Hi,
I'm inserting and then updating 250 cache entries using a couple of threads. So
a total of 500 cache puts. The initial 250 writes take a little under 500ms. So
each initial put is taking approx. 2ms. While that's a little faster than
writing to database, I would expect RAM write to be much
Hi running 2.7.0
I have a four node cluster. And I have inserted some records from an
application running on my laptop (wifi network) using the thin client.
Now I'm using the Ignite Visor to connect to the cluster from my laptop
(wifi network) and it seems to hang.
visor> open
By default Ignite thinks that data is collocated. You have to tell Ignite
that it is not. For example, by adding a parameter to JDBC connection:
distributedJoins=true or by using this method
SqlQueryFields.setDistributedJoins [1] in java API.
[1]
My assumption was that you used IgniteCache.withKeepBinary(true) in your own
method getCache(Foo.class) method. Anyway, congrats on finding a solution.
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Hi Jose,
There are no strict requirement for network connection quality as you can
adjust network properties [1] for your particular case.
Talking about a cache distributed across two separate data centres is
totally fine. Just make sure that connection between them is stable and
think of a
Hi Ignite Team,
- what is the recommended minimum network connection bandwidth between nodes
(100M? 1G? >1G?)
- what is the recommended minimum network latency between nodes (<1ms?
<10ms? <100ms?)
- can one use the same 'affinityBackupFilter' strategy that is recommended
for distributing backup
Hi Luqman,
Does your plugin just detect a segmentation occurrence? Or does it also
resolve the split-brain condition?
Thanks,
Jose
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