Hi Sage and Mark, A question here: OMAP pg logs are added by "set", are they only deleted by rm_range_keys in BlueStore? https://github.com/ceph/ceph/pull/18279/files If yes, maybe when dedup, we don't need to compare the keys in all memtables, we just compare keys in current memtable with rm_range_keys in later memtables? On Tue, Oct 17, 2017 at 10:18 AM, xiaoyan li <wisher2003@xxxxxxxxx> wrote: > Hi Sage and Mark, > Following tests results I give are tested based on KV sequences got > from librbd+fio 4k or 16k random writes in 30 mins. > In my opinion, we may use dedup flush style for onodes and deferred > data, but use default merge flush style for other data. > > On Mon, Oct 16, 2017 at 9:50 PM, Mark Nelson <mnelson@xxxxxxxxxx> wrote: >> >> >> On 10/16/2017 08:28 AM, Sage Weil wrote: >>> >>> [adding ceph-devel] >>> >>> On Mon, 16 Oct 2017, Mark Nelson wrote: >>>> >>>> Hi Lisa, >>>> >>>> Excellent testing! This is exactly what we were trying to understand. >>>> >>>> On 10/16/2017 12:55 AM, Li, Xiaoyan wrote: >>>>> >>>>> Hi Mark, >>>>> >>>>> Based on my testing, when setting min_write_buffer_number_to_merge as 2, >>>>> the >>>>> onodes and deferred data written into L0 SST can decreased a lot with my >>>>> rocksdb dedup package. >>>>> >>>>> But for omap data, it needs to span more memtables. I tested omap data >>>>> in >>>>> separate column family. From the data, you can see when >>>>> min_write_buffer_number_to_merge is set to 4, the data written into L0 >>>>> SST >>>>> is good. That means it has to compare current memTable to flush with >>>>> later 3 >>>>> memtables recursively. >>>>> kFlushStyleDedup is to new flush style in my rocksdb dedup package. >>>>> kFlushStyleMerge is current flush style in master branch. >>>>> >>>>> But this is just considered from data written into L0. With more >>>>> memtables >>>>> to compare, it sacrifices CPU and computing time. >>>>> >>>>> Memtable size: 256MB >>>>> max_write_buffer_number min_write_buffer_number_to_merge >>>>> flush_style Omap data written into L0 SST(unit: MB) >>>>> 16 8 kFlushStyleMerge 7665 >>>>> 16 8 kFlushStyleDedup 3770 >>>>> 8 4 kFlushStyleMerge 11470 >>>>> 8 4 kFlushStyleDedup 3922 >>>>> 6 3 kFlushStyleMerge 14059 >>>>> 6 3 kFlushStyleDedup 5001 >>>>> 4 2 kFlushStyleMerge 18683 >>>>> 4 2 kFlushStyleDedup 15394 >>>> >>>> >>>> Is this only omap data or all data? It looks like the 6/3 or 8/4 is >>>> still >>>> probably the optimal point (And the improvements are quite noticeable!). > This is only omap data. Dedup can decrease data written into L0 SST, > but it needs to compare too many memtables. > >>>> Sadly we were hoping we might be able to get away with smaller memtables >>>> (say >>>> 64MB) with KFlushStyleDedup. It looks like that might not be the case >>>> unless >>>> we increase the number very high. >>>> >>>> Sage, this is going to be even worse if we try to keep more pglog entries >>>> around on flash OSD backends? >>> >>> >>> I think there are three or more factors at play here: >>> >>> 1- If we reduce the memtable size, the CPU cost of insertion (baseline) >>> and the dedup cost will go down. >>> >>> 2- If we switch to a small min pg log entries, then most pg log keys >>> *will* fall into the smaller window (of small memtables * small >>> min_write_buffer_to_merge). The dup op keys probably won't, though... >>> except maybe they will because the values are small and more of them will >>> fit into the memtables. But then >>> >>> 3- If we have more keys and smaller values, then the CPU overhead will be >>> higher again. >>> >>> For PG logs, I didn't really expect that the dedup style would help; I was >>> only thinking about the deferred keys. I wonder if it would make sense to >>> specify a handful of key prefixes to attempt dedup on, and not bother on >>> the others? >> >> >> Deferred keys seem to be a much smaller part of the problem right now than >> pglog. At least based on what I'm seeing at the moment with NVMe testing. >> Regarding dedup, it's probably worth testing at the very least. > I did following tests: all data in default column family. Set > min_write_buffer_to_merge to 2, check the size of kinds of data > written into L0 SST files. > From the data, onodes and deferred data can be removed a lot in dedup style. > > Data written into L0 SST files: > > 4k random writes (unit: MB) > FlushStyle Omap onodes deferred