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From pragmaticbigdata <amits...@gmail.com>
Subject Re: Simulating Graph Dependencies With Ignite
Date Thu, 02 Jun 2016 06:26:20 GMT
Hi Alexei, I was able to implement this custom logic based on your guidance
below. Thanks for that. I do experience a couple of performance issues.

1. With a caching having 1 million entries, updating 11k entities 5 times
(cached entities are updated multiple times in the application) took 1 min.
The cluster configuration includes 5 server nodes with 16 cpu cores and 15
GB RAM. The cache is a partitioned cache with 0 backups. Can these timings
be improved?

2. I tried using the compute colocation feature by having a affinityRun()
but that seems to be degrading the performance otherwise. Making an affinity
call through affinityRun() method by passing a Callable resulted into a poor
performance compared to the default execution. The code does a localPeek and
updates that cache entry along with returning one of the properties from the
cached object. Would you have inputs on what could be the problem? The code
looks like below

        for(String key : keyValues) {
outputValues.add(ignite.compute().affinityCall(productCache.getName(), key,
() -> updateCacheEntry(key, productCache.localPeek(key))));

Kindly let me know your suggestions.

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