> IMO using bigserial by default is wrong. Use whatever data type is appropriate. Not every table will grow to 4 billion rows and not every table will grow to even 60k rows
The implication I took from that was that they were suggesting using serial over bigserial. My comment was pushing back on that.
Thus, not only would DB ids in principle never show in the UI, they wouldn't even be stable between sessions.
This would protect against a number of security attacks. (I don't know what I'd do about bookmarking, though I suspect most apps have a 80/20 solution they could deploy.) DB ids going out to a user really ought to be considered at least a smell, but it's pretty ingrained into our culture.
When anchors are needed I use a different column for that- not the primary index. (Usually some other unique, already-present, value like the sku or whatever.
The security implications though are substantial. I don't leak primary key info even if the PK is serialized. (These days I'm all-in on UIDS but I have older legacy systems to deal with too.)
It’s like hosting an internal app at a company that contains a SQL injection. “Well, if a hacker can access this app, then that’s a problem that needs addressing either way.” Sure, that may be true, but it’s also true that you’re not a good software engineer.
It's nothing like that at all because the wrong SQL injection can completely ruin people's lives due to leaking stuff it shouldn't whereas the worst an int exhaustion can do is bring some app offline. Whoopdie-doo. Okay, that's not brilliant, but it's not comparable at all.
And there's a reason there aren't tons of "int exhaustion attacks": because there's little point in doing so.
This does happen and break people. You usually don’t hear about it (except on the SRE side) because it is so obvious when it happens to someone they really don’t like talking about it.
"Denial of service" is just not a security bug on the same level as "zomg my credit card is stolen". I have argued this many times before, e.g. https://news.ycombinator.com/item?id=39377795 – It's easy to knock most sites offline regardless just by flooding it with traffic, don't need long-term plans like this (which are likely to be detected before it even has effect).
> This does happen and break people
I have never heard about a deliberate attack using this method.
Defending against denial of service attacks is a gradual, multifaceted problem that is pretty unlikely to hinge on the size of database keys.
If your system is dimensioned to serve a few hundered users then it's not going to be a whole lot more robust if it can theoretically create thousands of trillions of user records rather than just hundereds of millions.
In fact, infinite scalability is a risk in its own right because it can bankrupt you, which is arguably worse than a temporary outage.
That said, I tend to use 64 bit IDs by default as well unless there is a good reason not to (because, you know, what if I'm the next Google?!?).
All it requires is for there to be billions of rows. 32 bits is nutty small considering how little overhead there is in storing 64 bits instead.
This is especially true for PostgreSQL which increments sequences for upserts (even if no records are inserted).
That's how I've hit 32-bit limits on tables that had only a couple million rows.
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I would only use 32-bit for very selective items that is used in a lot of FKs, like a tenant ID.
Personally I would only use an int PK in a table where you know the bounds of the data with very high confidence. Like, at my last job the software involved working with our client's physical store locations. If we managed to capture the entire North American market for the type of business that we worked with, we'd be looking at about 50k stores.
CPU works just as fast with both, however your CPU cache is limited and you'll put more 4-byte integers into your L1.
I don't really understand what you want to convey. CPU is very fast with any kind of integer size. There's no performance penalty to use 1-byte integer compared to 8-byte integer. And there's performance penalty when your L1 or L2 or L3 cache is busted and you need to go to the next memory layer.
They don't. CPUs have as many issues with data alignment as with cache sizes.
As individual variables, they take exactly the same space as 64-bit integers, both in registers and in memory (i.e. in the stack used for automatic variables or in the heap used for dynamically-allocated variables), because of the alignment requirements.
Therefore it never makes sense to use other integers than 64-bit, except as members of aggregate data types.
A database table is an aggregate data type, so the use of small integers in some columns may be justified, but such types shall not be used for variables in the programs that process data from the tables, where misuse of the small integers may cause overflows and there is no advantage from using smaller integer sizes.
Never again.
2 digit years don’t even support the use case of ‘store the current year’ fully.
Secondly, it's not XXXk rows currently-you have to consider the complete lifetime of the table. When rows are deleted/created and how often.
So what you've said is true, but the set of appropriateness for smallint is a much smaller than expected.
For queue tables you can even use `CYCLE` to do that automatically.
You’re going to know well in advance before hitting this limit becomes an issue, and you’ll have plenty of time to either take a bit of downtime and do a column conversion, or do an online migration.
I didn't get your point. When it is 2^31, you definitely need bigint already. When it is much smaller, it will be much smaller overhead.
Also, per docs (https://www.postgresql.org/docs/current/storage-page-layout....), each postgres row has 23 bytes overhead, so your transition from 8->4 bytes will bring marginal improvement.
