalError::FieldidsWeightsMapMissingEntry { key: fid })?;
edges.push((
weight as u32 * term.term_ids.len() as u32,
conditions_interner.insert(FidCondition { term: term.clone(), fid: Some(fid) }),
fid as u32 * term.term_ids.len() as u32,
conditions_interner.insert(FidCondition { term: term.clone(), fid }),
));
}
// always lookup the max_fid if we don't already and add an artificial condition for max scoring
let max_weight: Option<u16> = weights_map.max_weight();
let max_fid: Option<u16> = {
if let Some(max_fid) = ctx
.index
.searchable_fields_ids(ctx.txn)?
.map(|field_ids| field_ids.into_iter().max())
{
max_fid
} else {
ctx.index.fields_ids_map(ctx.txn)?.ids().max()
}
};
if let Some(max_weight) = max_weight {
if !all_fields.contains(&max_weight) {
if let Some(max_fid) = max_fid {
if !all_fields.contains(&max_fid) {
edges.push((
max_weight as u32 * term.term_ids.len() as u32, // TODO improve the fid score i.e. fid^10.
max_fid as u32 * term.term_ids.len() as u32, // TODO improve the fid score i.e. fid^10.
conditions_interner.insert(FidCondition {
term: term.clone(), // TODO remove this ugly clone
fid: None,
fid: max_fid,
}),
));
}

View File

@ -1,5 +1,5 @@
use crate::index::tests::TempIndex;
use crate::{db_snap, Criterion, Search, SearchResult, TermsMatchingStrategy};
use crate::{Criterion, Search, SearchResult, TermsMatchingStrategy};
fn create_index() -> TempIndex {
let index = TempIndex::new();
@ -131,19 +131,6 @@ fn test_attribute_fid_simple() {
#[test]
fn test_attribute_fid_ngrams() {
let index = create_index();
db_snap!(index, fields_ids_map, @r###"
0 id |
1 title |
2 description |
3 plot |
"###);
db_snap!(index, searchable_fields, @r###"["title", "description", "plot"]"###);
db_snap!(index, fieldids_weights_map, @r###"
fid weight
1 0 |
2 1 |
3 2 |
"###);
let txn = index.read_txn().unwrap();

View File

@ -1,244 +0,0 @@
---
source: milli/src/search/new/tests/attribute_fid.rs
expression: "format!(\"{document_ids_scores:#?}\")"
---
[
(
2,
[
Fid(
Rank {
rank: 19,
max_rank: 19,
},
),
Position(
Rank {
rank: 91,
max_rank: 91,
},
),
],
),
(
6,
[
Fid(
Rank {
rank: 15,
max_rank: 19,
},
),
Position(
Rank {
rank: 81,
max_rank: 91,
},
),
],
),
(
5,
[
Fid(
Rank {
rank: 14,
max_rank: 19,
},
),
Position(
Rank {
rank: 79,
max_rank: 91,
},
),
],
),
(
4,
[
Fid(
Rank {
rank: 13,
max_rank: 19,
},
),
Position(
Rank {
rank: 77,
max_rank: 91,
},
),
],
),
(
3,
[
Fid(
Rank {
rank: 12,
max_rank: 19,
},
),
Position(
Rank {
rank: 83,
max_rank: 91,
},
),
],
),
(
9,
[
Fid(
Rank {
rank: 11,
max_rank: 19,
},
),
Position(
Rank {
rank: 75,
max_rank: 91,
},
),
],
),
(
8,
[
Fid(
Rank {
rank: 10,
max_rank: 19,
},
),
Position(
Rank {
rank: 79,
max_rank: 91,
},
),
],
),
(
7,
[
Fid(
Rank {
rank: 10,
max_rank: 19,
},
),
Position(
Rank {
rank: 73,
max_rank: 91,
},
),
],
),
(
11,
[
Fid(
Rank {
rank: 7,
max_rank: 19,
},
),
Position(
Rank {
rank: 77,
max_rank: 91,
},
),
],
),
(
10,
[
Fid(
Rank {
rank: 6,
max_rank: 19,
},
),
Position(
Rank {
rank: 81,
max_rank: 91,
},
),
],
),
(
13,
[
Fid(
Rank {
rank: 6,
max_rank: 19,
},
),
Position(
Rank {
rank: 81,
max_rank: 91,
},
),
],
),
(
12,
[
Fid(
Rank {
rank: 6,
max_rank: 19,
},
),
Position(
Rank {
rank: 78,
max_rank: 91,
},
),
],
),
(
14,
[
Fid(
Rank {
rank: 5,
max_rank: 19,
},
),
Position(
Rank {
rank: 75,
max_rank: 91,
},
),
],
),
(
0,
[
Fid(
Rank {
rank: 1,
max_rank: 19,
},
),
Position(
Rank {
rank: 91,
max_rank: 91,
},
),
],
),
]

