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  • chapmanjacobd · 1 ✖

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  • Filter table by a large bunch of ids · 1 ✖

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  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions issue performed_via_github_app
1592047502 https://github.com/simonw/sqlite-utils/issues/555#issuecomment-1592047502 https://api.github.com/repos/simonw/sqlite-utils/issues/555 IC_kwDOCGYnMM5e5LeO chapmanjacobd 7908073 2023-06-14T22:00:10Z 2023-06-14T22:01:57Z CONTRIBUTOR

You may want to try doing a performance comparison between this and just selecting all the ids with few constraints and then doing the filtering within python.

That might seem like a lazy-programmer, inefficient way but queries with large resultsets are a different profile than what databases like SQLITE are designed for. That is not to say that SQLITE is slow or that python is always faster but when you start reading >20% of an index there is an equilibrium that is reached. Especially when adding in writing extra temp tables and stuff to memory/disk. And especially given the NOT IN style of query...

You may also try chunking like this:

```py def chunks(lst, n) -> Generator: for i in range(0, len(lst), n): yield lst[i : i + n]

SQLITE_PARAM_LIMIT = 32765

data = [] chunked = chunks(video_ids, consts.SQLITE_PARAM_LIMIT) for ids in chunked: data.expand( list( db.query( f"""SELECT * from videos WHERE id in (""" + ",".join(["?"] * len(ids)) + ")", (*ids,), ) ) ) ```

but that actually won't work with your NOT IN requirements. You need to query the full resultset to check any row.

Since you are doing stuff with files/videos in SQLITE you might be interested in my side project: https://github.com/chapmanjacobd/library

 
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 Filter table by a large bunch of ids 1733198948  

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