+1 for getting rid of the TypeComparator interface and rely on the
serialized representation for grouping.
Adding a new type to DataStream API is quite difficult at the moment due
to too many components that are required: TypeInformation (tries to deal
with logical fields for TypeComparators), TypeSerializer (incl. it's
snapshot interfaces), and TypeComparator (with many methods and
internals such normalized keys etc.).
If necessary, we can add more simple comparison-related methods to the
TypeSerializer interface itself in the future (like
TypeSerializer.isDeterministic).
Regards,
Timo
On 04.09.20 11:48, Aljoscha Krettek wrote:
Thanks for publishing the FLIP!
On 2020/09/01 06:49:06, Dawid Wysakowicz <dwysakow...@apache.org> wrote:
1. How to sort/group keys? What representation of the key should we
use? Should we sort on the binary form or should we depend on
Comparators being available.
Initially, I suggested to Dawid (in private) to do the sorting/grouping
by using the binary representation. Then my opinion switched and I thought
we should use TypeComparator/Comparator because that's what the DataSet API
uses. After talking to Stephan, I'm again encouraged in my opinion to use
the binary representation because it means we can eventually get rid of the
TypeComparator interface, which is a bit complicated, and because we don't
need any good order in our sort, we only need the grouping.
This comes with some problems, though: we need to ensure that the
TypeSerializer of the type we're sorting is stable/deterministic. Beam has
infrastructure for this in the form of Coder.verifyDeterministic() [1]
which we don't have right now and should add if we go down this path.
2. Where in the stack should we apply the sorting (this rather a
discussion about internals)
Here, I'm gravitating towards the third option of implementing it in the
layer of the StreamTask, which probably means implementing a custom
InputProcessor. I think it's best to do it in this layer because we would
not mix concerns of different layers as we would if we implemented this as
a custom StreamOperator. I think this solution is also best when it comes
to multi-input operators.
3. How should we deal with custom implementations of StreamOperators
I think the cleanest solution would be to go through the complete
operator lifecycle for every key, because then the watermark would not
oscillate between -Inf and +Inf and we would not break the semantical
guarantees that we gave to operators so far, in that the watermark is
strictly monotonically increasing. However, I don't think this solution is
feasible because it would come with too much overhead. We should solve this
problem via documentation and maybe educate people to not query the current
watermark or not rely on the watermark being monotonically increasing in
operator implementations to allow the framework more freedoms in how user
programs are executed.
Aljoscha
[1]
https://github.com/apache/beam/blob/master/sdks/java/core/src/main/java/org/apache/beam/sdk/coders/Coder.java#L184
