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Xing Lin commented on HDFS-14703: --------------------------------- I did some performance benchmarks using a physical server (a d430 server in [utah Emulab testbed|[www.emulab.net].) |http://www.emulab.net].%29/]I used either RAMDISK or SSD, as the storage for HDFS. By using RAMDISK, we can remove the time used by the SSD to make each write persistent. For the RAM case, we observed an improvement of 45% from fine-grained locking. For the SSD case, fine-grained locking gives us 20% improvement. We used an Intel SSD (model: SSDSC2BX200G4R). We noticed for trunk, the mkdir OPS is lower for the RAMDISK than SSD. We don't know the reason for this yet. We repeated the experiment for RAMDISK for trunk twice to confirm the performance number. h1. tmpfs, hadoop-tmp-dir = /run/hadoop-utos h1. 45% improvements fgl vs. trunk h2. trunk 2021-05-16 20:37:20,280 INFO namenode.NNThroughputBenchmark: # operations: 10000000 2021-05-16 20:37:20,280 INFO namenode.NNThroughputBenchmark: Elapsed Time: 663510 2021-05-16 20:37:20,280 INFO namenode.NNThroughputBenchmark: Ops per sec: 15071.362 2021-05-16 20:37:20,280 INFO namenode.NNThroughputBenchmark: Average Time: 13 2021-05-16 22:15:13,515 INFO namenode.NNThroughputBenchmark: --- mkdirs stats --- 2021-05-16 22:15:13,515 INFO namenode.NNThroughputBenchmark: # operations: 10000000 2021-05-16 22:15:13,515 INFO namenode.NNThroughputBenchmark: Elapsed Time: 710248 2021-05-16 22:15:13,515 INFO namenode.NNThroughputBenchmark: Ops per sec: 14079.5 2021-05-16 22:15:13,515 INFO namenode.NNThroughputBenchmark: Average Time: 14 2021-05-16 22:15:13,515 INFO namenode.FSEditLog: Ending log segment 8345565, 10019540 fgl 2021-05-16 21:06:46,476 INFO namenode.NNThroughputBenchmark: --- mkdirs stats --- 2021-05-16 21:06:46,476 INFO namenode.NNThroughputBenchmark: # operations: 10000000 2021-05-16 21:06:46,476 INFO namenode.NNThroughputBenchmark: Elapsed Time: 445980 2021-05-16 21:06:46,476 INFO namenode.NNThroughputBenchmark: Ops per sec: 22422.530 2021-05-16 21:06:46,476 INFO namenode.NNThroughputBenchmark: Average Time: 8 h1. SSD, hadoop.tmp.dir=/dev/sda4 h1. 23% improvement fgl vs. trunk trunk: 2021-05-16 21:59:06,042 INFO namenode.NNThroughputBenchmark: --- mkdirs stats --- 2021-05-16 21:59:06,042 INFO namenode.NNThroughputBenchmark: # operations: 10000000 2021-05-16 21:59:06,042 INFO namenode.NNThroughputBenchmark: Elapsed Time: 593839 2021-05-16 21:59:06,042 INFO namenode.NNThroughputBenchmark: Ops per sec: 16839.581 2021-05-16 21:59:06,042 INFO namenode.NNThroughputBenchmark: Average Time: 11 fgl 2021-05-16 21:21:03,906 INFO namenode.NNThroughputBenchmark: --- mkdirs stats --- 2021-05-16 21:21:03,906 INFO namenode.NNThroughputBenchmark: # operations: 10000000 2021-05-16 21:21:03,906 INFO namenode.NNThroughputBenchmark: Elapsed Time: 481269 2021-05-16 21:21:03,906 INFO namenode.NNThroughputBenchmark: Ops per sec: 20778.400 2021-05-16 21:21:03,906 INFO namenode.NNThroughputBenchmark: Average Time: 9 /dev/sda: ATA device, with non-removable media Model Number: INTEL SSDSC2BX200G4R Serial Number: BTHC523202RD200TGN Firmware Revision: G201DL2D > NameNode Fine-Grained Locking via Metadata Partitioning > ------------------------------------------------------- > > Key: HDFS-14703 > URL: https://issues.apache.org/jira/browse/HDFS-14703 > Project: Hadoop HDFS > Issue Type: Improvement > Components: hdfs, namenode > Reporter: Konstantin Shvachko > Priority: Major > Attachments: 001-partitioned-inodeMap-POC.tar.gz, > 002-partitioned-inodeMap-POC.tar.gz, 003-partitioned-inodeMap-POC.tar.gz, > NameNode Fine-Grained Locking.pdf, NameNode Fine-Grained Locking.pdf > > > We target to enable fine-grained locking by splitting the in-memory namespace > into multiple partitions each having a separate lock. Intended to improve > performance of NameNode write operations. -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: hdfs-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: hdfs-issues-h...@hadoop.apache.org