RoundSparrow
“Finnegans Wake is the greatest guidebook to media study ever fashioned by man.” - Marshall McLuhan, Newsweek Magazine, page 56, February 28, 1966.
I have never done LSD or any other illegal drugs, but I have read FInnegans Wake: www.LazyWake.com
Lemmy tester, “RocketDerp” is my username on GitHub
So perhaps I’ve been over-focused on the quantity of data and back in May 2023 when I started using Lemmy daily, I should have considered that this kind of SQL query could be heavily influenced by statistics update as the table runs background analyze…
There may be 15 minutes where the stats say there with be 400 rows for a LIMIT 10 page listing… and then the stats get updated and it then projects 50 rows instead of 400. And that’s why the servers go into periods of crashing for 15 minutes and then it clears up.
All the JOIN logic just invites the query planner to go into some wild technique that it otherwise might not do based on quantity of data in the tables or even just plain wrong estimates in the first place… which get revised.
several people have confirmed it… I haven’t seen them explain how exactly, but they seem convinced it is causing crashes so they blocked it. Lemmy is practically in the realm of voodoo PostgreSQL at this point. Since April or May it’s been scaling very poorly as data gets added.
who would have predicted that Elon Musk would do all the wild things he did with Twitter. Reddit pissing everyone off in June… pretty odd how audiences are behaving in 2023 towards all this. Oh yha, Threads, that coming on the scene too. 2023 has really been odd for audiences.
The SQL speaks for itself, but I don’t know what’s going on in terms of why people are treating social media platforms like Lemmy, Twitter, Threads, Reddit this year so unusually. This SQL statement kind of thing has been covered in so many books, conferences, etc. It’s like forgotten history now in the era of Elon Musk X and Reddit Apollo times.
I don’t know what to say other than I can try to hire a translator or teacher to explain how this SQL problem is obvious and well understood 13 years ago. I mean, there was a whole “NoSQL movement” because of this kind of thing. But I clearly can’t get people to hear past all the Elon Musk, Threads, Lemmy from Reddit … and I’m left describing it as ‘social hazing’ or whatever is gong on with social media.
Lemmy has like 5 different Rust programming communities, but nobody fixing Lemmy. It’s surreal in 2023 the Elon Musk X days. I think it’s making all of us uncomfortable. The social movement underway.
Ok, so let’s look at recent changes that they have deployed… https://github.com/LemmyNet/lemmy/issues/3886
One of which makes entire tree of comments disappear. Do you see developers fretting over this and fixing it? Or do you see them ignoring the May 27 PostgreSQL JOIN problem.
How did such a bug go out? Do you see Lemmy developers actually using Lemmy to test things and notice these crashes and problems? Do you look at their posting and comment history? Do they actually go login over at Beehaw and Lemmy.world and see just how terrible the code performance is?
If it isn’t hazing, what is it?
It’s as if they build a product only for other people to use… and they don’t notice any of the constant crashes, incredibly slow performance etc - and they act like nobody in the computer industry ever heard of Memcache or Redis to solve performance problems. If it isn’t extreme hazing going on, then what is it?
Here, you can dig into what posted days before the pull request you read:
https://github.com/LemmyNet/lemmy/issues/2877#issuecomment-1685314733
June 4:
joins are better than
inqueries with potentially thousands of inserted IDs.
Given that more than 8 JOIN statements is something PostgreSQL specifically concerns itself with (join_collapse_limit). I hand-edit the query with a single IN clause and the performance problem disappears. 8 full seconds becomes less than 200ms against 5,431,043 posts. And that 200ms is still high, as I was extremely over-reaching with “LIMIT 1000” in case the end-user went wild with blocking lists or some other filtering before reaching the final “LIMIT 10”. When I change it to “LIMIT 20” in the subquery, it drops almost in half to 115ms… still meeting the needs of the outer “LIMIT 10” by double. More of the core query filtering can be put into the IN subquery, as we aren’t dealing with more than 500 length pages (currently limited to 50).