View File

@ -49,8 +49,19 @@ impl<Q: RankingRuleQueryTrait> VectorSort<Q> {
ctx: &mut SearchContext<'_>,
vector_candidates: &RoaringBitmap,
) -> Result<()> {
let readers: std::result::Result<Vec<_>, _> =
ctx.index.arroy_readers(ctx.txn, self.embedder_index).collect();
let writer_index = (self.embedder_index as u16) << 8;
let readers: std::result::Result<Vec<_>, _> = (0..=u8::MAX)
.map_while(|k| {
arroy::Reader::open(ctx.txn, writer_index | (k as u16), ctx.index.vector_arroy)
.map(Some)
.or_else(|e| match e {
arroy::Error::MissingMetadata => Ok(None),
e => Err(e),
})
.transpose()
})
.collect();
let readers = readers?;
let target = &self.target;

View File

@ -1,111 +0,0 @@
use std::sync::Arc;
use ordered_float::OrderedFloat;
use roaring::RoaringBitmap;
use crate::score_details::{self, ScoreDetails};
use crate::vector::Embedder;
use crate::{filtered_universe, DocumentId, Filter, Index, Result, SearchResult};
pub struct Similar<'a> {
id: DocumentId,
// this should be linked to the String in the query
filter: Option<Filter<'a>>,
offset: usize,
limit: usize,
rtxn: &'a heed::RoTxn<'a>,
index: &'a Index,
embedder_name: String,
embedder: Arc<Embedder>,
}
impl<'a> Similar<'a> {
pub fn new(
id: DocumentId,
offset: usize,
limit: usize,
index: &'a Index,
rtxn: &'a heed::RoTxn<'a>,
embedder_name: String,
embedder: Arc<Embedder>,
) -> Self {
Self { id, filter: None, offset, limit, rtxn, index, embedder_name, embedder }
}
pub fn filter(&mut self, filter: Filter<'a>) -> &mut Self {
self.filter = Some(filter);
self
}
pub fn execute(&self) -> Result<SearchResult> {
let universe = filtered_universe(self.index, self.rtxn, &self.filter)?;
let embedder_index =
self.index
.embedder_category_id
.get(self.rtxn, &self.embedder_name)?
.ok_or_else(|| crate::UserError::InvalidEmbedder(self.embedder_name.to_owned()))?;
let readers: std::result::Result<Vec<_>, _> =
self.index.arroy_readers(self.rtxn, embedder_index).collect();
let readers = readers?;
let mut results = Vec::new();
for reader in readers.iter() {
let nns_by_item = reader.nns_by_item(
self.rtxn,
self.id,
self.limit + self.offset + 1,
None,
Some(&universe),
)?;
if let Some(mut nns_by_item) = nns_by_item {
results.append(&mut nns_by_item);
} else {
break;
}
}
results.sort_unstable_by_key(|(_, distance)| OrderedFloat(*distance));
let mut documents_ids = Vec::with_capacity(self.limit);
let mut document_scores = Vec::with_capacity(self.limit);
// list of documents we've already seen, so that we don't return the same document multiple times.
// initialized to the target document, that we never want to return.
let mut documents_seen = RoaringBitmap::new();
documents_seen.insert(self.id);
for (docid, distance) in results
.into_iter()
// skip documents we've already seen & mark that we saw the current document
.filter(|(docid, _)| documents_seen.insert(*docid))
.skip(self.offset)
// take **after** filter and skip so that we get exactly limit elements if available
.take(self.limit)
{
documents_ids.push(docid);
let score = 1.0 - distance;
let score = self
.embedder
.distribution()
.map(|distribution| distribution.shift(score))
.unwrap_or(score);
let score = ScoreDetails::Vector(score_details::Vector { similarity: Some(score) });
document_scores.push(vec![score]);
}
Ok(SearchResult {
matching_words: Default::default(),
candidates: universe,
documents_ids,
document_scores,
degraded: false,
used_negative_operator: false,
})
}
}

