Following PRs are optimization we (Kuaishou) made for machine learning workloads (randomly read billions of small files) . [1] https://github.com/ceph/ceph/pull/39315 [2] https://github.com/ceph/ceph/pull/43126 [3] https://github.com/ceph/ceph/pull/43125 The first PR adds an option that disables dirfrag prefetch. When files are accessed randomly, dirfrag prefetch adds lots of useless files to cache and causes cache thrash. Performance of MDS can be dropped below 100 RPS. When dirfrag prefetch is disabled, MDS sends a getomapval request to rados for cache missed lookup. Single mds can handle about 6k cache missed lookup requests per second (all ssd metadata pool). The second PR optimizes MDS performance for a large number of clients and a large number of read-only opened files. It also can greatly reduce mds recovery time for read-mostly wordload. The third PR makes MDS cluster randomly distribute all dirfrags. MDS uses consistent hash to calculate target rank for each dirfrag. Compared to dynamic balancer and subtree pin, metadata can be distributed among MDSs more evenly. Besides, MDS only migrates single dirfrag (instead of big subtree) for load balancing. So MDS has shorter pause when doing metadata migration. The drawbacks of this change are: stat(2) directory can be slow; rename(2) file to different directory can be slow. The reason is, with random dirfrag distribution, these operations likely involve multiple MDS. Above three PRs are all merged into an integration branch https://github.com/ukernel/ceph/tree/wip-mds-integration. We (Kuaishou) have run these codes for months, 16 active MDS cluster serve billions of small files. In file random read test, single MDS can handle about 6k ops, performance increases linearly with the number of active MDS. In file creation test (mpirun -np 160 -host xxx:160 mdtest -F -L -w 4096 -z 2 -b 10 -I 200 -u -d ...), 16 active MDS can serve over 100k file creation per second. Yan, Zheng _______________________________________________ ceph-users mailing list -- ceph-users@xxxxxxx To unsubscribe send an email to ceph-users-leave@xxxxxxx
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