parent_asin stringlengths 10 10 | value listlengths 4.15k 4.15k | main_category stringclasses 40 values | title stringlengths 0 1.47k | average_rating float64 1 5 | rating_number float64 1 451k ⌀ | description stringlengths 2 90k ⌀ | price float64 0 16.5k ⌀ | categories stringlengths 9 149 ⌀ | image_url stringlengths 51 87 ⌀ |
|---|---|---|---|---|---|---|---|---|---|
0448013045 | [
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... | Automotive | KRSEC FIRELIZARD Bike Headset Top Cap Light CNC Aluminum Roadbike Creative Personality capz MTB Stem Caps with Screws (Style 5) | 4.6 | 4 | null | null | null | |
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0.01322085317... | Books | The Best of Chef at Home: Essential Recipes for Today's Kitchen | 4.6 | 99 | About the Author Food Network star Chef Michael Smith has been cooking professionally for over twenty years. An honours graduate of the prestigious Culinary Institute of America in New York, Chef Michael's contagious love of food has earned him friends and admirers worldwide. There's no doubt that Chef Michael Smith is passionate about food. You'll catch his enthusiasm just by watching his hit Food Network television shows Chef at Home and Chef Abroad . Now he's back with the much-awaited follow-up to his first book, Chef at Home , which has sold over 28,000 copies. The Best of Chef at Home is a collection of the recipes that Michael is most passionate about, the everyday comfort food his own family craves. Both simple and easy to adapt, the recipes reflect Michael's belief that making great food is about relaxing, enjoying the process, and losing yourself in the moment. It includes everything from quick recipes for weekday meals, like macaroni and cheese, to fancier fare for entertaining guests, like short ribs braised in red wine. Michael's laid-back approach encourages creativity in the kitchen, with suggestions for altering and adjusting each recipe until it is truly your own. Why not try adding pine nuts to your chocolate chip cookies? Or curry powder to a classic chicken stew? Once you know the basics, you can create flavourful food for your family and friends with a personal touch. Try your hand at Chef Michael Smith's most popular crowd-pleasers: Chicken Noodle Soup Brined Holiday Turkey with Herb Gravy The Perfect Burger Classic Chicken Stew Old-Fashioned Apple Pie Chocolate Chip Cookies | 22.72 | Books Cookbooks, Food & Wine | null |
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0739477889 | [0.3437846899032593,0.08253540098667145,0.0,6.142208803794347e-6,0.3535533845424652,0.0,0.0,0.0,0.0,(...TRUNCATED) | Books | By the Rivers of Babylon | 4.4 | 22 | Hardcover 422pgs. | null | Books Foreign Language Books German | |
B00BDDSG2W | [0.3535533845424652,2.164890316292761e-17,0.0,5.849722697348625e-7,0.3535533845424652,0.0,0.00008663(...TRUNCATED) | Amazon Home | Member's Mark Simple Tie Drum Liner - 55 gal - 80 Count (4 Pack) | 5 | 3 | "Member's Mark Simple Tie Drum Liners - 55 gal. - 80 ct. (4 pack)More leak and tear resistant than e(...TRUNCATED) | 156 | Health & Household Household Supplies Paper & Plastic Trash, Compost & Lawn Bags Trash Bags | |
B01ETSX8ZC | [0.3535533845424652,2.164890316292761e-17,0.0,8.774583761805843e-7,0.3535533845424652,0.0,4.71500970(...TRUNCATED) | Amazon Home | UnBra Gray Auto Detailing Leather Upholstery Brush | 5 | 4 | A great all around brush for cleaning | 8.49 | Automotive Car Care Tools & Equipment Brushes & Dusters | |
