8/29/2023 0 Comments Sqlite transaction increased speed![]() ![]() ![]() This is quite a generalised point so difficult to really respond to but some frameworks do provide a mechanism to check if a transaction has been closed. Use last_insert_rowid() or the equivalent for your database. I just tested Sqlite, and it does seem to work there regardless of WAL since it only allows concurrent readers plus a single writer. When I tested this, Postgres and MSSQL handled this as expected while MySQL allowed the select to return a different row. It's only correct on systems with true serializability, when you have opted into full serializability, and where such systems consider autoincrementing IDs to be part of serializability. I used to do this, but this is a very bad habit that may be incorrect (assuming that id is an autoincrementing column). However, it's usually still better for bulk inserts without updates to use fine grained locking or MVCC since you can often avoid acquiring any locks at all beyond the basic ones guarding fundamental DB data structures (these aren't locks as far as SQL is concerned since they cannot cause deadlock, it's a big pet peeve of mine when people think lock-free = no use of mutexes).Īs a side note, don't do the following pattern: "BEGIN TRAN INSERT INTO T. You are right that the Sqlite approach actually works quite well for bulk operations since you only require a single lock. MVCC is good for such cases because you can avoid the overhead of taking lots of locks but still get fine grained concurrency control. I think they are referring to a OLTP type scenario where you have lots of inserts and reads, but the reads only look at a couple of rows at a time, often only a single row. According to that article, it was introduced in, and improved to better handle large transactions (>100MB) in. I believe the only reason it isn't enabled by default is for backwards compatibility. One option you didn't have at the time but might help today is write-ahead mode with journal_mode = WAL (but still presumably not as fast as journal_mode = OFF!). I'm surprised that alone wouldn't have got you decent performance. Yes those are fairly magical hacks, but synchronous and journal_mode at least are things are always worth considering for a new SQLite database (and before building it with debugging symbols!).Įven without those tweaks, the really key thing is to use fairly large transactions. Again depending on your application, you could have set journal_mode = OFF or increased the mmap_size (both also discussed on that page). Depending on your application, you might have got away with NORMAL or even OFF. What you are describing sounds almost exactly like PRAMGA synchronous = FULL (which is the default). Like everyone else, I'm going to offer tuning tips even thought that very much wasn't your point :-) I am probably munging some of the details, but it made me angry enough to learn postgres and port my code over despite having a fix for my immediate problem. I found an email thread where someone in effectively the same situation made some constructive suggestions and got turned away on the principle that even casual users ought to just know performance knobs like this one. The problem turned out to be a default setting that made spill-to-disk very aggressive and basically guaranteed that any workflow like mine would grind along with miserable slowness and no outward indication of what to do about it. The perf tooling wasn't there to quickly figure out where the problem was (this was 10 years ago, not sure if things have improved) so I wound up building a version of SQLite with debug symbols and profiling it with a C profiler. I tried tricks like deleting and recreating indices but without luck. Long version: I couldn't get bulk insert performance above absolutely miserable levels. Counterpoint: I over-used SQLite because it was the first database I encountered and spent waaaay longer working around its shortcomings than I eventually spent porting to postgres. ![]()
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