SELECT
"post"."id" AS post_id, "post"."name" AS post_title,
-- "post"."url", "post"."body", "post"."creator_id", "post"."community_id", "post"."removed", "post"."locked", "post"."published", "post"."updated", "post"."deleted", "post"."nsfw", "post"."embed_title", "post"."embed_description", "post"."thumbnail_url",
-- "post"."ap_id", "post"."local", "post"."embed_video_url", "post"."language_id", "post"."featured_community", "post"."featured_local",
"person"."id" AS p_id, "person"."name",
-- "person"."display_name", "person"."avatar", "person"."banned", "person"."published", "person"."updated",
-- "person"."actor_id", "person"."bio", "person"."local", "person"."private_key", "person"."public_key", "person"."last_refreshed_at", "person"."banner", "person"."deleted", "person"."inbox_url", "person"."shared_inbox_url", "person"."matrix_user_id", "person"."admin",
-- "person"."bot_account", "person"."ban_expires",
"person"."instance_id" AS p_inst,
"community"."id" AS c_id, "community"."name" AS community_name,
-- "community"."title", "community"."description", "community"."removed", "community"."published", "community"."updated", "community"."deleted",
-- "community"."nsfw", "community"."actor_id", "community"."local", "community"."private_key", "community"."public_key", "community"."last_refreshed_at", "community"."icon", "community"."banner",
-- "community"."followers_url", "community"."inbox_url", "community"."shared_inbox_url", "community"."hidden", "community"."posting_restricted_to_mods",
"community"."instance_id" AS c_inst,
-- "community"."moderators_url", "community"."featured_url",
("community_person_ban"."id" IS NOT NULL) AS ban,
-- "post_aggregates"."id", "post_aggregates"."post_id", "post_aggregates"."comments", "post_aggregates"."score", "post_aggregates"."upvotes", "post_aggregates"."downvotes", "post_aggregates"."published",
-- "post_aggregates"."newest_comment_time_necro", "post_aggregates"."newest_comment_time", "post_aggregates"."featured_community", "post_aggregates"."featured_local",
--"post_aggregates"."hot_rank", "post_aggregates"."hot_rank_active", "post_aggregates"."community_id", "post_aggregates"."creator_id", "post_aggregates"."controversy_rank",
-- "community_follower"."pending",
("post_saved"."id" IS NOT NULL) AS save,
("post_read"."id" IS NOT NULL) AS read,
("person_block"."id" IS NOT NULL) as block,
"post_like"."score",
coalesce(("post_aggregates"."comments" - "person_post_aggregates"."read_comments"), "post_aggregates"."comments") AS unread
FROM (
((((((((((
(
(
"post_aggregates"
INNER JOIN "person" ON ("post_aggregates"."creator_id" = "person"."id")
)
INNER JOIN "community" ON ("post_aggregates"."community_id" = "community"."id")
)
LEFT OUTER JOIN "community_person_ban"
ON (("post_aggregates"."community_id" = "community_person_ban"."community_id") AND ("community_person_ban"."person_id" = "post_aggregates"."creator_id"))
)
INNER JOIN "post" ON ("post_aggregates"."post_id" = "post"."id")
)
LEFT OUTER JOIN "community_follower" ON (("post_aggregates"."community_id" = "community_follower"."community_id") AND ("community_follower"."person_id" = 3))
)
LEFT OUTER JOIN "community_moderator" ON (("post"."community_id" = "community_moderator"."community_id") AND ("community_moderator"."person_id" = 3))
)
LEFT OUTER JOIN "post_saved" ON (("post_aggregates"."post_id" = "post_saved"."post_id") AND ("post_saved"."person_id" = 3))
)
LEFT OUTER JOIN "post_read" ON (("post_aggregates"."post_id" = "post_read"."post_id") AND ("post_read"."person_id" = 3))
)
LEFT OUTER JOIN "person_block" ON (("post_aggregates"."creator_id" = "person_block"."target_id") AND ("person_block"."person_id" = 3))
)
LEFT OUTER JOIN "post_like" ON (("post_aggregates"."post_id" = "post_like"."post_id") AND ("post_like"."person_id" = 3))
)
LEFT OUTER JOIN "person_post_aggregates" ON (("post_aggregates"."post_id" = "person_post_aggregates"."post_id") AND ("person_post_aggregates"."person_id" = 3))
)
LEFT OUTER JOIN "community_block" ON (("post_aggregates"."community_id" = "community_block"."community_id") AND ("community_block"."person_id" = 3)))
LEFT OUTER JOIN "local_user_language" ON (("post"."language_id" = "local_user_language"."language_id") AND ("local_user_language"."local_user_id" = 3))
)
WHERE
post_aggregates.id IN (
SELECT id FROM post_aggregates
WHERE "post_aggregates"."creator_id" = 3
ORDER BY "post_aggregates"."featured_local" DESC , "post_aggregates"."published" DESC
LIMIT 1000
)
AND
(((((((
(
(("community"."deleted" = false) AND ("post"."deleted" = false))
AND ("community"."removed" = false))
AND ("post"."removed" = false)
)
AND ("post_aggregates"."creator_id" = 3)
)
AND ("post"."nsfw" = false))
AND ("community"."nsfw" = false)
)
AND ("local_user_language"."language_id" IS NOT NULL)
)
AND ("community_block"."person_id" IS NULL)
)
AND ("person_block"."person_id" IS NULL)
)
ORDER BY "post_aggregates"."featured_local" DESC , "post_aggregates"."published" DESC
LIMIT 10
OFFSET 0
;
If it isn’t social hazing, then what is going on here? Why has this issue gone on since May and servers are crashing every day?
