The significant decrease they talk about is a side effect of their chosen language having a GC. This means the strings take more work to deal with than expected.
This feels more like this speaks to the fact that the often small costs associated with certain operations do eventually add up. it's not entirely clear in the post where and when the cost from the GC is incurred, though; I'd presume on creation and destruction?
edit: There are tricks to not traverse a compound object every time, but assume that at least one of the 80M objects in that giant array gets modified in between GC activations.
but, maybe we'd need to know more about how the output data is consumed to know if this would actually help much in the real application. if the next stage of processing wants to randomly access records using Get(int i), where i is the index of the item, then even if we transform the input to JSON with a constant amount of RAM, we still have to store this output JSON somewhere so we can Get those items.
the blog post mentioned "padding", i didn't immediately understand what that was referring to (padding in the output format?) but i guess it must be talking about struct padding, where the items were previously stored as an array of structs, while the code in the article transposed everything into homogeneous arrays, eliminating the overhead of padding
If we had an "array of structs" instead of "struct of arrays" it would be: string(8) + long(8) + int(4) + padding(4) = 24 bytes
The problem isn’t well constrained because it seems to imply that for some reason it needs to be all accessible in memory, doesn’t specify the cardinality of terms, doesn’t specify whether Get(i) is used in a way that requires that particular interface for accessing a row by number.
If I were to do it, I’d just parse a Page at a time and update a metadata index saying Page P contains entries starting at N. The output file could be memmapped and only the metadata loaded, allowing directly index into the correct Page which could be quickly scanned for a record, and would maybe use 1-2MB of RAM for metadata and whatever Pages are actually being touched.
But like I said the problem is not well constrained enough for even a solution like that to be optimal, since it would suffer from full dataset sequential or random access, as opposed to hot Pages and a long tail.
/shrug specs matter if you’re in the optimization phase
The sibling comment provided a good hint already. All you need to store are some file offsets, amounting to a few dozen bytes.
