Hi!
By default you cannot assign a specific affinity key to a specific node
but I think that could be done with a custom affinity function, you can
do pretty much whatever you want with that, for example set an attribute
in the XML file and use that to match with a specific affinity key
value, so a node with attribute x will be assigned all affinity keys
with value y.
I never tried it but I do not see any reason why it would not work.
Mikael
Den 2019-01-02 kl. 17:13, skrev Clay Teahouse:
Thanks Mikael.
I did come across that link before, but I am not sure it addresses my
concern. I want to see how I need I size my physical VMs based on
affinity keys. How would I say for India affinity key use this super
size VM and for others use the other smaller ones, so the data doesn't
get shuffled around? Maybe, there is no way, and I just have to wait
for ignite to rebalance the partitions and fit things where they
should be based on the affinity key.
On Wed, Jan 2, 2019 at 8:32 AM Mikael <mikael-arons...@telia.com
<mailto:mikael-arons...@telia.com>> wrote:
You can find some information about capacity planning here:
https://apacheignite.readme.io/docs/capacity-planning
About your India example you can use affinity keys to keep data
together in groups to avoid network traffic.
https://apacheignite.readme.io/docs/affinity-collocation
Mikael
Den 2019-01-02 kl. 14:44, skrev Clay Teahouse:
Thanks Naveen.
-- Cache Groups: When would I start considering cache groups, if
my system is growing, and sooner or later I will have to add to
my caches and I need to know 1) should I starting grouping now
(I'd think yes), 2) if no, when, what number of caches?
-- Capacity Planning: So, there is no guidelines on how to size
the nodes and the physical storage nodes reside on? How do I make
sure all the related data fit the same VM? It can't be the case
that I have to come up with 100s of super size VMs just because I
have one instance with a huge set of entries. For example, if I
have millions of entries for India and only a few for other
countries, how do I make sure all the India related data fits the
same VM (to avoid the network) and have the data for all the
small countries fit on the same VM?
-- Pinning the data to cache: the data pinned to on-heap cache
does not get evicted from the memory? I want to see if there is
something similar to Oracle's memory pinning.
-- Read through: How do I know if something on cache or disk
(using native persistence)?
5) Service chaining: Is there an example of service chaining that
you can point me to?
6) How do I implement service pipelining in apache ignite? Would
continuous query be the mechanism? Any examples?
7) Streaming: Are there examples on how to define watermarks,
i.e., input completeness with regard to the event timestamp?
thank you
Clay
On Tue, Jan 1, 2019 at 11:29 PM Naveen <naveen.band...@gmail.com
<mailto:naveen.band...@gmail.com>> wrote:
Hello
Couple of things I would like to with my experience
1. Cache Groups : Around 100 caches, I do not think we need
to go for Cache
groups, as you mentioned cache groups will have impact on you
read/writes.
However, changing the partition count to 128 from default
1024 would improve
your cluster restart.
2. I doubt if Ignite has any settings we have for this.
3. The only I can think of is to keep the data in on-heap if
the data size
is not so huge.
4. Read through, with native persistence enabled, doing a
read to the disk
will load the cache. But the read is much slower compared
with read from
RAM, by default it does not pre-load the data. If you want to
avoid this you
can pre-load the data programatically and load Memory, good
for even SQL
SELECT as well. But with the 3rd party persistence, we need
to pre-load the
data to make your read work for SQL SELECT.
Thanks
Naveen
--
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