. However, I’m far from an expert,
Funny, because I’m a published author and expert on messaging systems… like Lemmy. Iv’e been building them since 1986 professionally.
There was a massive thread I posted dozens of comments on that came before today’s pull request… I suggest you read that too.
Did you notice them even acknowledge server crashes are happening? Do you think developers ever suggest Memcache or Redis? Or discuss how Reddit solved their scaling in 2010 with PostgreSQL?
but perhaps they themselves felt attacked. I know that wasn’t your intention, but misunderstanding happen, especially over text.
I don’t have any trouble understanding a bad SQL statement that has 14 JOINs and being told “JOIN is a distraction” after posting tons of examples.
Do we really need to spoon fed the stuff I did post?
Have you never seen social hazing in action? is it possible that I might be on to something going on psychologically besides my autism?
I can’t believe anyone thinks a server should be crashing with 1 user on it.
may I voice my opinion on the exchange? This is coming from a place of trying to help, since I really do appreciate all the work you’ve put in and are putting in, and the fediverse can really use your talents, so I hope I don’t offend you.
Can you explain to me why it isn’t social hazing?
it didn’t appear that you were being ignored/hazed
Do you know how to read a SQL statement? I just can’t grasp how it isn’t social hazing. I’ve been reading SQL statements for decades, this is obviously a problematic one.
Can you offer alternate explanations of how 3 people could think that SQL statement isn’t … poor performing and gong to cause problems? And how an SQL statement without a WHERE clause took them months to discover and fix?
Extreme hazing is my best answer. I just can’t accept that the SQL statements don’t speak for themselves along with the server crashes. 57K users for 1300 servers is very… taking several seconds to load 10 posts…
Look at the date… May… this has been going on since May. If it isn’t social hazing … what is it? I keep asking myself that.
Why is there a lack of gifs/videos on Lemmy?
Lemmy’s internal data performance is so horribly slow and crash-causing that I think the last thing they want is even more popular data.
Video is simply the most superior type of media there is, and I think that not having easy access to it on Lemmy is hurting it.
Video is more data, popularity is more data. For whatever reason, at every turn, I’ve seen developers turn away from scaling options like Memcache, Redis, or just abandoning ORM data management and rewriting the data interfaces by hand…
since the sites on which the videos are hosted can track you.
That’s already true for images that are hot linked routinely, so I don’t think video really changes it.
I’ve been baffled since June why data and fixing lemmy’s data coding hasn’t been front and center. It’s pretty wild to witness so many come to Lemmy and then turn away… Elon Musk has been flocking people, Reddit, etc. It’s as if the project wants to make code that won’t work on any data. It’s baffeling.
You’re putting too much importance into this matter. If this is distressing you should let it go and think about something else.
The apologists come out of the woodwork around here who can’t see an SQL statement for what it is, a charade. Anyone who has worked with SQL knows that this is bloated SQL statement and poorly engineered.
I notice the scientific facts of server crashing and SQL statements you won’t discuss, but you sure dish out the social advice for me to “move along” like a Jedi mind trick. Let’s talk about the human attraction to truth and honesty since you are so great at handing out life advice to people. What do you know about the works of Marshall McLuhan on media?
Repeating: Its’ as if the mere concept of Redis or Memcache never existed… and that nobody ever heard of JOIN performance problems. If it isn’t extreme social hazing, what is it?
