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Optimum Cluster for 1M Documents with OpenAI Embedding

TLDR Denny inquired about the ideal cluster configuration for handling 1M documents with openAI embedding. Jason recommended a specific configuration, explained record size calculation, and clarified embedding generation speed factors and the conditions that trigger openAI.

1mo

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Sep 01, 2023 (1 month ago)

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Denny

12:37 AM

Hi - If I have about 1M documents (using embedding with openAI), what cluster should I be using? Approx 2 request per second or ~160k per day.

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Jason

12:38 AM

The vector search section under here gives you a formula for calculating RAM usage: https://typesense.org/docs/guide/system-requirements.html#choosing-ram

12:41

Jason

12:41 AM

Based on that I would recommend this config: https://cloud.typesense.org/pricing?memory=16_gb&vcpu=4_vcpus&gpu=no&high_perf_disk=no&typesense_server_version=0.25.0&ha=no&sdn=off&regions=ohio

Denny

12:43 AM

thanks for checking!

01:17

Denny

01:17 AM

how do i check the size of each record?

Jason

01:18 AM

For keyword search: https://typesense.helpscoutdocs.com/article/161-how-do-i-calculate-average-record-size

For vector search, it's just number of dimensions * 7 bytes

Denny

01:33 AM

Will increasing the size of my cluster make embedding generation faster?

Jason

02:49 AM

If you’re using OpenAI, embedding generation speed is completely dependent on OpenAI api response times, which I’ve seen take a second or two for each api call.

If you’re using a built-in model, then enabling GPU Acceleration will speed up the embedding generation process: https://typesense.helpscoutdocs.com/article/174-gpu-acceleration

Denny

02:57 AM

Ah I see… I’ve noticed the syncing is a lot slower due to this.

02:57

Denny

02:57 AM

When I update a document, using upsert, will it trigger OpenAI?

Jason

02:58 AM

Only if the value for the embed.from fields specified in the schema change

02:59

Jason

02:59 AM

Btw, you want to make sure you use the import endpoint with as many as 1K documents per API call, so the call to openai is also a bulk embedding call

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