Hi, first, thanks a lot for your input! Am 19.05.20 16:16 schrieb(en) Stephen Frost:
That's only going to work up to a certain size for that text and blob value too, of course..
These three columns (stripped-down code, there are more in the table) are a “lazy” import from various python scripts. The text and bytea (actually a sha256 hash) fields always have a fixed, short size, but the json varies between a single item and a quite large dict, so extracting the data into columns seems to be cumbersome.
This is looking like it might be some kind of KV store which is generally discouraged.
Well, yes, somehow…
"jsonb" uses an internal binary representation that reorders the attributes in a deterministic fashin, so yes, that is guaranteed.Sure- but the md5() isn't going to run on the jsonb data directly, it'll run on the text representation that's returned, and I'm not at all convinced that the project has agreed to make that text form always be canonical and identical forever, including across major version upgrades..
Ok, I see.
Further, there are some other cases to consider- such as: do you think that 0.00001230 is different from 0.0000123? Since we'll store numbers in jsonb as numeric, we preserve trailing franctional zeroes.
Good point; currently no problem for me (strings and ints only in the json dicts), but might be a serious issue in the future.
Overall, if what you need is uniqueness here, I'd strongly reconsider the choice to use jsonb to store this data and instead see if you can break the data out into proper columns with a proper unique constraint across them (or across some hash of the combination of them that's done in a way that is clear and unambiguous).
Got your point, I hope – probably the clean solution would be a defined, sorted serialisation plus hashing of the json (and the text and bytea columns) either in the python producers, or in the (already existing) db function called by the python scripts for inserting data… Thanks again, Albrecht.
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