Github user fhueske commented on the pull request:
https://github.com/apache/flink/pull/1624#issuecomment-183251312
Hi, I thought about using POJOs as native types within Table/SQL operators.
IMO, the gains are very little compared to the added code complexity. Given a
POJO input, we can preserve the input type only for very few operations such as
a Filter. For most other operations, we need to generate a new output type
(Tuple or Row). I am a bit skeptical about adding a lot of codeGen code with
special cases for POJOs (such as the field index mapping) which is very seldom
used. Moreover, POJO field accesses (for operations and serialization) go
through reflection and are not very efficient. So even the performance gain for
those few cases where POJOs can be used is not clear.
I do not question the native type support in general. Tuples and primitives
should definitely be supported, but I don't think we need to support POJOs
within Table / SQL operators. Instead, I would convert POJO datasets into Row
tables during table scan. Most of the code in this PR can be used to implement
a codeGen'd converter Map function.
What do you think @twalthr?
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