View File

@ -308,25 +308,6 @@ pub fn snap_fields_ids_map(index: &Index) -> String {
}
snap
}
pub fn snap_fieldids_weights_map(index: &Index) -> String {
let rtxn = index.read_txn().unwrap();
let weights_map = index.fieldids_weights_map(&rtxn).unwrap();
let mut snap = String::new();
writeln!(&mut snap, "fid weight").unwrap();
let mut field_ids: Vec<_> = weights_map.ids().collect();
field_ids.sort();
for field_id in field_ids {
let weight = weights_map.weight(field_id).unwrap();
writeln!(&mut snap, "{field_id:<3} {weight:<3} |").unwrap();
}
snap
}
pub fn snap_searchable_fields(index: &Index) -> String {
let rtxn = index.read_txn().unwrap();
let searchable_fields = index.searchable_fields(&rtxn).unwrap();
format!("{searchable_fields:?}")
}
pub fn snap_geo_faceted_documents_ids(index: &Index) -> String {
let rtxn = index.read_txn().unwrap();
let geo_faceted_documents_ids = index.geo_faceted_documents_ids(&rtxn).unwrap();
@ -488,12 +469,6 @@ macro_rules! full_snap_of_db {
($index:ident, fields_ids_map) => {{
$crate::snapshot_tests::snap_fields_ids_map(&$index)
}};
($index:ident, fieldids_weights_map) => {{
$crate::snapshot_tests::snap_fieldids_weights_map(&$index)
}};
($index:ident, searchable_fields) => {{
$crate::snapshot_tests::snap_searchable_fields(&$index)
}};
($index:ident, geo_faceted_documents_ids) => {{
$crate::snapshot_tests::snap_geo_faceted_documents_ids(&$index)
}};

View File

@ -21,6 +21,8 @@ impl<'t, 'i> ClearDocuments<'t, 'i> {
name = "clear_documents"
)]
pub fn execute(self) -> Result<u64> {
puffin::profile_function!();
self.index.set_updated_at(self.wtxn, &OffsetDateTime::now_utc())?;
let Index {
env: _env,

View File

@ -499,7 +499,7 @@ impl FacetsUpdateIncrementalInner {
ModificationResult::Expand | ModificationResult::Reduce { .. }
)
{
// if any modification occurred, insert it in the database.
// if any modification occured, insert it in the database.
self.db.put(txn, &insertion_key.as_ref(), &updated_value)?;
Ok(insertion_key_modification)
} else {

View File

@ -379,7 +379,7 @@ pub(crate) mod test_helpers {
let mut options = heed::EnvOpenOptions::new();
let options = options.map_size(4096 * 4 * 1000 * 100);
let tempdir = tempfile::TempDir::new().unwrap();
let env = unsafe { options.open(tempdir.path()) }.unwrap();
let env = options.open(tempdir.path()).unwrap();
let mut wtxn = env.write_txn().unwrap();
let content = env.create_database(&mut wtxn, None).unwrap();
wtxn.commit().unwrap();

View File

@ -29,6 +29,8 @@ pub fn enrich_documents_batch<R: Read + Seek>(
autogenerate_docids: bool,
reader: DocumentsBatchReader<R>,
) -> Result<StdResult<EnrichedDocumentsBatchReader<R>, UserError>> {
puffin::profile_function!();
let (mut cursor, mut documents_batch_index) = reader.into_cursor_and_fields_index();
let mut external_ids = tempfile::tempfile().map(BufWriter::new).map(grenad::Writer::new)?;

