Hi,
During the implementation of this KIP and after some discussion about
RocksDB metrics, I decided to make some major modifications to this KIP
and kick off discussion again.
https://cwiki.apache.org/confluence/display/KAFKA/KIP-607%3A+Add+Metrics+to+Kafka+Streams+to+Report+Properties+of+RocksDB
Best,
Bruno
On 15.05.20 17:11, Bill Bejeck wrote:
Thanks for the KIP, Bruno. Having sensible, easy to access RocksDB memory
reporting will be a welcomed addition.
FWIW I also agree to have the metrics reported on a store level. I'm glad
you changed the KIP to that effect.
-Bill
On Wed, May 13, 2020 at 6:24 PM Guozhang Wang <wangg...@gmail.com> wrote:
Hi Bruno,
Sounds good to me.
I think I'm just a bit more curious to see its impact on performance: as
long as we have one INFO level rocksDB metrics, then we'd have to turn on
the scheduled rocksdb metrics recorder whereas previously, we can decide to
not turn on the recorder at all if all are set as DEBUG and we configure at
INFO level in production. But this is an implementation detail anyways and
maybe the impact is negligible after all. We can check and re-discuss this
afterwards :)
Guozhang
On Wed, May 13, 2020 at 9:34 AM Sophie Blee-Goldman <sop...@confluent.io>
wrote:
Thanks Bruno! I took a look at the revised KIP and it looks good to me.
Sophie
On Wed, May 13, 2020 at 6:59 AM Bruno Cadonna <br...@confluent.io>
wrote:
Hi John,
Thank you for the feedback!
I agree and I will change the KIP as I stated in my previous e-mail to
Guozhang.
Best,
Bruno
On Tue, May 12, 2020 at 3:07 AM John Roesler <vvcep...@apache.org>
wrote:
Thanks, all.
If you don’t mind, I’ll pitch in a few cents’ worth.
In my life I’ve generally found more granular metrics to be more
useful,
as long as there’s a sane way to roll them up. It does seem nice to see
it
on the per-store level. For roll-up purposes, the task and thread tags
should be sufficient.
I think the only reason we make some metrics Debug is that
_recording_
them can be expensive. If there’s no added expense, I think we can just
register store-level metrics at Info level.
Thanks for the KIP, Bruno!
-John
On Mon, May 11, 2020, at 17:32, Guozhang Wang wrote:
Hello Sophie / Bruno,
I've also thought about the leveling question, and one motivation I
had for
setting it in instance-level is that we want to expose it in INFO
level:
today our report leveling is not very finer grained --- which I
think
is
sth. worth itself --- such that one have to either turn on all
DEBUG
metrics recording or none of them. If we can allow users to e.g.
specify
"turn on streams-metrics and stream-state-metrics, but not others"
and
then
I think it should be just at store-level. However, right now if we
want to
set it as store-level then it would be DEBUG and not exposed by
default.
So it seems we have several options in addition to the proposed
one:
a) we set it at store-level as INFO; but then one can argue why
this
is
INFO while others (bytes-written, etc) are DEBUG.
b) we set it at store-level as DEBUG, believing that we do not
usually
need
to turn it on.
c) maybe, we can set it at task-level (? I'm not so sure myself
about
this.. :P) as INFO.
Guozhang
On Mon, May 11, 2020 at 12:29 PM Sophie Blee-Goldman <
sop...@confluent.io>
wrote:
Hey Bruno,
Thanks for the KIP! I have one high-level concern, which is that
we
should
consider
reporting these metrics on the per-store level rather than
instance-wide. I
know I was
the one who first proposed making it instance-wide, so bear with
me:
While I would still argue that the instance-wide memory usage is
probably
the most *useful*,
exposing them at the store-level does not prevent users from
monitoring the
instance-wide
memory. They should be able to roll up all the store-level
metrics
on an
instance to
compute the total off-heap memory. But rolling it up for the
users
does
prevent them from
using this to debug rare cases where one store may be using
significantly
more memory than
expected.
It's also worth considering that some users may be using the
bounded
memory
config setter
to put a cap on the off-heap memory of the entire process, in
which
case
the memory usage
metric for any one store should reflect the memory usage of the
entire
instance. In that case
any effort to roll up the memory usages ourselves would just be
wasted.
Sorry for the reversal, but after a second thought I'm pretty
strongly in
favor of reporting these
at the store level.
Best,
Sophie
On Wed, May 6, 2020 at 8:41 AM Bruno Cadonna <br...@confluent.io
wrote:
Hi all,
I'd like to discuss KIP-607 that aims to add RocksDB memory
usage
metrics to Kafka Streams.
https://cwiki.apache.org/confluence/display/KAFKA/KIP-607%3A+Add+Metrics+to+Record+the+Memory+Used+by+RocksDB+to+Kafka+Streams
Best,
Bruno
--
-- Guozhang
--
-- Guozhang
