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[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
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li
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determining if a polygon intersects with a rectangle
|
[
"articles",
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] | 1,500 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ol > li:nth-of-type(2)
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li
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ascertaining if a point lies within a polygon.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,501 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > figure:nth-of-type(3) > figcaption > p
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p
|
Geometry Computation Testing
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,502 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(6)
|
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p
|
While we have a geo crate (a Rust library) that provides APIs for these computations, we dug in deeper to understand the underlying algorithms and verify their accuracy.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,503 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(6)
|
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p
|
This lead us to conduct extensive testing and visualization to determine correctness.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,504 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(6)
|
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p
|
In addition to assessing the current crate, we also discovered that there are multiple algorithms available for these computations.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,505 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(6)
|
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p
|
We invested time in exploring different approaches, such as winding windows and ray casting, to grasp their distinctions, and pave the way for future improvements.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,506 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
|
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p
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Through this process, I enjoyed honing my ability to swiftly grasp unfamiliar concepts.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,507 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
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p
|
In addition, I needed to develop analytical strategies to dissect and draw meaningful conclusions from them.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,508 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
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p
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This experience has been invaluable in expanding my problem-solving toolkit.
|
[
"articles",
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[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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2.
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[
"articles",
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[
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"Technical Challenges"
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/articles/geo-polygon-filter-gsoc/
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
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Proto and JSON format design
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,511 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(9)
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p
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Considerable effort was devoted to designing the ProtoBuf and JSON interfaces for this new feature.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,512 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(9)
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p
|
This component is directly exposed to users, requiring a consistent and user-friendly interface, which in turns help drive a a positive user experience and less code modifications in the future.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,513 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
|
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p
|
Initially, we contemplated aligning our interface with the GeoJSON specification, given its prominence as a standard for many geo-related APIs.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,514 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
|
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p
|
However, we soon realized that the way GeoJSON defines geometries significantly differs from our current JSON and ProtoBuf coordinate definitions for our point radius and rectangular filter.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,515 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
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p
|
As a result, we prioritized API-level consistency and user experience, opting to align the new polygon definition with all our existing definitions.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,516 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(11)
|
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p
|
In addition, we planned to develop a separate multi-polygon filter in addition to the polygon.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,517 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(11)
|
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p
|
However, after careful consideration, we recognize that, for our use case, polygon filters can achieve the same result as a multi-polygon filter.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,518 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(11)
|
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p
|
This relationship mirrors how we currently handle multiple circles or rectangles.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,519 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(11)
|
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p
|
Consequently, we deemed the multi-polygon filter redundant and would introduce unnecessary complexity to the API.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,520 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
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p
|
Doing this work illustrated to me the challenge of navigating real-world solutions that require striking a balance between adhering to established standards and prioritizing user experience.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,521 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Technical Challenges"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
|
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p
|
It also was key to understanding the wisdom of focusing on developing what’s truly necessary for users, without overextending our efforts.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,522 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h2:nth-of-type(4)
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Outcomes
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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/articles/geo-polygon-filter-gsoc/
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
|
Capability of Deep Dive
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,525 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
|
Navigating unfamiliar code bases, concepts, APIs, and techniques is a common challenge for developers.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,526 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
|
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p
|
Participating in GSoC was akin to me going from the safety of a swimming pool and right into the expanse of the ocean.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,527 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
|
Having my mentor’s support during this transition was invaluable.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,528 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
|
He provided me with numerous opportunities to independently delve into areas I had never explored before.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,529 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
|
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p
|
I have grown into no longer fearing unknown technical areas, whether it’s unfamiliar code, techniques, or concepts in specific domains.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,530 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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I’ve gained confidence in my ability to learn them step by step and use them to create the things I envision.
|
[
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[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
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p
|
Always Put User in Minds
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,533 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
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p
|
Another crucial lesson I learned is the importance of considering the user’s experience and their specific use cases.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,534 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
|
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p
|
While development may sometimes entail iterative processes, every aspect that directly impacts the user must be approached and executed with empathy.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,535 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
|
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p
|
Neglecting this consideration can lead not only to functional errors but also erode the trust of users due to inconsistency and confusion, which then leads to them no longer using my work.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,536 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
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3.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,537 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
|
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p
|
Speak Up and Effectively Communicate
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,538 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
|
Finally, In the course of development, encountering differing opinions is commonplace.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,539 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
|
It’s essential to remain open to others’ ideas, while also possessing the resolve to communicate one’s own perspective clearly.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,540 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Outcomes"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
|
This fosters productive discussions and ultimately elevates the quality of the development process.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,541 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h3
|
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h3
|
Wrap up
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,542 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
|
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p
|
Being selected for Google Summer of Code 2023 and collaborating with Arnaud and the other Qdrant engineers, along with all the other community members, has been a true privilege.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,543 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
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p
|
I’m deeply grateful to those who invested their time and effort in reviewing my code, engaging in discussions about alternatives and design choices, and offering assistance when needed.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,544 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
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p
|
Through these interactions, I’ve experienced firsthand the essence of open source and the culture that encourages collaboration.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,545 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
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p
|
This experience not only allowed me to write Rust code for a real-world product for the first time, but it also opened the door to the amazing world of open source.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,546 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
|
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p
|
Without a doubt, I’m eager to continue growing alongside this community and contribute to new features and enhancements that elevate the product.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,547 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
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p
|
I’ve also become an advocate for Qdrant, introducing this project to numerous coworkers and friends in the tech industry.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,548 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
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p
|
I’m excited to witness new users and contributors emerge from within my own network!