View File

@ -29,6 +29,8 @@ pub fn extract_docid_word_positions<R: io::Read + io::Seek>(
settings_diff: &InnerIndexSettingsDiff,
max_positions_per_attributes: Option<u32>,
) -> Result<(grenad::Reader<BufReader<File>>, ScriptLanguageDocidsMap)> {
puffin::profile_function!();
let max_positions_per_attributes = max_positions_per_attributes
.map_or(MAX_POSITION_PER_ATTRIBUTE, |max| max.min(MAX_POSITION_PER_ATTRIBUTE));
let max_memory = indexer.max_memory_by_thread();
@ -184,7 +186,7 @@ fn searchable_fields_changed(
) -> bool {
let searchable_fields = &settings_diff.new.searchable_fields_ids;
for (field_id, field_bytes) in obkv.iter() {
if searchable_fields.contains(&field_id) {
if searchable_fields.as_ref().map_or(true, |sf| sf.contains(&field_id)) {
let del_add = KvReaderDelAdd::new(field_bytes);
match (del_add.get(DelAdd::Deletion), del_add.get(DelAdd::Addition)) {
// if both fields are None, check the next field.
@ -296,7 +298,7 @@ fn lang_safe_tokens_from_document<'a>(
/// Extract words mapped with their positions of a document.
fn tokens_from_document<'a>(
obkv: &KvReader<FieldId>,
searchable_fields: &[FieldId],
searchable_fields: &Option<Vec<FieldId>>,
tokenizer: &Tokenizer,
max_positions_per_attributes: u32,
del_add: DelAdd,
@ -307,7 +309,7 @@ fn tokens_from_document<'a>(
let mut document_writer = KvWriterU16::new(&mut buffers.obkv_buffer);
for (field_id, field_bytes) in obkv.iter() {
// if field is searchable.
if searchable_fields.as_ref().contains(&field_id) {
if searchable_fields.as_ref().map_or(true, |sf| sf.contains(&field_id)) {
// extract deletion or addition only.
if let Some(field_bytes) = KvReaderDelAdd::new(field_bytes).get(del_add) {
// parse json.

View File

@ -23,6 +23,8 @@ pub fn extract_facet_number_docids<R: io::Read + io::Seek>(
indexer: GrenadParameters,
_settings_diff: &InnerIndexSettingsDiff,
) -> Result<grenad::Reader<BufReader<File>>> {
puffin::profile_function!();
let max_memory = indexer.max_memory_by_thread();
let mut facet_number_docids_sorter = create_sorter(

View File

@ -28,6 +28,8 @@ pub fn extract_facet_string_docids<R: io::Read + io::Seek>(
indexer: GrenadParameters,
_settings_diff: &InnerIndexSettingsDiff,
) -> Result<(grenad::Reader<BufReader<File>>, grenad::Reader<BufReader<File>>)> {
puffin::profile_function!();
let max_memory = indexer.max_memory_by_thread();
let options = NormalizerOption { lossy: true, ..Default::default() };

View File

@ -37,7 +37,7 @@ pub struct ExtractedFacetValues {
/// Extracts the facet values of each faceted field of each document.
///
/// Returns the generated grenad reader containing the docid the fid and the original value as key
/// Returns the generated grenad reader containing the docid the fid and the orginal value as key
/// and the normalized value as value extracted from the given chunk of documents.
/// We need the fid of the geofields to correctly parse them as numbers if they were sent as strings initially.
#[tracing::instrument(level = "trace", skip_all, target = "indexing::extract")]
@ -45,7 +45,10 @@ pub fn extract_fid_docid_facet_values<R: io::Read + io::Seek>(
obkv_documents: grenad::Reader<R>,
indexer: GrenadParameters,
settings_diff: &InnerIndexSettingsDiff,
geo_fields_ids: Option<(FieldId, FieldId)>,
) -> Result<ExtractedFacetValues> {
puffin::profile_function!();
let max_memory = indexer.max_memory_by_thread();
let mut fid_docid_facet_numbers_sorter = create_sorter(
@ -124,18 +127,12 @@ pub fn extract_fid_docid_facet_values<R: io::Read + io::Seek>(
add_exists.insert(document);
}
let del_geo_support = settings_diff
.old
.geo_fields_ids
.map_or(false, |(lat, lng)| field_id == lat || field_id == lng);
let add_geo_support = settings_diff
.new
.geo_fields_ids
.map_or(false, |(lat, lng)| field_id == lat || field_id == lng);
let geo_support =
geo_fields_ids.map_or(false, |(lat, lng)| field_id == lat || field_id == lng);
let del_filterable_values =
del_value.map(|value| extract_facet_values(&value, del_geo_support));
del_value.map(|value| extract_facet_values(&value, geo_support));
let add_filterable_values =
add_value.map(|value| extract_facet_values(&value, add_geo_support));
add_value.map(|value| extract_facet_values(&value, geo_support));
// Those closures are just here to simplify things a bit.
let mut insert_numbers_diff = |del_numbers, add_numbers| {

View File

@ -26,6 +26,8 @@ pub fn extract_fid_word_count_docids<R: io::Read + io::Seek>(
indexer: GrenadParameters,
_settings_diff: &InnerIndexSettingsDiff,
) -> Result<grenad::Reader<BufReader<File>>> {
puffin::profile_function!();
let max_memory = indexer.max_memory_by_thread();
let mut fid_word_count_docids_sorter = create_sorter(

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