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From Yury Lazouski <yury_lazou...@epam.com>
Subject Performance issue with REPLICATED cache
Date Mon, 26 Oct 2015 20:22:41 GMT
Hi All, 
we are using Ignite 1.3.3 in win server environment. 

*Caches configuration*

Each Ignite node has ~15 caches ~1M records each of Integer-to-Object
entries (total memory required ~7Gb), configured as "REPLICATED",
readFromBackup flag is set to "true", transaction mode is "ATOMIC", all the
rest left defaults. One instance of loader service is configured which
populates caches using IgniteDataStreamer on regular basis (scheduler) with
deltas found in source DB, no other writes/updates are performed on caches,
from client perspective cache is effectively read-only. For the sake of
experiment simplification database is getting loaded to caches only once -
no further updates are happening. 

*Job execution*

In-process (same jvm) client submits callable task to Ignite node which
essentially traverses caches via get(key) and does calculations on retrieved


With one Ignite node average get(key) operation time is 20-40 μs, with
enabling second node timings (same local node timings!) are getting
increased to >100 μs. With adding parallel clients (parallel execution of
callable tasks which travers same caches) numbers reach millisecond level.
If we configure loader service on each node and switch mode to "LOCAL",
get(key) time is constant (0-1 μs) and performance scalability is linear
with addition of Ignite nodes. So the question is how to make "REPLICATED"
cache perform like "LOCAL" if there are no updates to the caches and data is
only getting accessed locally? Please advise. 

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