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,549 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(18)
|
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p
|
If you want to try out my work, read the documentation and then, either sign up for a free cloud account or download the Docker image.
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,550 |
[
"Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database - Qdrant",
"Wrap up"
] |
/articles/geo-polygon-filter-gsoc/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(18)
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p
|
I look forward to seeing how people are using my work in their own applications!
|
[
"articles",
"articles/geo-polygon-filter-gsoc"
] | 1,551 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(1) > li:nth-of-type(1)
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[
"articles",
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[
"Binary Quantization - Vector Search, 40x Faster - Qdrant"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(1) > li:nth-of-type(3)
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li
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Articles
|
[
"articles",
"articles/binary-quantization"
] | 1,554 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(1) > li:nth-of-type(2)
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(1) > li:nth-of-type(5)
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Binary Quantization - Vector Search, 40x Faster
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h1
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h1
|
Binary Quantization - Vector Search, 40x Faster
|
[
"articles",
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] | 1,557 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant"
] |
/articles/binary-quantization/
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h4:nth-of-type(1)
|
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h4
|
Optimizing high-dimensional vectors
|
[
"articles",
"articles/binary-quantization"
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[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(1)
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p
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Qdrant is built to handle typical scaling challenges: high throughput, low latency and efficient indexing.
|
[
"articles",
"articles/binary-quantization"
] | 1,559 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(1)
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p
|
Binary quantization (BQ) is our latest attempt to give our customers the edge they need to scale efficiently.
|
[
"articles",
"articles/binary-quantization"
] | 1,560 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(1)
|
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p
|
This feature is particularly excellent for collections with large vector lengths and a large number of points.
|
[
"articles",
"articles/binary-quantization"
] | 1,561 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(2)
|
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p
|
Our results are dramatic: Using BQ will reduce your memory consumption and improve retrieval speeds by up to 40x.
|
[
"articles",
"articles/binary-quantization"
] | 1,562 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
|
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p
|
As is the case with other quantization methods, these benefits come at the cost of recall degradation.
|
[
"articles",
"articles/binary-quantization"
] | 1,563 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
|
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p
|
However, our implementation lets you balance the tradeoff between speed and recall accuracy at time of search, rather than time of index creation.
|
[
"articles",
"articles/binary-quantization"
] | 1,564 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(4)
|
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p
|
The rest of this article will cover:
|
[
"articles",
"articles/binary-quantization"
] | 1,565 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ol:nth-of-type(1) > li:nth-of-type(1)
|
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li
|
The importance of binary quantization
|
[
"articles",
"articles/binary-quantization"
] | 1,566 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ol:nth-of-type(1) > li:nth-of-type(2)
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li
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Basic implementation using our Python client
|
[
"articles",
"articles/binary-quantization"
] | 1,567 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Optimizing high-dimensional vectors"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ol:nth-of-type(1) > li:nth-of-type(3)
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li
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Benchmark analysis and usage recommendations
|
[
"articles",
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[
"Binary Quantization - Vector Search, 40x Faster - Qdrant"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h2:nth-of-type(1)
|
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h2
|
What is Binary Quantization?
|
[
"articles",
"articles/binary-quantization"
] | 1,569 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
|
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p
|
Binary quantization (BQ) converts any vector embedding of floating point numbers into a vector of binary or boolean values.
|
[
"articles",
"articles/binary-quantization"
] | 1,570 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
|
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p
|
This feature is an extension of our past work on scalar quantization where we convert float32 to uint8 and then leverage a specific SIMD CPU instruction to perform fast vector comparison.
|
[
"articles",
"articles/binary-quantization"
] | 1,571 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
|
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p
|
This binarization function is how we convert a range to binary values.
|
[
"articles",
"articles/binary-quantization"
] | 1,572 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
|
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[
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
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/articles/binary-quantization/
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
|
The benefit of reducing the vector embeddings to binary values is that boolean operations are very fast and need significantly less CPU instructions.
|
[
"articles",
"articles/binary-quantization"
] | 1,575 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
|
In exchange for reducing our 32 bit embeddings to 1 bit embeddings we can see up to a 40x retrieval speed up gain!
