I have created an app in Rails on Heroku using a PostgreSQL database.
It has a couple of tables designed to be able to sync with mobile devices where data can be created on different places. Therefor I have a uuid field that is a string storing a GUID in addition to an auto increment primary key. The uuid is the one that is communicated between the server and the clients.
I realised after implementing the sync engine on the server side that this leads to performance issues when needing to map between uuid<->id all the time (when writing objects, I need to query for the uuid to get the id before saving and the opposite when sending back data).
I'm now thinking about switching to only using UUID as primary key making the writing and reading much simpler and faster.
I've read that UUID as primary key can sometimes give bad index performance (index fragmentation) when using clustered primary key index. Does PostgreSQL suffer from this problem or is it OK to use UUID as primary key?
I already have a UUID column today so storage wise it will be better because I drop the regular id column.
Numbers generated by a sequence and UUID s are both useful as auto-generated primary keys. Use identity columns unless you need to generate primary keys outside a single database, and make sure all your primary key columns are of type bigint .
Primary keys should never be exposed, even UUIDsA primary key is, by definition unique within its scope. It is, therefore, an obvious thing to use as a customer number, or in a URL to identify a unique page or row. Don't! I would argue that using a PK in any public context is a bad idea.
Pros. Using UUID for a primary key brings the following advantages: UUID values are unique across tables, databases, and even servers that allow you to merge rows from different databases or distribute databases across servers. UUID values do not expose the information about your data so they are safer to use in a URL.
On performance, briefly: A UUID like the one above is 36 characters long, including dashes. If you store this VARCHAR(36), you're going to decrease compare performance dramatically. This is your primary key, you don't want it to be slow.
(I work on Heroku Postgres)
We use UUIDs as primary keys on a few systems and it works great.
I recommend you use the uuid-ossp
extension, and even have postgres generate UUIDs for you:
heroku pg:psql psql (9.1.4, server 9.1.6) SSL connection (cipher: DHE-RSA-AES256-SHA, bits: 256) Type "help" for help. dcvgo3fvfmbl44=> CREATE EXTENSION "uuid-ossp"; CREATE EXTENSION dcvgo3fvfmbl44=> CREATE TABLE test (id uuid primary key default uuid_generate_v4(), name text); NOTICE: CREATE TABLE / PRIMARY KEY will create implicit index "test_pkey" for table "test" CREATE TABLE dcvgo3fvfmbl44=> \d test Table "public.test" Column | Type | Modifiers --------+------+------------------------------------- id | uuid | not null default uuid_generate_v4() name | text | Indexes: "test_pkey" PRIMARY KEY, btree (id) dcvgo3fvfmbl44=> insert into test (name) values ('hgmnz'); INSERT 0 1 dcvgo3fvfmbl44=> select * from test; id | name --------------------------------------+------- e535d271-91be-4291-832f-f7883a2d374f | hgmnz (1 row)
EDIT performance implications
It will always depend on your workload.
The integer primary key has the advantage of locality where like-data sits closer together. This can be helpful for eg: range type queries such as WHERE id between 1 and 10000
although lock contention is worse.
If your read workload is totally random in that you always make primary key lookups, there shouldn't be any measurable performance degradation: you only pay for the larger data type.
Do you write a lot to this table, and is this table very big? It's possible, although I haven't measured this, that there are implications in maintaining that index. For lots of datasets UUIDs are just fine though, and using UUIDs as identifiers has some nice properties.
Finally, I may not be the most qualified person to discuss or advice on this, as I have never run a table large enough with a UUID PK where it has become a problem. YMMV. (Having said that, I'd love to hear of people who run into problems with the approach!)
As the accepted answer states, range queries may be slow in this case, but not only on id
.
Autoincrement is naturally sorted by date, so when autoincrement is used the data is stored chronologically on disk (see B-Tree) which speeds up reads (no seeking for HDDs). For example, if one lists all the users the natural order would be by date created which is the same as autoincrement and so range queries execute faster on HDDs while on SSD, i guess, the difference would be nonexistent since SSDs are by design always random access (no head seeking, no mechanical parts involved, just pure electricity)
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