others > merge 22431.56 23224.54 1530.105 0.906106 > dedup 22188.28 14161.18 12.68681 0.90906 > > 16k random writes (unit: MB) > FlushStyle Omap onodes deferred others > merge 19260.20 8230.02 0 1914.50 > dedup 19154.92 2603.90 0 > 2517.15 > > Note here: for others type, which use "merge" operation, dedup style > can't make it more efficient. In later, we can set it in separate CF, > use default merge flush style. > >> >>> >>> Also, there is the question of where the CPU time is spent. >> >> >> Indeed, but if we can reduce the memtable size it means we save CPU in other >> areas. Like you say below, it's complicated. >>> >>> >>> 1- Big memtables means we spend more time in submit_transaction, called by >>> the kv_sync_thread, which is a bottleneck. >> >> >> At least on NVMe we see it pretty regularly in the wallclock traces. I need >> to retest with Radoslav and Adam's hugepages PR to get a feel for how bad it >> is after that. >> >>> >>> 2- Higher dedup style flush CPU usage is spent in the compaction thread(s) >>> (I think?), which are asynchronous. >> >> >> L0 compaction is single threaded though so we must be careful.... >> >>> >>> At the end of the day I think we need to use less CPU total, so the >>> optimization of the above factors is a bit complicated. OTOH if the goal >>> is IOPS at whatever cost it'll probably mean a slightly different choice. >> >> >> I guess we should consider the trends. Lots of cores, lots of flash cells. >> How do we balance high throughput and low latency? >> >>> >>> I would *expect* that if we go from, say, 256mb tables to 64mb tables and >>> dedup of <= 4 of them, then we'll see a modest net reduction of total CPU >>> *and* a shift to the compaction threads. >> >> >> It seems like based on Lisa's test results that's too short lived? Maybe I'm >> not understanding what you mean? >> >>> >>> And changing the pg log min entries will counterintuitively increase the >>> costs of insertion and dedup flush because more keys will fit in the same >>> amount of memtable... but if we reduce the memtable size at the same time >>> we might get a win there too? Maybe? >> >> >> There's too much variability here to theorycraft it and your "maybe" >> statement confirms for me. ;) We need to get a better handle on what's >> going on. >> >>> >>> Lisa, do you think limiting the dedup check during flush to specific >>> prefixes would make sense as a general capability? If so, we could target >>> this *just* at the high-value keys (e.g., deferred writes) and avoid >>> incurring very much additional overhead for the key ranges that aren't >>> sure bets. > The easiest way to do it is to set data in different CFs, and use > different flush style(dedup or merge) in different CFs. > >> >> >> At least in my testing deferred writes during rbd 4k random writes are >> almost negligible: >> >> http://pad.ceph.com/p/performance_weekly >> >> I suspect it's all going to be about OMAP. We need a really big WAL that >> can keep OMAP around for a long time while quickly flushing object data into >> small memtables. On disk it's a big deal that this gets layed out >> sequentially but on flash I'm wondering if we'd be better off with a >> separate WAL for OMAP (a different rocksdb shard or different data store >> entirely). > Yes, OMAP data is main data written into L0 SST. > > Data written into every memtable: (uint: MB) > IO load omap ondes deferred others > 4k RW 37584 85253 323887 250 > 16k RW 33687 73458 0 3500 > > In merge flush style with min_buffer_to_merge=2. > Data written into every L0 SST: (unit MB) > IO load Omap onodes deferred others > 4k RW 22188.28 14161.18 12.68681 0.90906 > 16k RW 19260.20 8230.02 0 1914.50 > >> >> Mark >> >> >>> >>> sage >>> >>> >>>>> The above KV operation sequences come from 4k random writes in 30mins. >>>>> Overall, the Rocksdb dedup package can decrease the data written into L0 >>>>> SST, but it needs more comparison. In my opinion, whether to use dedup, >>>>> it >>>>> depends on the configuration of the OSD host: whether disk is over busy >>>>> or >>>>> CPU is over busy. >>>> >>>> >>>> Do you have any insight into how much CPU overhead it adds? >>>> >>>>> >>>>> Best wishes >>>>> Lisa >> >> -- >> 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 > > > > -- > Best wishes > Lisa -- Best wishes Lisa -- 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
