[concurrency-interest] ConcurrentSkipListMap performance

Ben Manes ben_manes at yahoo.com
Sun Oct 23 15:58:11 EDT 2011


There's not enough information to diagnose the cause, but you may want to try one of the CSLM replacements.


https://github.com/mspiegel/lockfreeskiptree
https://github.com/nbronson/snaptree



________________________________
From: Ted Yu <ted_yu at yahoo.com>
To: "concurrency-interest at cs.oswego.edu" <concurrency-interest at cs.oswego.edu>
Sent: Sunday, October 23, 2011 12:01 PM
Subject: [concurrency-interest] ConcurrentSkipListMap performance


HBase expects ConcurrentSkipListMap to have good performance.
See the following discussion.

Comments are welcome.

---------- Forwarded message ----------
From: Akash Ashok <thehellmaker at gmail.com>
Date: Sun, Oct 23, 2011 at 2:57 AM
Subject: Re: SILT - nice keyvalue store paper
To: dev at hbase.apache.org


I
 was running some similar tests and came across a surprising finding. I 
compared reads and write on ConcurrentSkipListMap ( which the memstore 
uses) and synchronized TreeMap ( Which was literally treemap 
synchronized). Executed concurrent reads, writes and deletes on both of 
them.
Surprisingly synchronized treeMap performed better, though just slightly
 better, than ConcurrentSkipListMap which KeyValueSkipListSet uses.

Here are the output of a few runs

Sometimes the difference was considerable
Using HBaseMap it took 20438ms
Using TreeMap it took 11613ms
Time Difference:8825ms

And sometimes the difference was negligible
Using HBaseMap it took 13370ms
Using TreeMap it took 9482ms
Time Difference:3888ms

I've attaching the test  java file which I wrote to test it. 
This
 might be a very minor differece but still surprising considering the 
fact that ConcurrentSkipListMap uses fancy 2 level indexes which they 
say improves the deletion performance.

And here are the details about the test run.
100 Threads each fetching 10,000 records
100 threads each adding 10,000 records.
100 threads each deletin 10,000 records
( Reads, Writes and deletes simultaneously )

Cheers,
Akash A
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