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all.equal.data.table throws "Dataset 'current' has rows not present in 'target'" when double precision values are numerically, but not exactly, equal #7816
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The test is at line 244 of setops.R:
ans1 = target[current, roll=tolerance, rollends=TRUE, which=TRUE, on=jn.on]Importantly,
all.equal.data.frame()finds them equal:x <- data.frame(v = 1.0) y <- transform(x, v=v - sqrt(.Machine$double.eps) / 3.0) all.equal(x,y) # [1] TRUEThere is related issue: #7434
I have a wip branch to rewrite data.table's method to follow "data.frame way" (although df doesn't have ignore.row.order feature), so instead of rolling joins, to sort the data and compare using all.equal.list.
I believe it will break a lot of downstream code so I somehow haven't made it ready enough to open PR.
If we agree on replacing rolling joins with sort + all.equal.list then I am happy to submit it.
Optionally we could have a new function for that, as there are few other useful things that could be plugged in.
When
ignore.row.order = TRUE,all.equal.data.tablethrows' "Dataset 'current' has rows not present in 'target'" when there are multiple double precision columns and any but the last one are not perfectly equal.