Your tests are not close to what you are going to have in production IMHO, here are few recommendations:

1. Build a cluster with at least 5 nodes with N=3 and R=W=2 (You can
   update your bucket properties via PBC with Java)
2. Use PBC instead of HTTP.
3. If you are only importing data call
   .store()....withoutFetch().execute() to avoid unnecessary roundtrips.

If you test using unrealistic scenarios you will find unpleasant surprises when you are about to be go live so better to set your expectations right at the beginning.

HTH,

Guido.

On 29/10/13 14:59, Georgi Ivanov wrote:
Hello,
I am importing some big data to Riak.
I am importing like 10GB per day and i have to import one year of data.
The task is to speed up the initial import. After  that i will import on daily
basis, so the speed is not very important.

I am using JAVA HTTP client. So far my test show that the fastest setup is to
use n_val 1 and import to single server.

I tested importing on 2 servers (with n_val:2), but it is actually slower.
My JAVA client is multi-threaded.

My idea is to use n_val:1 on single node, then increase the n_val:2 and add
one more node to the cluster. The problem is that i don't see the storage to
grow when i change n_val : 2
I was looking at Riak Active Anti-Entropy feature and i am expecting my
storage to grow after i increase the n_val. Unfortunately this is not the case
or i don't understand AAE feature ....
I can't any changes in storage size at all. I don't want to go in direction of
force repair as it would take forever.

Can anyone shed some light on AAE ? Or any tips for speeding up the import in
general.

To summarize the situation :
1. One Riak node with n_val : 1 , eLevelDb as back-end
2. Import data.
3. Change n_val to 2
4. Join one more node to the cluster.

What i expect to happen :
To have all the keys distributed to 2 riak nodes with n_val:2
So if i had 1TB of data on node1 with n_val:1 , after changing to n_val 2 and
joining one more node, to have 1TB of data on each node.


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