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authorJohannes Weiner <hannes@cmpxchg.org>2014-04-03 14:47:34 -0700
committerLinus Torvalds <torvalds@linux-foundation.org>2014-04-03 16:21:00 -0700
commit6a3ed2123a78de22a9e2b2855068a8d89f8e14f4 (patch)
tree6ae701db81d3996752761bcf600008ba5abcc446 /lib/Kconfig.kgdb
parentd5bc5fd3fcb7b8dfb431694a8c8052466504c10c (diff)
mm: vmstat: fix UP zone state accounting
Summary: The VM maintains cached filesystem pages on two types of lists. One list holds the pages recently faulted into the cache, the other list holds pages that have been referenced repeatedly on that first list. The idea is to prefer reclaiming young pages over those that have shown to benefit from caching in the past. We call the recently used list "inactive list" and the frequently used list "active list". Currently, the VM aims for a 1:1 ratio between the lists, which is the "perfect" trade-off between the ability to *protect* frequently used pages and the ability to *detect* frequently used pages. This means that working set changes bigger than half of cache memory go undetected and thrash indefinitely, whereas working sets bigger than half of cache memory are unprotected against used-once streams that don't even need caching. This happens on file servers and media streaming servers, where the popular files and file sections change over time. Even though the individual files might be smaller than half of memory, concurrent access to many of them may still result in their inter-reference distance being greater than half of memory. It's also been reported as a problem on database workloads that switch back and forth between tables that are bigger than half of memory. In these cases the VM never recognizes the new working set and will for the remainder of the workload thrash disk data which could easily live in memory. Historically, every reclaim scan of the inactive list also took a smaller number of pages from the tail of the active list and moved them to the head of the inactive list. This model gave established working sets more gracetime in the face of temporary use-once streams, but ultimately was not significantly better than a FIFO policy and still thrashed cache based on eviction speed, rather than actual demand for cache. This series solves the problem by maintaining a history of pages evicted from the inactive list, enabling the VM to detect frequently used pages regardless of inactive list size and facilitate working set transitions. Tests: The reported database workload is easily demonstrated on a 8G machine with two filesets a 6G. This fio workload operates on one set first, then switches to the other. The VM should obviously always cache the set that the workload is currently using. This test is based on a problem encountered by Citus Data customers: http://citusdata.com/blog/72-linux-memory-manager-and-your-big-data unpatched: db1: READ: io=98304MB, aggrb=885559KB/s, minb=885559KB/s, maxb=885559KB/s, mint= 113672msec, maxt= 113672msec db2: READ: io=98304MB, aggrb= 66169KB/s, minb= 66169KB/s, maxb= 66169KB/s, mint=1521302msec, maxt=1521302msec sdb: ios=835750/4, merge=2/1, ticks=4659739/60016, in_queue=4719203, util=98.92% real 27m15.541s user 0m19.059s sys 0m51.459s patched: db1: READ: io=98304MB, aggrb=877783KB/s, minb=877783KB/s, maxb=877783KB/s, mint=114679msec, maxt=114679msec db2: READ: io=98304MB, aggrb=397449KB/s, minb=397449KB/s, maxb=397449KB/s, mint=253273msec, maxt=253273msec sdb: ios=170587/4, merge=2/1, ticks=954910/61123, in_queue=1015923, util=90.40% real 6m8.630s user 0m14.714s sys 0m31.233s As can be seen, the unpatched kernel simply never adapts to the workingset change and db2 is stuck indefinitely with secondary storage speed. The patched kernel needs 2-3 iterations over db2 before it replaces db1 and reaches full memory speed. Given the unbounded negative affect of the existing VM behavior, these patches should be considered correctness fixes rather than performance optimizations. Another test resembles a fileserver or streaming server workload, where data in excess of memory size is accessed at different frequencies. There is very hot data accessed at a high frequency. Machines should be fitted so that the hot set of such a workload can be fully cached or all bets are off. Then there is a very big (compared to available memory) set of data that is used-once or at a very low frequency; this is what drives the inactive list and does not really benefit from caching. Lastly, there is a big set of warm data in between that is accessed at medium frequencies and benefits from caching the pages between the first and last streamer of each burst. unpatched: hot: READ: io=128000MB, aggrb=160693KB/s, minb=160693KB/s, maxb=160693KB/s, mint=815665msec, maxt=815665msec warm: READ: io= 81920MB, aggrb=109853KB/s, minb= 27463KB/s, maxb= 29244KB/s, mint=717110msec, maxt=763617msec cold: READ: io= 30720MB, aggrb= 35245KB/s, minb= 35245KB/s, maxb= 35245KB/s, mint=892530msec, maxt=892530msec sdb: ios=797960/4, merge=11763/1, ticks=4307910/796, in_queue=4308380, util=100.00% patched: hot: READ: io=128000MB, aggrb=160678KB/s, minb=160678KB/s, maxb=160678KB/s, mint=815740msec, maxt=815740msec warm: READ: io= 81920MB, aggrb=147747KB/s, minb= 36936KB/s, maxb= 40960KB/s, mint=512000msec, maxt=567767msec cold: READ: io= 30720MB, aggrb= 40960KB/s, minb= 40960KB/s, maxb= 40960KB/s, mint=768000msec, maxt=768000msec sdb: ios=596514/4, merge=9341/1, ticks=2395362/997, in_queue=2396484, util=79.18% In both kernels, the hot set is propagated to the active list and then served from cache. In both kernels, the beginning of the warm set is propagated to the active list as well, but in the unpatched case the active list eventually takes up half of memory and no new pages from the warm set get activated, despite repeated access, and despite most of the active list soon being stale. The patched kernel on the other hand detects the thrashing and manages to keep this cache window rolling through the data set. This frees up enough IO bandwidth that the cold set is served at full speed as well and disk utilization even drops by 20%. For reference, this same test was performed with the traditional demotion mechanism, where deactivation is coupled to inactive list reclaim. However, this had the same outcome as the unpatched kernel: while the warm set does indeed get activated continuously, it is forced out of the active list by inactive list pressure, which is dictated primarily by the unrelated cold set. The warm set is evicted before subsequent streamers can benefit from it, even though there would be enough space available to cache the pages of interest. Costs: Page reclaim used to shrink the radix trees but now the tree nodes are reused for shadow entries, where the cost depends heavily on the page cache access patterns. However, with workloads that maintain spatial or temporal locality, the shadow entries are either refaulted quickly or reclaimed along with the inode object itself. Workloads that will experience a memory cost increase are those that don't really benefit from caching in the first place. A more predictable alternative would be a fixed-cost separate pool of shadow entries, but this would incur relatively higher memory cost for well-behaved workloads at the benefit of cornercases. It would also make the shadow entry lookup more costly compared to storing them directly in the cache structure. Future: To simplify the merging process, this patch set is implementing thrash detection on a global per-zone level only for now, but the design is such that it can be extended to memory cgroups as well. All we need to do is store the unique cgroup ID along the node and zone identifier inside the eviction cookie to identify the lruvec. Right now we have a fixed ratio (50:50) between inactive and active list but we already have complaints about working sets exceeding half of memory being pushed out of the cache by simple streaming in the background. Ultimately, we want to adjust this ratio and allow for a much smaller inactive list. These patches are an essential step in this direction because they decouple the VMs ability to detect working set changes from the inactive list size. This would allow us to base the inactive list size on the combined readahead window size for example and potentially protect a much bigger working set. It's also a big step towards activating pages with a reuse distance larger than memory, as long as they are the most frequently used pages in the workload. This will require knowing more about the access frequency of active pages than what we measure right now, so it's also deferred in this series. Another possibility of having thrashing information would be to revisit the idea of local reclaim in the form of zero-config memory control groups. Instead of having allocating tasks go straight to global reclaim, they could try to reclaim the pages in the memcg they are part of first as long as the group is not thrashing. This would allow a user to drop e.g. a back-up job in an otherwise unconfigured memcg and it would only inflate (and possibly do global reclaim) until it has enough memory to do proper readahead. But once it reaches that point and stops thrashing it would just recycle its own used-once pages without kicking out the cache of any other tasks in the system more than necessary. This patch (of 10): Fengguang Wu's build testing spotted problems with inc_zone_state() and dec_zone_state() on UP configurations in out-of-tree patches. inc_zone_state() is declared but not defined, dec_zone_state() is missing entirely. Just like with *_zone_page_state(), they can be defined like their preemption-unsafe counterparts on UP. [akpm@linux-foundation.org: make it build] Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Bob Liu <bob.liu@oracle.com> Cc: Christoph Hellwig <hch@infradead.org> Cc: Dave Chinner <david@fromorbit.com> Cc: Greg Thelen <gthelen@google.com> Cc: Hugh Dickins <hughd@google.com> Cc: Jan Kara <jack@suse.cz> Cc: KOSAKI Motohiro <kosaki.motohiro@jp.fujitsu.com> Cc: Luigi Semenzato <semenzato@google.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Metin Doslu <metin@citusdata.com> Cc: Michel Lespinasse <walken@google.com> Cc: Minchan Kim <minchan.kim@gmail.com> Cc: Ozgun Erdogan <ozgun@citusdata.com> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rik van Riel <riel@redhat.com> Cc: Roman Gushchin <klamm@yandex-team.ru> Cc: Ryan Mallon <rmallon@gmail.com> Cc: Tejun Heo <tj@kernel.org> Cc: Vlastimil Babka <vbabka@suse.cz> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
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