ohhh...thank you. Its cleared now
On Tue, Oct 31, 2017 at 4:36 PM, Damian Guy wrote:
> Hi, the `map` when it is followed by `groupByKey` will cause a
> repartitioning of the data, so you will have your 5 tasks processing the
> input partitions and 5 tasks processing the partitions from the
> rep
Hi, the `map` when it is followed by `groupByKey` will cause a
repartitioning of the data, so you will have your 5 tasks processing the
input partitions and 5 tasks processing the partitions from the
repartitioning.
On Tue, 31 Oct 2017 at 10:56 pravin kumar wrote:
> I have created a stream with
I have created a stream with topic contains 5 partitions and expected to
create 5 stream tasks ,i got 10 tasks as
0_0 0_1 0_2 0_3 0_4 1_0 1_1 1_2 1_3 1_4
im doing wordcount in this example,
here is my topology in this link: 1.
https://gist.github.com/Pk007790/72b0718f26e6963246e83da992
It would depend on what your topology looks like, which you haven't show
here. But if there may be internal topics generated due to repartitioning
which would cause the extra tasks.
If you provide the topology we would be able to tell you.
Thanks,
Damian
On Tue, 24 Oct 2017 at 10:14 pravin kumar
I have created a stream with topic contains 5 partitions and expected to
create 5 stream tasks ,i got 10 tasks as
0_0 0_1 0_2 0_3 0_4 1_0 1_1 1_2 1_3 1_4
my doubt is:im expected to have 5 tasks how it produced 10 tasks
here are some logs:
[2017-10-24 10:27:35,284] INFO Kafka
