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Fast and Easy Vector Ingestion from Python DataFrames

Blog post from SingleStore

Post Details
Company
Date Published
Author
Arnaud Comet
Word Count
373
Company Posts That Month
7
Language
English
Hacker News Points
-
Post removed?
No
Summary

To ingest embeddings from Pandas DataFrames into SingleStoreDB using Python, you can convert the array containing the vector embedding into a packed byte string using numpy. This approach offers speed and simplicity when loading your embeddings as vectors into SingleStoreDB. To get started, create a connection to SingleStoreDB or use a SingleStore notebook, select the database you want to access, install necessary libraries, and get a sample dataset from the 2022 Beijing Winter Olympics that includes text chunks and their embeddings. Then, create a simple table using SQL and load your DataFrame into the SQL table using the `to_sql` method. Note that this approach assumes the data is in a form of array; if not, additional conversion code may be required. The pandas documentation provides more information about options available through the `to_sql` method.

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