Hi!
Not so easy to answer, if you also run your own code for example it will
use memory, I would suggest you create an application or a test
application, run it and see how much memory it use (just run JConsole or
something) and you will get a pretty clear view of how much you will
need, add
Thanks for your reply.
I mean if we store data in off-heap memory, should give much heap memory
by setup ignite jvm start option (-XMX)? We setup
CacheConfiguration.setOnheapCacheEnabled (false) . How many memory
should we configurate for ignite jvm start option (-XMX) is enough usually?
Mikae
Hi!
I would not expect any big difference, withKeepBinary allows you to work
with object without having to deserialize the entire object and you do
not need the actual class to be available, and you can also add/remove
fields from objects, but from a heap point of view I do not think you
will
By reading document we know it need read object from off-heap to on-heap
when do some reads on server node. We do some timer job that would query
cache(igniteCache.withKeepBinary().query(new ScanQuery())) , Does this
operation need more on-heap memory? we setup
CacheConfiguration.setOnheapCacheEnab
thank you very much.
Mikael 于2019年12月8日周日 上午1:24写道：
> Hi!
>
> The data regions are always off-heap, you just configure the Java heap for
> on-heap usage with -Xmx and so on as usual, have a look in the
> ignite.sh/ignite.bat, it depends on how you run your application, just
> configure this any
Hi!
The data regions are always off-heap, you just configure the Java heap
for on-heap usage with -Xmx and so on as usual, have a look in the
ignite.sh/ignite.bat, it depends on how you run your application, just
configure this any way you like if you use embedded Ignite instance,
also read t
HI,
According to document we can setup memory size by
org.apache.ignite.configuration.DataStorageConfiguration.
But we do not know this works for off-heap or on-heap memory. We want to
know how to setup ignite jvm startup option(xms, xmx). Shoud jvm heap
memory be great than maxSixe in DataStor
