if its just a single array, how would you define group/sort keys?
On 31.07.2015 07:03, Aljoscha Krettek wrote:
I think then the Python part would just serialize all the tuple fields to a
big byte array. And all the key fields to another array, so that the java
side can to comparisons on the whole "key blob".
Maybe it's overly simplistic, but it might work. :D
On Thu, 30 Jul 2015 at 23:35 Chesnay Schepler <c.schep...@web.de> wrote:
I can see this working for basic types, but am unsure how it would work
with Tuples. Wouldn't the java API still need to know the arity to setup
serializers?
On 30.07.2015 23:02, Aljoscha Krettek wrote:
I believe it should be possible to create a special PythonTypeInfo where
the python side is responsible for serializing data to a byte array and
to
the java side it is just a byte array and all the comparisons are also
performed on these byte arrays. I think partitioning and sort should
still
work, since the sorting is (in most cases) only used to group the
elements
for a groupBy(). If proper sort order would be required this would have
to
be done on the python side.
On Thu, 30 Jul 2015 at 22:21 Chesnay Schepler <c.schep...@web.de> wrote:
To be perfectly honest i never really managed to work my way through
Spark's python API, it's a whole bunch of magic to me; not even the
general structure is understandable.
With "pure python" do you mean doing everything in python? as in just
having serialized data on the java side?
I believe the way to do this with Flink is to add a switch that
a) disables all type checks
b) creates serializers dynamically at runtime.
a) should be fairly straight forward, b) on the other hand....
btw., the Python API itself doesn't require the type information, it
already does the b part.
On 30.07.2015 22:11, Gyula Fóra wrote:
That I understand, but could you please tell me how is this done
differently in Spark for instance?
What would we need to change to make this work with pure python (as it
seems to be possible)? This probably have large performance
implications
though.
Gyula
Chesnay Schepler <c.schep...@web.de> ezt írta (időpont: 2015. júl.
30.,
Cs,
22:04):
because it still goes through the Java API that requires some kind of
type information. imagine a java api program where you omit all
generic
types, it just wouldn't work as of now.
On 30.07.2015 21:17, Gyula Fóra wrote:
Hey!
Could anyone briefly tell me what exactly is the reason why we force
the
users in the Python API to declare types for operators?
I don't really understand how this works in different systems but I
am
just
curious why Flink has types and why Spark doesn't for instance.
If you give me some pointers to read that would also be fine :)
Thank you,
Gyula
