issue_comments: 1592047502
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
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| https://github.com/simonw/sqlite-utils/issues/555#issuecomment-1592047502 | https://api.github.com/repos/simonw/sqlite-utils/issues/555 | 1592047502 | IC_kwDOCGYnMM5e5LeO | 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 | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | 1733198948 |