> Hi,
> I was under the impression that countdown latch is implemented in
> replicated cache. So when any number of nodes go down it does not loose
> it's state.
>
> Can you please explain why atmoc data structures are using 1 back when its
> state is very important?
>
> Can we enforce atomic data structures to use replicated cache?
>
> Which cache does ignite use to store atomic data structures?
>
> Thanks
> Prasad
>
> On Mon 8 Jun, 2020, 11:58 PM Evgenii Zhuravlev <
[hidden email]
> wrote:
>
>> Hi,
>>
>> By default, cache, that stores all atomic structures has only 1 backup,
>> so, after losing all data for this certain latch, it recreates it. To
>> change the default atomic configuration use
>> IgniteConfiguration.setAtomicConfiguration.
>>
>> Evgenii
>>
>> сб, 6 июн. 2020 г. в 06:20, Akash Shinde <
[hidden email]>:
>>
>>> *Issue:* Countdown latched gets reinitialize to original value(4) when
>>> one or more (but not all) node goes down. *(Partition loss happened)*
>>>
>>> We are using ignite's distributed countdownlatch to make sure that cache
>>> loading is completed on all server nodes. We do this to make sure that our
>>> kafka consumers starts only after cache loading is complete on all server
>>> nodes. This is the basic criteria which needs to be fulfilled before starts
>>> actual processing
>>>
>>>
>>> We have 4 server nodes and countdownlatch is initialized to 4. We use
>>> cache.loadCache method to start the cache loading. When each server
>>> completes cache loading it reduces the count by 1 using countDown method.
>>> So when all the nodes completes cache loading, the count reaches to zero.
>>> When this count reaches to zero we start kafka consumers on all server
>>> nodes.
>>>
>>> But we saw weird behavior in prod env. The 3 server nodes were shut
>>> down at the same time. But 1 node is still alive. When this happened the
>>> count down was reinitialized to original value i.e. 4. But I am not able to
>>> reproduce this in dev env.
>>>
>>> Is this a bug, when one or more (but not all) nodes goes down then
>>> count re initializes back to original value?
>>>
>>> Thanks,
>>> Akash
>>>
>>