Hi team,
I was going through the documentation of durable memory at
https://apacheignite.readme.io/docs/durable-memory
As per the documentation, durable memory comes into picture when
PersistentStore configuration is enabled. Now durable memory uses both
RAM(hot data) and disk (superset). When
Hi Ravi,
I don't think it currently will, because this will require integration with
data frames. We have it plans, but it is not implemented yet. I think you
should use IgniteRDD or Ignite APIs directly.
Can you describe business use case you're trying to implement?
-Val
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1. These are just two different protocols for communication between client
and cluster. With current implementations of both, client node would most
likely provide better performance. We're already working on new thin client
implementation though.
2. Can you provide the exact query you run,
any help here ?
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dear ignite gurus,
I have 2 questions about ignite jdbc:
1. why ignite creates two jdbc driver: jdbc thin vs. jdbc client node
2. I tried the jdbc client node driver lots of times on loading data from
Oracle. it is about 6k+ rows. and the sql statement - "select xxx/count
(*)" takes more ms
Well, we need to take a closer look then. This may be affected by
transaction protocol. Viacheslav Koptilin, can you please create a test and
see what time goes to?
kestas, you can switch to Ignite.compute().affinityCall("key", () ->
{return cacheBinary.get("key").field("f"));}); This should work
Hi,
This depends on the feature scope you will need in C++, but in general,
it is not trivial task to implement some of Ignite features in C++. For
example, that's true that you have to specialize BinaryType in C++ now to
work with it, but if you will choose to implement your own solution you
Hi,
this configuration shouldn't work because there is typo in property name in
this code snippet (AffinityKeyFieldName should start with lower case, my
fault from previous posts):
Thanks using latest Java 7 resolves the issue.
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Thanks using latest Java 7 resolves the issue.
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Hi Amit,
Your understanding is correct, an on-heap cache is like a frontend for an
off-heap cache.
It's useful in cases when a lot of cache reads are expected.
The only thing that should be considered is setting an eviction policy for
on-heap cache to
prevent it growing unrestrictedly.
Please
Hi,
By default Ignite runs checkpointing asynchronously in single thread. Configure
number of checkpointing threads, for example:
Right now I am not sure why you see that "caching almost stops": as I said
checkpointing is async. If you put data into a memory page being currently
Hi Val,
Indeed, it does make sense. Thanks for all your help.
- Luqman
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Hi
I have a c++ application that requires querying some data with transactions
on ignite. So I require a ignite client which would be called by this c++
application which would request the ignite server for processing the query.
Now there are two ways in which I could implement the ignite
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