B09HZWD17D | [0.34675994515419006,0.06897484511137009,0.0,0.000021059000573586673,0.3535533845424652,0.0,0.0,0.0,(...TRUNCATED) | AMAZON FASHION | "50pcs Christmas Disposable Face_Mask for Women Adults Men, 3ply Xmas Printed Protective Safety Mout(...TRUNCATED) | 4.5 | 73 | " Ear Loop closure 【3 PLY Non-Woven Design】The Christmas face_mask is made of high-quality non-w(...TRUNCATED) | null | "Tools & Home Improvement Safety & Security Personal Protective Equipment Masks & Respirators Dispos(...TRUNCATED) | |
0989542157 | [0.34027931094169617,0.09596869349479675,0.0,4.094805717613781e-6,0.3535533845424652,0.0,0.0,0.0,0.0(...TRUNCATED) | Books | The Girl Who Watched Over Dreams | 4.3 | 15 | " What if a person could live in their dreams? What if the power of imagination could erase the ineq(...TRUNCATED) | null | Books Literature & Fiction Genre Fiction | |
1690812974 | [0.351102739572525,0.0415557436645031,0.0,8.482097655360121e-6,0.3535533845424652,0.0,7.769491276121(...TRUNCATED) | Books | "Secrets of the Carousel: A Story of Strong Courageous Friends Pursuing Their Texas Roots (The Grist(...TRUNCATED) | 4.7 | 30 | " Juggling the challenges of a husband with Alzheimer’s disease and the responsibilities of a busy(...TRUNCATED) | 13.99 | Books Mystery, Thriller & Suspense Mystery | null |
End of preview. Expand
in Data Studio
Vector Search Benchmarks
This repo contains datasets for benchmarking vector search performance, to help Superlinked prioritize integration partners. For performing actual benchmarking on this dataset, see the github repository README.
Overview
We reviewed a number of publicly available datasets and noted 3 core problems + here is how this dataset fixes them:
| Problems of other vector search benchmarks | How this dataset solves it |
|---|---|
| Not enough metadata of various types makes it hard to test filter performance | 3 number, 1 categorical, 3 text, 1 image column |
| Vectors too small, while SOTA models usually output 2k+ even 4k+ dims | 4154 dims |
| Dataset too small, especially if larger vectors are used | 100k, 1M and 10M item variants, all sampled from the large dataset |
Available Datasets
Product data
The data_dirs contain parquet files with the metadata and vectors.
| Dataset | Records | # Files | Size |
|---|---|---|---|
| benchmark_10k | 10,000 | 100 | ~230 MB |
| benchmark_100k | 100,000 | 100 | ~2.3 GB |
| benchmark_1M | 1,000,000 | 100 | ~23 GB |
| benchmark_10M | 10,534,536 | 1000 | ~240 GB |
The structure of the files is the same throughout:
Schema([('parent_asin', String), # the id
('main_category', String),
('title', String),
('average_rating', Float64),
('rating_number', Float64),
('description', String),
('price', Float64),
('categories', String),
('image_url', String)])
('value', List(Float64)), # the vectors
Data Access
The product metadata and vectors are available using HF Datasets.
from datasets import load_dataset
benchmark_10k = load_dataset("superlinked/external-benchmarking", data_dir="benchmark-10k")
benchmark_100k = load_dataset("superlinked/external-benchmarking", data_dir="benchmark-100k")
benchmark_1M = load_dataset("superlinked/external-benchmarking", data_dir="benchmark-1M")
benchmark_10M = load_dataset("superlinked/external-benchmarking", data_dir="benchmark-10M")
Dataset Production
Source Data
- Origin: Amazon Reviews 2023 dataset
- Categories:
["Books", "Automotive", "Tools and Home Improvement", "All Beauty", "Electronics", "Software", "Health and Household"]
Embeddings
The embeddings are created via a superlinked config. The resulting 4154 dim vector contains:
- 1 categorical,
- 3 number,
- 3 text (
Qwen/Qwen3-Embedding-0.6B), - and 1 image (
laion/CLIP-ViT-H-14-laion2B-s32B-b79K)
embeddings concatenated.
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