SQLite notes
| Database related
More theoretical - thinking about databases:
Everyday-use notes |
For some introduction, see Some_databases,_sorted_by_those_types#SQLite
On text coding
On SQLite typing
This page mentions a lot of what you want to know.
For contrast: where most RDBMSes are statically typed (converts data to the column's type on storage, fails if it can't)...
...SQLite is more like dynamic typing in that SQLite decides the type from the value you give it, and only somewhat cares about the according column's type.
A little more precisely, the schema defines a type affinity, not a rigid type.
- 'type affinity' here meaning 'the value may still be of any type, but we prefer this one if that works'
The SQL types map to the affinity of INTEGER, REAL, NUMERIC, TEXT, BLOB, or NULL
- e.g. INTEGER is split into seven specific-sized things -- on disk, anyway; in memory all are loaded into int64(verify)
- TEXT is stored as UTF-8, UTF-16LE, or UTF-16BE (according to the database encoding) (verify)
For example(verify)
- if you store into a numeric column, it will do something like
- if not well formed as an integer or real, it's stored as TEXT
- if it's a real number (with digit) and store as REAL if (seems like float64 so if there was more precision in the text that will be lost)
- if it's an integer, and find the smallest integer type that will store it
- if it's an integer larger than int64 can store, it will try REAL
- hex is stored as text
Assume that the schema is not used for conversions going out
AFAICT, what you get out is whatever type that got stored, and it is the logic on insert that is interesting.
...at least, that's what synamically typed languages tend to do with it. Statically typed languages (including SQLite's onw API) may get you to convert it, and/or makes you test for it(verify).
On concurrency
Say the writers: "SQLite is not designed to replace Oracle. It is designed to replace fopen()"
That said, it does about as much as it can with what the filesystem provides, which is pretty great on a single device.
...but keep in mind there are limits - and that filesystems vary. In particular some network filesystems do not do enough.
Concurrency from distinct tasks
Multiple threads
There is usually nothing to be gained from distinct threads accessing the same database, so maybe avoid doing this.
Yet if you insist: SQLite can be compiled to be thread-safe, and usually is. (the reason you can compile without is that removing this safety is slightly faster for cases you know will always be single-threaded)
You can query that compile option from the database at runtime if you want to be sure.
This page points out there is a further distinction between multi-threaded (where threads must not share a connection) and serialized (where that appears to be fine).
Some libraries may have their own decisions - e.g. python3's sqlite3 will complain SQLite objects created in a thread can only be used in that same thread, though that seems to be overzealous.
Multiple processes
Multiple processes can access the same database.
Assume that:
- multiple can read concurrently
- writes are not concurrent with other writes
- writes are not concurrent with reads
It is somewhat up to clients to error out, or wait and/or time out(verify)
Things work a little better with a non-standard method, but it comes with more requirements.
Limitations:
- locking (and the journaling that relies on it) relies on some filesystem semantics
- assume this will not work properly over some network filesystems (e.g. NFS, some SMB, a.k.a. windows network mounts).
- You should not carry an open connection though a fork
More on concurrent operations
See also: