Tuesday, June 08, 2010

11GR2 Result Cache Scalability

Result Cache in 11GR1

Two years ago I wrote a series of posts where I explained some of the dynamics around Result Cache latch. To recap, the result cache memory in 11GR1 is backed up by a single RC latch. That in itself wouldn't be so much of an issue (at least relatively to what we've got in reality) had the latch allowed for shared mode gets in case all you have to do is read from the result cache memory.

Alas, the latch turned out to be without shared mode gets. It is going almost without saying that, as concurrency levels increased, that single latch was behaving more and more like to a hand brake (link to a test I've done back then on a 8-way Itanium 2).

Back to the future

When 11GR2 has been released I knew that at some point in time I'll need to go back and revisit this subject. What I did is a couple of quick and dirty runs which came back confirming the same single latch and no shared mode gets so it didn't look like something has really changed. At this point I've decided to revisit it a bit later. This a "bit later" happened just recently.

How bad can it get?

What I wanted to do is get an UltraSPARC T2 and face it against Core i7 980X on a different concurrency levels in order to see how bad it can get. T2 will require quite a lot of parallelism in order to keep up even with a single i7 core. But since all we've got is a single RC latch, I've expected T2 to choke on it quite fast as not only there will be a lot of processes competing for the same latch, the slow single-threaded performance will cause the latch to be held for a much longer periods of time. Performance degradation will be dare.

Result Cache in 11GR2

I used the same test described here as it is targeted at exploiting RC latch weakness and gives me the ability to compare with the old results. I've used 250K lookup iterations. The performance was measured as a total number of lookups performed per second and RC latch statistics were captured for analysis.

Since 980X has 6 cores and 12 threads, the tests were done with 1 to 12 processes running at the same time which also gave an opportunity to see how well HT will scale. Note that I plan to do some further testing on T2 with up to 64 threads but for now I've tested up to 12 threads only as I couldn't get a test window big enough.

UltraSPARC T2 Results





























































































# of processes Buffer Cache % linear Result Cache % linear
1 4426 100 4555 100
2 8930 100.88 9124 100.15
3 13465 101.41 13731 100.48
4 17886 101.03 18179 99.77
5 22290 100.72 22715 99.74
6 26615 100.22 27012 98.84
7 30659 98.96 30804 96.61
8 34347 97 34910 95.8
9 38389 96.37 39029 95.2
10 42772 96.64 43126 94.68
11 46840 96.21 46936 93.68
12 50667 95.4 50590 92.55

When I saw these numbers for the first time I was quite surprised just how good these results are! UlstraSPARC T2 end up being far from choking and, as a matter of fact, the only position where Result Cache had to give up is the last one. If you reference the results I've obtained on 8-way Itanium 2 in 11GR1 you'll see that Result Cache gave up much earlier and scaled a lot worse.

This certainly looks promising so let's take a look at the RC latch statistic:






























































































# of processes Gets Misses Sleeps Wait Time
1 500001 0 0 0
2 1000002 40253 1 0
3 1500003 50404 0 0
4 2000004 165116 9 464
5 2500005 211559 5 182
6 3000006 437898 8 6877
7 3500007 805752 52 16556
8 4000008 1214762 20 2980
9 4500009 1775372 188 3140
10 5000010 2244964 491 29568
11 5500011 2552323 664 28011
12 6000012 3019903 1226 60005


There is one astonishing fact about the above number. Let's get some efficiency metrics in place for comparison between these numbers and the ones I've got in 11GR1. I'll use a data point with eight parallel processes as it's the highest reference point I can get across both data sets.

First of all, the number of gets per execution remained the same and equals two gets per exec. If we were going to calculate % miss per get we'll get 28.62% in 11GR1 and 50.33% in 11GR2. In other words, roughly every second get request has resulted in a miss in 11GR2 and every third in 11GR1. It may appear as if this got worse but it's really a consequence from something else.

If we calculate % sleep per miss we'll get 31.36% in 11GR1 but only 0.04% in 11GR2! In other words, the amount of times a process had to go to sleep has drastically decreased. In almost all of the cases the process was able to acquire a latch during a spin without going into a sleep. This also explains why % miss per get in 11GR2 went up and shows that a lowering in efficiency for a single metric does not necessarily indicates a problem, it might happen because some other correlated metric has in fact improved.

There is certainly a sign of a great improvement but what is it? Most likely the improvement is related to the optimization of how long the latch is required to be held. The time required to hold the latch became so small that, in most of the cases, the process is able to acquire it during spinning before being required to go to sleep (i.e. less than _spin_count iterations).

