Hi Arun,
Thanks for your promptly answer.
As we have problems with our windowed topology (the average processing
time keeps increasing, while the processing speed keeps dropping until
hitting zero) I kept thinking about the value of max.spout.pending
parameter for the case of field based windowing.
Imagine the following situation: we have a window length of 1s and a
sliding interval of 0.1s, with the max.pending.spout set to 2, thus each
second the expired tuples are going to be evicted. Now if our windowed
bolt have a parallelism of 2, and the messages are partitioned in a
round robin fashion (well it's not an actually existion partitioning
scheme in Storm, let's say that for the example's sake) between the
component instances, then the topology are going to stop processing
messages, as the watermarks are emitted on a per component basis.
Unless I'm mistaken somewhere, the max.spout.pending should be higher
than (parallelism * (number of tuples in window length + sliding
interval)), right?
Best regards,
Balazs
On 08/24/2016 05:31 PM, Arun Mahadevan wrote:
Hi Balazs,
Tuples are acked only when the window slides and the events fall out of the
window.
So max.spout.pending should be more than max number of tuples in window length
+ sliding interval.
Thanks,
Arun
On 8/24/16, 8:33 PM, "Balázs Kossovics" <balazs.kossov...@s4m.io> wrote:
Hello,
I've recently hit a problem with my topology using the windowing mode
when I set the TOPOLOGY_MAX_SPOUT_PENDING too low.
I have a window lenght of 60 seconds and sliding interval of 1 seconds
with field based timestamping. In my first tests I didn't specify
TOPOLOGY_MAX_SPOUT_PENDING, so when I was working on historical data my
topology died with an OutOfMemoryError because of the practically
unbounded dataflow. Nothing surprising here.
Just to make sure to avoid the OOMError at the next run, I set
TOPOLOGY_MAX_SPOUT_PENDING to 10, which basically pushed my topology in
a deadlock, because the first 10 tuple was all in the same second, so
the WatermarkTimeEvictionPolicy didn't trigger Action. EXPIRE. Following
this train of thought, imagine that the number of messages during given
window attains this limit: your spout stops emitting, so the tuple which
would make the expire event trigger would never come.
Am I right in thinking that TOPOLOGY_MAX_SPOUT_PENDING must always be
greate than the number of messages during any timeperiod equivalent to
the window length?
Best regards,
Balazs
