#community-help

Increasing Server Startup Speed Through Parallelization

TLDR Robert was experiencing long server startup times due to single-threaded data loading. Jason and Kishore Nallan suggested increasing parallelization by adjusting load settings and distributing data across multiple collections.

14mo

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Oct 20, 2022 (14 months ago)

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Robert

10:14 PM

Any chance of server startup ever being multi-threaded? It feels so painful to watch 250GB of data being loaded in with just a single core at 100% and taking 15+ hours.

10:34

Robert

10:34 PM

Looks like the very long duration is because it hasn't had a chance to do a snapshot yet. The instance I have that has snapshotted before takes about 3 hours to load instead 15+ hours.

10:35

Robert

10:35 PM

Even the snapshot load is still single-threaded, would be amazing if it could use more threads, but I can understand how that might be... tricky.

Oct 21, 2022 (14 months ago)

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Jason

12:32 AM

You can configure how many documents and collections are loaded in parallel using: --num-collections-parallel-load and --num-documents-parallel-load

Documented here: https://typesense.org/docs/0.23.1/api/server-configuration.html#using-command-line-arguments

12:33

Jason

12:33 AM

You could also improve parallelization (for both indexing and searching) if you’re able to shard the data across multiple collections using some attribute as the shard key, if possible.

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Kishore Nallan

12:37 AM

You can shard your data across N collections to parallelize things.

Robert

12:38 AM

Only have a single collection. I'm running with --num-documents-parallel-load=10000

12:38

Robert

12:38 AM

Thanks for the tip about going across multiple collections, I'll look into that, thanks!

Kishore Nallan

12:40 AM

There are limits to how much things can be parallelized within a single collection because there are hot spots and locks of various kinds. Of course there is potential for much work to be done to improve, but for these large datasets sharding is the most reliable way to scale out because you can independently index N collections without inter dependency.

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