New index building APIs for simpler and flexible usage
维护者通常 5 天内回复
还没有人认领这个 Issue。
评估
调研方向
首先查看现有的 Vamana::build API 以及 issue 中描述的 SQDataset::compress 流程。此变更应提供接受未压缩数据和数据集类型的索引构建入口,支持回退到未压缩数据,并允许压缩和图构建独立进行。
由索引模型根据 Issue 内容生成。
描述
In SVS, we separate the concept of dataset and index. This allows an index to accept different datasets, such as FP32, Scalar Quantization (SQDataset), LVQ, and LeanVec.
Currently, using SQDataset as an example, users must call compress to get a SQDataset, then pass it to the index. However, most use cases don't care about the dataset itself - this two-step process is often unnecessary for most users. Additionally, this approach makes runtime fallback impossible to implement in SVS, as each dataset (i.e., type) is determined at compile time.
auto loaded =
svs::VectorDataLoader<float>(std::filesystem::path(SVS_DATA_DIR) / "data_f32.svs").load();
auto data =
svs::scalar::SQDataset<std::int8_t>::compress(loaded, threadpool); // SQDataset is determined at compile time
auto parameters = svs::index::vamana::VamanaBuildParameters{};
svs::Vamana index = svs::Vamana::build<float>(
parameters, data, svs::distance::DistanceL2(), num_threads
);
I propose adding index building APIs that directly accept uncompressed data and take the dataset type as a parameter to determine which dataset format to use internally.
auto loaded =
svs::VectorDataLoader<float>(std::filesystem::path(SVS_DATA_DIR) / "data_f32.svs").load();
auto parameters = svs::index::vamana::VamanaBuildParameters{};
svs::Vamana index = svs::Vamana::build<float>(
parameters, data, svs::distance::DistanceL2(), num_threads, svs::SQ8
); // internally, SVS fallbacks to uncompressed data if scalar quantization failed
Another advantage of this is that we could optionally utilize uncompressed data to build the graph rather than compressed data, which typically gives worse quality graphs as compression introduces approximation errors that can degrade the graph structure during construction.
Note that when calling build, we can compress the data and build the graph in parallel, as the two things are independent.
- 主要语言
- C++
- 星标
- 241
- 派生
- 48
- 平均合并
- 4 天 21 小时
- 30 天内合并 PR
- 11
环境准备
- 没有 Dockerfile 或 Docker Compose 文件
- 没有 Pull Request 模板
- 阅读贡献指南
从这里开始
- 先读完整个 Issue,再读项目的贡献指南。
- 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
- Fork 仓库,在一个分支上完成修改。
- 提交 Pull Request,并在描述里引用这个 Issue 编号。
intel/ScalableVectorSearch 的其他 Issue
-
难度 1/5 1 小时以内 新手友好度 88/100
intel/ScalableVectorSearch#356 ·
维护者通常 5 天内回复
-
难度 4/5 3-5 天 新手友好度 42/100
intel/ScalableVectorSearch#469 ·
维护者通常 5 天内回复
-
enhancement
难度 3/5 1-2 天 新手友好度 32/100
intel/ScalableVectorSearch#460 ·
维护者通常 5 天内回复
-
难度 4/5 3-5 天 新手友好度 55/100
intel/ScalableVectorSearch#438 ·
维护者通常 5 天内回复
-
CI: tier the test matrix into PR / main / nightly to cut Actions minutes可能已有人在做 关联的 PR 仍在进行中或已合并。 未关闭
难度 5/5 一周以上 新手友好度 32/100
intel/ScalableVectorSearch#432 · 1 条评论 ·
维护者通常 5 天内回复
查看 intel/ScalableVectorSearch 的全部 Issue
相似的 Issue
-
runtime: lf_f128_mod is documented as fmodq (truncating) but implements floor-based modulo; unused未关闭internal correctness low priority rt_lib
难度 2/5 1-3 小时 新手友好度 72/100
维护者通常 1 天内回复
-
难度 1/5 1 小时以内 新手友好度 87/100
-
PriorityNotificationQueue::wakeUpAll() loses the wake-up for a thread that is not waiting yet可能已有人在做 @matejk 今天认领。 未关闭bug
难度 2/5 1-3 小时 新手友好度 78/100
pocoproject/poco#5674 ·
维护者通常 2 天内回复
-
bug docs GUI
难度 2/5 1-3 小时 新手友好度 62/100
sonic-pi-net/sonic-pi#3609 ·
-
bug
难度 2/5 1-3 小时 新手友好度 70/100
SanderMertens/flecs#2395 ·
维护者通常 1 天内回复