2 May 2023
Goal: Implement reference counting for buffers in the buffer pool so that I can Uuse the scanner to iterate through a large database file with an out of memory error
Reference counting is in place! Clients can use
BufferPool.get_page(relation, page_no) to get a buffer with the page’s contents. When finished, clients can
.return_page(buffer) to the pool. If two clients request the same page it will be re-used and usage counted accordingly. If all buffers are full when a new page is requested we’ll evict a page that’s not being used (ie,
refcount: 0) and bring in the new page. If all buffers are full and in-use, an exception is raised.
To test, I scanned the
ratings.db file. Before reference counting and evicting buffers I was only able to make it through ~17.5k records (that’s 64 4kb pages worth!) After adding reference counting I got to ~800k records before I killed it. Inspecting the sorted text output from the other day I see that table has 17M records!
I was looking at my entry from a few days ago when I wrapped up out-of-core sorting. At that point I was ready to swear off sorting to move onto other things, but now that I have a nice
Buffer abstraction I think it might be fun to revisit the sorting exercise (though probably with a smaller dataset). With a fixed buffer pool page size, my
Sort node would know if it should try sorting the dataset in-memory or out-of-core.
I may start there next time. After that, I think I should return to the lecture videos and work through hashing. Hopefully with having spent so much time on foundational work during sorting, hashing will go quicker.
Written by Dan Drust on 2 May 2023
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