> Do you have the system sharing There are 2 HDD 7200 2TB each. There is 300GB OS partition on each drive with mirroring enabled. I can't persuade devops that mirroring could cause IO issues. What arguments can I bring? They use OS partition mirroring when disck fails, we can use other partition to boot OS and continue to work...
>Do you have to compact? In other words, do you have read SLAs? Unfortunately, I have mixed workload from web applications. I need to write and read and SLA is < 50ms. >How are your read times currently? Cloudera manager says it's 4K reads per second and 500 writes per second >Does your working dataset fit in RAM or do reads have to go to disk? I have several tables for 500GB each and many small tables 10-20 GB. Small tables loaded hourly/daily using bulkload (prepare HFiles using MR and move them to HBase using utility). Big tables are used by webapps, they read and write them. >It looks like you are running at about three storefiles per column family is it hbase.hstore.compactionThreshold=3? >What if you upped the threshold at which minors run? you mean bump hbase.hstore.compactionThreshold to 8 or 10? >Do you have a downtime during which you could schedule compactions? Unfortunately no. It should work 24/7 and sometimes it doesn't do it. >Are you managing the major compactions yourself or are you having hbase do it for you? HBase, once a day hbase.hregion.majorcompaction=1day I can disable WAL. It's ok to loose some data in case of RS failure. I'm not doing banking transactions. If I disable WAL, could it help? 2015-05-20 18:04 GMT+03:00 Stack <st...@duboce.net>: > On Mon, May 18, 2015 at 4:26 PM, Serega Sheypak <serega.shey...@gmail.com> > wrote: > > > Hi, we are using extremely cheap HW: > > 2 HHD 7200 > > 4*2 core (Hyperthreading) > > 32GB RAM > > > > We met serious IO performance issues. > > We have more or less even distribution of read/write requests. The same > for > > datasize. > > > > ServerName Request Per Second Read Request Count Write Request Count > > node01.domain.com,60020,1430172017193 195 171871826 16761699 > > node02.domain.com,60020,1426925053570 24 34314930 16006603 > > node03.domain.com,60020,1430860939797 22 32054801 16913299 > > node04.domain.com,60020,1431975656065 33 1765121 253405 > > node05.domain.com,60020,1430484646409 27 42248883 16406280 > > node07.domain.com,60020,1426776403757 27 36324492 16299432 > > node08.domain.com,60020,1426775898757 26 38507165 13582109 > > node09.domain.com,60020,1430440612531 27 34360873 15080194 > > node11.domain.com,60020,1431989669340 28 44307 13466 > > node12.domain.com,60020,1431927604238 30 5318096 2020855 > > node13.domain.com,60020,1431372874221 29 31764957 15843688 > > node14.domain.com,60020,1429640630771 41 36300097 13049801 > > > > ServerName Num. Stores Num. Storefiles Storefile Size Uncompressed > > Storefile > > Size Index Size Bloom Size > > node01.domain.com,60020,1430172017193 82 186 1052080m 76496mb 641849k > > 310111k > > node02.domain.com,60020,1426925053570 82 179 1062730m 79713mb 649610k > > 318854k > > node03.domain.com,60020,1430860939797 82 179 1036597m 76199mb 627346k > > 307136k > > node04.domain.com,60020,1431975656065 82 400 1034624m 76405mb 655954k > > 289316k > > node05.domain.com,60020,1430484646409 82 185 1111807m 81474mb 688136k > > 334127k > > node07.domain.com,60020,1426776403757 82 164 1023217m 74830mb 631774k > > 296169k > > node08.domain.com,60020,1426775898757 81 171 1086446m 79933mb 681486k > > 312325k > > node09.domain.com,60020,1430440612531 81 160 1073852m 77874mb 658924k > > 309734k > > node11.domain.com,60020,1431989669340 81 166 1006322m 75652mb 664753k > > 264081k > > node12.domain.com,60020,1431927604238 82 188 1050229m 75140mb 652970k > > 304137k > > node13.domain.com,60020,1431372874221 82 178 937557m 70042mb 601684k > > 257607k > > node14.domain.com,60020,1429640630771 82 145 949090m 69749mb 592812k > > 266677k > > > > > > When compaction starts random node gets I/O 100%, io wait for seconds, > > even tenth of seconds. > > > > What are the approaches to optimize minor and major compactions when you > > are I/O bound..? > > > > Yeah, with two disks, you will be crimped. Do you have the system sharing > with hbase/hdfs or is hdfs running on one disk only? > > Do you have to compact? In other words, do you have read SLAs? How are > your read times currently? Does your working dataset fit in RAM or do > reads have to go to disk? It looks like you are running at about three > storefiles per column family. What if you upped the threshold at which > minors run? Do you have a downtime during which you could schedule > compactions? Are you managing the major compactions yourself or are you > having hbase do it for you? > > St.Ack >