Have you probe to partitioning your data? It’s pretty simple by adding a field 
(integer partitionId) on your table, so each node will load only its own 
partitions. You could see an example here: 

El 18 oct 2016, a las 9:06, Alexey Kuznetsov 
<akuznet...@apache.org<mailto:akuznet...@apache.org>> escribió:


In current Ignite implementation, if you are loading data via cache store each 
node will iterate whole data set
 and take only those keys that will satisfy affinity function.

 in case of one node - all keys will loaded.
 in case of two nodes: first node will iterate WHOLE data set, but will take 
50% of keys, same with second node.
 in case of three nodes: each node will iterate WHOLE data set, but will take 
33% of keys.

There is no general solution to speedup load.

On Tue, Oct 18, 2016 at 1:34 PM, 胡永亮/Bob 
<hu...@neusoft.com<mailto:hu...@neusoft.com>> wrote:

    I load data into Ignite from oracle with loadCache().

    I load 100w data, when Ignite cluster has one node, its cost time is 2m27s.
    Two nodes, its cost time is 2m18s, three 2m15s, four 2m11s.

    I have tested reading the 100w data through jdbc, its cost time is 40s.

    Why don't the loading speed increase with mode Ignite nodes?



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