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author | Travis Watkins <amaranth@ubuntu.com> | 2012-09-11 05:51:09 -0500 |
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committer | Travis Watkins <amaranth@ubuntu.com> | 2012-09-21 11:20:10 -0500 |
commit | 74b3be57b77ff3bee30b8fb0fd993c325d7f9207 (patch) | |
tree | 6489bffc74a33452a3a9298eae2ed50569fefef9 /LGPL.txt | |
parent | 9f70c1f3864632b90a4c4edfbde7f6fc2c10b9b0 (diff) | |
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Replace LongObjectHashMap with a more efficient implementation
After further testing it appears that while the original LongHashtable
has issues with object creation churn and is severly slower than even
java.util.HashMap in general case benchmarks it is in fact very efficient
for our use case.
With this in mind I wrote a replacement LongObjectHashMap modeled after
LongHashtable. Unlike the original implementation this one does not use
Entry objects for storage so does not have the same object creation churn.
It also uses a 2D array instead of a 3D one and does not use a cache as
benchmarking shows this is more efficient. The "bucket size" was chosen
based on benchmarking performance of the HashMap with contents that would
be plausible for a 200+ player server. This means it uses a little extra
memory for smaller servers but almost always uses less than the normal
java.util.HashMap.
To make up for the original LongHashtable being a poor choice for generic
datasets I added a mixer to the new implementation based on code from
MurmurHash. While this has no noticable effect positive or negative with
our normal use of chunk coordinates it makes the HashMap perform just as
well with nearly any kind of dataset.
After these changes ChunkProviderServer.isChunkLoaded() goes from using
20% CPU time while sampling to not even showing up after 45 minutes of
sampling due to the CPU usage being too low to be noticed.
Diffstat (limited to 'LGPL.txt')
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