On 02/13/2017 08:16 PM, Sage Weil wrote: > On Mon, 13 Feb 2017, Loic Dachary wrote: >> Hi Sage, >> >> I wrote a little program to show where objects are moving when a new disk is added (disk 10 below) and it looks like this: >> >> 00 01 02 03 04 05 06 07 08 09 10 >> 00: 0 14 17 14 19 23 13 22 21 20 1800 >> 01: 12 0 11 13 19 19 15 10 16 17 1841 >> 02: 17 27 0 17 15 15 13 19 18 11 1813 >> 03: 14 17 15 0 23 11 20 15 23 17 1792 >> 04: 14 18 16 25 0 27 13 8 15 16 1771 >> 05: 19 16 22 25 13 0 9 19 21 21 1813 >> 06: 18 15 21 17 10 18 0 10 18 11 1873 >> 07: 13 17 22 13 16 17 14 0 25 12 1719 >> 08: 23 20 16 17 19 18 11 12 0 18 1830 >> 09: 14 20 15 17 12 16 17 11 13 0 1828 >> 10: 0 0 0 0 0 0 0 0 0 0 0 >> >> before: 20164 19990 19863 19959 19977 20004 19926 20133 20041 19943 0 >> after: 18345 18181 18053 18170 18200 18190 18040 18391 18227 18123 18080 >> >> >> Each line shows how many objects moved from a given disk to the others >> after disk 10 was added. Most objects go to the new disk and around 1% >> go to each other disks. The before and after lines show how many objects >> are mapped to each disk. They all have the same weight and it's using >> replica 2 and straw2. Does that look right ? > > Hmm, that doesn't look right. This is what the CRUSH.straw2_reweight unit > test is there to validate: that data on moves to or from the device whose > weight changed. In the above, the bucket size changes: it has a new item. And the bucket size plays a role in bucket_straw2_choose because it loops on all items. In CRUSH.straw2_reweight only the weights change. I'm not entirely sure how that would explain the results I get though... > It also follows from the straw2 algorithm itself: each possible choice > gets a 'straw' length derived only from that item's weight (and other > fixed factors, like the item id and the bucket id), and we select the max > across all items. Two devices whose weights didn't change will have the > same straw lengths, and the max between them will not change. It's only > possible that the changed item's straw length changed and wasn't max and > now is (got longer) or was max and now isn't (got shorter). That's a crystal clear explanation, cool :-) Cheers > sage > > >> >> Cheers >> >> On 02/13/2017 03:21 PM, Sage Weil wrote: >>> On Mon, 13 Feb 2017, Loic Dachary wrote: >>>> Hi, >>>> >>>> Dan van der Ster reached out to colleagues and friends and Pedro >>>> López-Adeva Fernández-Layos came up with a well written analysis of the >>>> problem and a tentative solution which he described at : >>>> https://github.com/plafl/notebooks/blob/master/replication.ipynb >>>> >>>> Unless I'm reading the document incorrectly (very possible ;) it also >>>> means that the probability of each disk needs to take in account the >>>> weight of all disks. Which means that whenever a disk is added / removed >>>> or its weight is changed, this has an impact on the probability of all >>>> disks in the cluster and objects are likely to move everywhere. Am I >>>> mistaken ? >>> >>> Maybe (I haven't looked closely at the above yet). But for comparison, in >>> the normal straw2 case, adding or removing a disk also changes the >>> probabilities for everything else (e.g., removing one out of 10 identical >>> disks changes the probability from 1/10 to 1/9). The key property that >>> straw2 *is* able to handle is that as long as the relative probabilities >>> between two unmodified disks does not change, then straw2 will avoid >>> moving any objects between them (i.e., all data movement is to or from >>> the disk that is reweighted). >>> >>> sage >>> >>> >>>> >>>> Cheers >>>> >>>> On 01/26/2017 04:05 AM, Sage Weil wrote: >>>>> This is a longstanding bug, >>>>> >>>>> http://tracker.ceph.com/issues/15653 >>>>> >>>>> that causes low-weighted devices to get more data than they should. Loic's >>>>> recent activity resurrected discussion on the original PR >>>>> >>>>> https://github.com/ceph/ceph/pull/10218 >>>>> >>>>> but since it's closed and almost nobody will see it I'm moving the >>>>> discussion here. >>>>> >>>>> The main news is that I have a simple adjustment for the weights that >>>>> works (almost perfectly) for the 2nd round of placements. The solution is >>>>> pretty simple, although as with most probabilities it tends to make my >>>>> brain hurt. >>>>> >>>>> The idea is that, on the second round, the original weight for the small >>>>> OSD (call it P(pick small)) isn't what we should use. Instead, we want >>>>> P(pick small | first pick not small). Since P(a|b) (the probability of a >>>>> given b) is P(a && b) / P(b), >>>>> >>>>> P(pick small | first pick not small) >>>>> = P(pick small && first pick not small) / P(first pick not small) >>>>> >>>>> The last term is easy to calculate, >>>>> >>>>> P(first pick not small) = (total_weight - small_weight) / total_weight >>>>> >>>>> and the && term is the distribution we're trying to produce. For exmaple, >>>>> if small has 1/10 the weight, then we should see 1/10th of the PGs have >>>>> their second replica be the small OSD. So >>>>> >>>>> P(pick small && first pick not small) = small_weight / total_weight >>>>> >>>>> Putting those together, >>>>> >>>>> P(pick small | first pick not small) >>>>> = P(pick small && first pick not small) / P(first pick not small) >>>>> = (small_weight / total_weight) / ((total_weight - small_weight) / total_weight) >>>>> = small_weight / (total_weight - small_weight) >>>>> >>>>> This is, on the second round, we should adjust the weights by the above so >>>>> that we get the right distribution of second choices. It turns out it >>>>> works to adjust *all* weights like this to get hte conditional probability >>>>> that they weren't already chosen. >>>>> >>>>> I have a branch that hacks this into straw2 and it appears to work >>>>> properly for num_rep = 2. With a test bucket of [99 99 99 99 4], and the >>>>> current code, you get >>>>> >>>>> $ bin/crushtool -c cm.txt --test --show-utilization --min-x 0 --max-x 40000000 --num-rep 2 >>>>> rule 0 (data), x = 0..40000000, numrep = 2..2 >>>>> rule 0 (data) num_rep 2 result size == 2: 40000001/40000001 >>>>> device 0: 19765965 [9899364,9866601] >>>>> device 1: 19768033 [9899444,9868589] >>>>> device 2: 19769938 [9901770,9868168] >>>>> device 3: 19766918 [9898851,9868067] >>>>> device 6: 929148 [400572,528576] >>>>> >>>>> which is very close for the first replica (primary), but way off for the >>>>> second. With my hacky change, >>>>> >>>>> rule 0 (data), x = 0..40000000, numrep = 2..2 >>>>> rule 0 (data) num_rep 2 result size == 2: 40000001/40000001 >>>>> device 0: 19797315 [9899364,9897951] >>>>> device 1: 19799199 [9899444,9899755] >>>>> device 2: 19801016 [9901770,9899246] >>>>> device 3: 19797906 [9898851,9899055] >>>>> device 6: 804566 [400572,403994] >>>>> >>>>> which is quite close, but still skewing slightly high (by a big less than >>>>> 1%). >>>>> >>>>> Next steps: >>>>> >>>>> 1- generalize this for >2 replicas >>>>> 2- figure out why it skews high >>>>> 3- make this work for multi-level hierarchical descent >>>>> >>>>> sage >>>>> >>>>> -- >>>>> To unsubscribe from this list: send the line "unsubscribe ceph-devel" in >>>>> the body of a message to majordomo@xxxxxxxxxxxxxxx >>>>> More majordomo info at http://vger.kernel.org/majordomo-info.html >>>>> >>>> >>>> -- >>>> Loïc Dachary, Artisan Logiciel Libre >>>> -- >>>> To unsubscribe from this list: send the line "unsubscribe ceph-devel" in >>>> the body of a message to majordomo@xxxxxxxxxxxxxxx >>>> More majordomo info at http://vger.kernel.org/majordomo-info.html >>>> >> >> -- >> Loïc Dachary, Artisan Logiciel Libre -- Loïc Dachary, Artisan Logiciel Libre -- To unsubscribe from this list: send the line "unsubscribe ceph-devel" in the body of a message to majordomo@xxxxxxxxxxxxxxx More majordomo info at http://vger.kernel.org/majordomo-info.html