As to the maximal 8.6 GB mentioned, that's not nothing, _especially_ for RAM. Disk is cheap, but RAM isn't. If you have a smaller instance – say, an r6i.xlarge on AWS (4 vCPU, 32 GB RAM), that's 1/4 of the entire DB's memory.
[0]: https://www.postgresql.org/docs/current/storage-page-layout....
The fact that this overhead exists has nothing to do with the 8.6 GB of wasted space on the INTs.
I disagree its orthogonal and explained why. I guess lets agree on disagree.
For example I have a table that has about a billion rows and uses bigserial, but that table references about 6 other much smaller tables that use serial. I'm saving 48 bytes per row, or 90GB in total. It's a fairly significant save, and that's just on this one table: I have a bunch of tables like this. If I had bigint'd everything my disk space would be roughly double. And all of that is not even considering the extra index size and memory requirements.
Using bigint here would add absolutely nothing. I'm never going to have billions of users. I'm never going to have billions of different operating systems. There will never be billions of countries. I can probably get away with smallint for some of those, but I felt the extra headroom for that was worth the extra bytes.
This is why "bigint by default" is just bad advice IMHO. You will always need to think about it. Of course you shouldn't prematurely optimize integer sizes, but it's also not true that it doesn't matter, because it does. "Better safe than sorry" also applies in the other direction: "zomg we're wasting tons of disk space and spend much more money on servers than we need to" just because someone unthinkingly applied some stupid dogma they read on HN and didn't spend 4 seconds thinking about it.
you saving 24 bytes per row: downsizing 6 columns from 8 bytes to 4, which is fraction of your table size. If your system is sensitive to such change, you likely should optimize something else.
> Using bigint here would add absolutely nothing. I'm never going to have billions of users. I'm never going to have billions of different operating systems.
I think you cherry picked some fictional examples which you won't combine in one table, and your real entities are different. It adds process safety: you don't need to play mind quizzes to estimate how system can grow/change in a N years.
What an incredibly rude and dismissive accusation. Here's my table: https://github.com/arp242/goatcounter/blob/master/db/schema.... – number of IDs is actually 7, not 6.
I can give a lot more details and context on all of that and why it works the way it works and the savings are certainly not insignificant and theoretical, but save me real money in server costs every month. But I have little interest in talking to you further since you're just going to insult everyone who tries to inject the slightest nuance into "always use bigserial"-extremism. So good day to you.
the point is that some/many of those ids are not timezone and country, and potentially can grow high in cardinality.
I said you described fictional scenario, and it appears to be true, your table ID fields are very different than timezone, country and user_id.
Unrelated, I quite enjoyed reading your blog posts. Cheers!
This isn’t even optimization, it’s just understanding your tools and needs. It’s akin to profiling your app under load, seeing that at worst it needs 1 GiB of RAM allocated, and then giving it 8 EiB just in case.
By all means, if you can reasonably predict that a given table will near or pass 2^31 rows in the near future, just set it to BIGINT now. But as has been pointed out, most apps are never, ever going to have close to 2 billion users, or for that matter 2 billion anything. The only thing I can think of that might reasonably run up against that would be invoices for large scales, or object metadata for something like Notion.
all computers will be fine with 640kb of ram
Differences can appear in multicolumn indexes because two ints takes 8 bytes while two bigints takes 16, however the right layout of columns for an index is not always the layout that minimizes padding.
CREATE TABLE foo
(id INT GENERATED ALWAYS AS IDENTITY PRIMARY KEY, iid INT NOT NULL);
CREATE TABLE bar
(id INT GENERATED ALWAYS AS IDENTITY PRIMARY KEY, iid BIGINT NOT NULL);
CREATE TABLE baz
(id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY, iid BIGINT NOT NULL);
-- fill each with 1,000,000 rows, then index
CREATE INDEX {foo,bar,baz}_iid_idx ON {foo,bar,baz}(iid);
SELECT table_name,
pg_size_pretty(pg_table_size(quote_ident(table_name))) "table_size",
pg_size_pretty(pg_indexes_size(quote_ident(table_name))) "index_size"
FROM information_schema.tables
WHERE table_schema = 'public';
table_name | table_size | index_size
------------+------------+------------
foo | 35 MB | 43 MB
bar | 42 MB | 43 MB
baz | 42 MB | 43 MB
As your example shows, there is no benefit in index size (e.g for supporting FKs) in going from int to bigint for a single key. You end up with the same index size no matter what, not twice the size which was what I took your original post to mean.
Outside of that, put absolutely no thought into it and pick a bigint/bigserial.
Trying to be clever about this ignores the fact that tables and their usage change, and what you believe now will not be correct later.
And when you realise you’ve been too clever, it’s 3am on a Sunday, your production database has exploded and nothing works. You now need to rewrite 30 tables and their foreign keys ASAP with upper management breathing down your neck.