Core i7 980X Results





























































































# of processes Buffer Cache % linear Result Cache % linear
1 40064 100 43554 100
2 78989 98.58 84602 97.12
3 121753 101.3 127768 97.79
4 159490 99.52 166667 95.67
5 194704 97.2 204583 93.94
6 229709 95.56 240770 92.13
7 231788 82.65 244755 80.28
8 233918 72.98 246305 70.69
9 250836 69.57 260718 66.51
10 267094 66.67 275330 63.22
11 280326 63.61 290084 60.55
12 290416 60.41 293830 56.22


Here Result Cache won across all the positions. We need about 10 processes running on UltraSPARC T2 in order to beat a single process running on i7 980X. Performance gains declined rapidly once we got over six concurrent processes but still we were able to realize some additional performance with 12 threads being about 22% faster than 6 threads.

Latch statistics:






























































































# of processes Gets Misses Sleeps Wait Time
1 500001 0 0 0
2 1000002 40456 0 0
3 1500003 117893 5 71
4 2000004 209399 0 0
5 2500005 381160 0 0
6 3000006 517745 11 179
7 3500007 913125 20 555
8 4000008 1355226 26 11914
9 4500009 1834112 13 1017
10 5000010 2602801 42 1607
11 5500011 3196415 145 3451
12 6000012 3730467 184 123954


Essentially we're looking at the same phenomena with the amount of sleeps being significantly lower compared to what we observed in 11GR1. With six concurrent processes % miss per get is 17.26% and % sleep per miss is 0.002%! This allowed Result Cache to stay ahead with up to (and including) 12 concurrent processes running.

UltraSPARC T2 vs i7 980X

We'll wrap up with a nice graph showing result cache performance on both UltraSPARC T2 and Core i7 980X:



i7 980X starts almost where 12 UltraSPARC T2 processes ends. Would T2 be able to narrow the gap with more parallel threads? I'll certainly find out.

Conclusion

There is an enormous improvement when it comes to Result Cache scalability in 11GR2. Still it's slower than if we had shared mode gets (or multiple child latches or, even better, both) but it gets very, very close.

6 comments:

  1. result cache,real cool feature in 11g !

    ReplyDelete
  2. Your blog was recommended by my google reader, and I must say I really like this post!!

    Keep up the technical content!!!

    Regards,
    Magnus Fagertun

    ReplyDelete
  3. hi Alex,
    Loved your post. Really like your older one too.I need to know if can run these test from application where its using hibernate for ORM.
    Also can you share some scripts at hemkant.c@gmail.com which you used for your test runs.

    Regards
    Hemkant Chavan

    ReplyDelete
  4. Anonymous11:31 AM

    As far I know (and able to try), Oracle gets RC latch in shared mode while process is selecting data in 11gR2 (at least in 11.2.0.3)

    Regards
    Pavol Babel

    ReplyDelete
  5. Yes you are correct -- I did another post on the subject later (http://afatkulin.blogspot.ca/2012/05/result-cache-latch-in-11gr2-shared-mode.html)

    ReplyDelete
  6. Anonymous4:24 AM

    I found that blog after I had wrote my post. using "oradebug call kslgetsl_w" is nice trick, however it was not usable for me since I'm mainly on AIX and Solaris64 (AIX never permitted to use oradebug call with function names and Solaris 64bit port introduced bug where oradebug call corrupts input arguments). I've used my dummy old script, however tanel's latchrpofx would be much more smarter nowdays...

    SELECT /*+ ORDERED USE_NL(lh) */
    gen1.sample_id, t1.hsecs, t2.hsecs, lh.*
    FROM (SELECT hsecs FROM v$timer) t1,
    (SELECT rownum sample_id
    FROM DUAL
    CONNECT BY LEVEL <= 1000) gen1,
    X$KSUPRLAT lh,
    (SELECT hsecs FROM v$timer) t2
    /

    One more note, it seems Oracle grabs only one "RC latch" per fetch (aka RC Cache access), at least in 11.2.0.3 again.
    RC latch in shared more is great improvement, however shared latch contention can have great impact, too. If you rewrote your testcase using RESULT_CACHE at PL/SQL function level, the scalability would be under 10% on most platforms (since there is no context switch between PL/SQL and SQL, the iteration is much faster, on the other hand shared latch contention much higher).

    Regards
    Pavol Babel
    OCM 10g/11g

    ReplyDelete