HI Martin, It depends on the RDBMS. Some are still one row at a time, which makes insert and bulk_insert the same speed (it just makes the statement easier to write.
Hi MIke, One of the goals of the DAL is to make the api database neutral, allowing you to switch between databases without changing your code (hopefully). The thing you sacrifice if you use a bulk native loader (today) is that you are locking yourself into a specific database platform. The api for the DAL doesn't have any platform specific features (I think), although some features don't apply to all. What I was suggesting was a "Native Load" method which is defined within each database adapter as they will all be different. Just a thought although unlike ANSI SQL, every separate platform probably has their own syntax for their bulk loader. Reiterating, I think bulk loading is a thing you would do as a batch / scheduler process. It's not what you'd use with your web end-user app. If that's the case, does it make sense for it to be a part of the DAL, or as perhaps separate (contrib) modules targetting specific platforms ? On Monday, August 20, 2012 1:36:14 PM UTC+12, Mike Girard wrote: > > "bulk insert is a way faster than regular insert when you have many rows" > > I think we need to clarify terms. By Massimo's own account in the web2py > book, the DAL bulk insert is not faster than db.insert unless you are using > the GAE. So are you talking about your db's native bulk methods or is the > book wrong? > > Could someone just please answer what, if anything, is being sacrificed > when you use your database's own bulk loading methods instead of using the > DAL? Why the DAL religion about this? > > On Sunday, August 19, 2012 5:09:43 PM UTC-4, Martin.Mulone wrote: >> >> bulk insert is a way faster than regular insert when you have many rows. >> If you are under mysql you can use load data infile, this is incredible >> fast, but you need special privileges under mysql. >> >> 2012/8/19 Andrew <awill...@gmail.com> >> >>> Is it possible that we add a "native bulk insert" function which is >>> coded up in each adapter. Even bulk_insert is an odbc 1 row at a time-slow >>> for big files. I need to load huge files all the time and I am writing >>> custom modules to do this with a native loader. Should this be a dal >>> option? Worth noting that this type of operation is a batch, back end >>> thing, I wouldn't do this for a end user web app. >>> >>> I would expect that each DBMS needs different info to start a bulk load, >>> so the interface may be tricky, or just pass a dict and let the adapter >>> work it out. >>> What do you think? >>> >>> -- >>> >>> >>> >>> >> >> >> -- >> http://www.tecnodoc.com.ar >> >> --