|
[
"articles",
"articles/binary-quantization"
] | 1,576 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(9)
|
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p
|
One of the reasons vector search still works with such a high compression rate is that these large vectors are over-parameterized for retrieval.
|
[
"articles",
"articles/binary-quantization"
] | 1,577 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(9)
|
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p
|
This is because they are designed for ranking, clustering, and similar use cases, which typically need more information encoded in the vector.
|
[
"articles",
"articles/binary-quantization"
] | 1,578 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
|
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p
|
For example, The 1536 dimension OpenAI embedding is worse than Open Source counterparts of 384 dimension at retrieval and ranking.
|
[
"articles",
"articles/binary-quantization"
] | 1,579 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
|
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p
|
Specifically, it scores 49.25 on the same Embedding Retrieval Benchmark where the Open Source bge-small scores 51.82.
|
[
"articles",
"articles/binary-quantization"
] | 1,580 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
|
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p
|
This 2.57 points difference adds up quite soon.
|
[
"articles",
"articles/binary-quantization"
] | 1,581 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(11)
|
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p
|
Our implementation of quantization achieves a good balance between full, large vectors at ranking time and binary vectors at search and retrieval time.
|
[
"articles",
"articles/binary-quantization"
] | 1,582 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"What is Binary Quantization?"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(11)
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p
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It also has the ability for you to adjust this balance depending on your use case.
|
[
"articles",
"articles/binary-quantization"
] | 1,583 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h2:nth-of-type(2)
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h2
|
Fast Search and Retrieval
|
[
"articles",
"articles/binary-quantization"
] | 1,584 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Fast Search and Retrieval"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
|
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p
|
Unlike product quantization, binary quantization does not rely on reducing the search space for each probe.
|
[
"articles",
"articles/binary-quantization"
] | 1,585 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Fast Search and Retrieval"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
|
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p
|
Instead, we build a binary index that helps us achieve large increases in search speed.
|
[
"articles",
"articles/binary-quantization"
] | 1,586 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Fast Search and Retrieval"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
|
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p
|
HNSW is the approximate nearest neighbor search.
|
[
"articles",
"articles/binary-quantization"
] | 1,587 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Fast Search and Retrieval"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
|
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p
|
This means our accuracy improves up to a point of diminishing returns, as we check the index for more similar candidates.
|
[
"articles",
"articles/binary-quantization"
] | 1,588 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Fast Search and Retrieval"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
|
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p
|
In the context of binary quantization, this is referred to as the oversampling rate.
|
[
"articles",
"articles/binary-quantization"
] | 1,589 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Fast Search and Retrieval"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
|
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p
|
For example, if oversampling=2.0 and the limit=100, then 200 vectors will first be selected using a quantized index.
|
[
"articles",
"articles/binary-quantization"
] | 1,590 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Fast Search and Retrieval"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
|
For those 200 vectors, the full 32 bit vector will be used with their HNSW index to a much more accurate 100 item result set.
|
[
"articles",
"articles/binary-quantization"
] | 1,591 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Fast Search and Retrieval"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
|
As opposed to doing a full HNSW search, we oversample a preliminary search and then only do the full search on this much smaller set of vectors.
|
[
"articles",
"articles/binary-quantization"
] | 1,592 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h2:nth-of-type(3)
|
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h2
|
Improved Storage Efficiency
|
[
"articles",
"articles/binary-quantization"
] | 1,593 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Improved Storage Efficiency"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
|
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p
|
The following diagram shows the binarization function, whereby we reduce 32 bits storage to 1 bit information.
|
[
"articles",
"articles/binary-quantization"
] | 1,594 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Improved Storage Efficiency"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
|
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p
|
Text embeddings can be over 1024 elements of floating point 32 bit numbers.
|
[
"articles",
"articles/binary-quantization"
] | 1,595 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Improved Storage Efficiency"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
|
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p
|
For example, remember that OpenAI embeddings are 1536 element vectors.
|
[
"articles",
"articles/binary-quantization"
] | 1,596 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Improved Storage Efficiency"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
|
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p
|
This means each vector is 6kB for just storing the vector.
|
[
"articles",
"articles/binary-quantization"
] | 1,597 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Improved Storage Efficiency"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(19)
|
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p
|
In addition to storing the vector, we also need to maintain an index for faster search and retrieval.
|
[
"articles",
"articles/binary-quantization"
] | 1,598 |
[
"Binary Quantization - Vector Search, 40x Faster - Qdrant",
"Improved Storage Efficiency"
] |
/articles/binary-quantization/
|
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(19)
|
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0.012503992766141891
] |
p
|
Qdrant’s formula to estimate overall memory consumption is:
|
[
"articles",
"articles/binary-quantization"
] | 1,599 |
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