Hi,
I have a problem which seems to be unsolvable in Flink at the moment
(1.0-Snapshot, current master branch)
and I would kindly ask for some input, ideas on alternative approaches or just a
confirmatory "yup, that doesn't work".
### Here's the situation:
I have a dataset and its elements are totally ascending sorted by some
key (Int). Each element has a "next-pointer" to its successor, which is
just another field with the key of the following element: x0 -> x1 -> x2
-> x3 -> ... -> xn The keys are not necessarily increasing by 1, so it
may be that: x0 has key 2 and x1 has key 10, x2 has 11, x3 has 25 and so
on. I need to process that set in the following way: iterate: find all
pairs of elements where "next == key" BUT make sure no element appears
in multiple pairs example: do pair (x0, x1), (x2, x3), (x4, x5), ... but
don't pair (x1, x2), (x3, x4), ... then, if some condition is met,
combine a pair run above procedure again with switched
pairing-condition: example: do pair (x1, x2), (x3, x4), (x5, x6), ... do
not pair (x0, x1), (x2, x3), .. I hope the problem is clear... ### Now
my approach: pseudo-scala-code:
val indexed = input.zipWithIndex val flagged = indexed.map((i, el) =>
el.setFlag(i % 2 == 0)) val left = flagged.filter(el => el.flag)
val right = flagged.filter(el => !el.flag) left.fullOuterJoin(right)
.where(el.next) .equalTo(el.key) ... I attach my elements with a
temporary key, that is increasing by 1, with zipWithIndex. Then, I map
that tempKey to a boolean joinFlag: true if key is even, false if key is
odd. Then I filter all elements with true, and put them in a dataset
that is the left side of the next == key join. The right side are all
elements with flag == false In the second run, I switch the flag
construction to el.setFlag(i % 2 != 0). That actually works, there is
only one problem: ### The problem: In my approach, I must not loose the
total ordering of the data, because only if that ordering is preserved,
the assignment of alternating join-flags works. Initially it is done by
range-partitioning and partition-sorting. However, that ordering is
destroyed, when data is shuffled for the join. And I can not restore it,
because I have to run the whole thing in an iteration, and
range-partitioning is not supported within iterations. ### Help? It
sounds all very complicated, but the only thing I really have to solve
is that join without any element appearing in multiple pairs (as
described in "the situation"). If anyone has any idea how to solve this,
that person would make my day so hard... Anyways, thanks for your time!
Best, Fridtjof
