I have used the following site: http://grokbase.com/t/hbase/user/11bat80x7m/row-get-very-slow
to lessen the value of block cache. -Vibhav On Mon, Apr 1, 2013 at 4:23 PM, Ted <[email protected]> wrote: > Can you increase block cache size ? > > What version of hbase are you using ? > > Thanks > > On Apr 1, 2013, at 3:47 AM, Vibhav Mundra <[email protected]> wrote: > > > The typical size of each of my row is less than 1KB. > > > > Regarding the memory, I have used 8GB for Hbase regionservers and 4 GB > for > > datanodes and I dont see them completely used. So I ruled out the GC > aspect. > > > > In case u still believe that GC is an issue, I will upload the gc logs. > > > > -Vibhav > > > > > > On Mon, Apr 1, 2013 at 3:46 PM, ramkrishna vasudevan < > > [email protected]> wrote: > > > >> Hi > >> > >> How big is your row? Are they wider rows and what would be the size of > >> every cell? > >> How many read threads are getting used? > >> > >> > >> Were you able to take a thread dump when this was happening? Have you > seen > >> the GC log? > >> May be need some more info before we can think of the problem. > >> > >> Regards > >> Ram > >> > >> > >> On Mon, Apr 1, 2013 at 3:39 PM, Vibhav Mundra <[email protected]> wrote: > >> > >>> Hi All, > >>> > >>> I am trying to use Hbase for real-time data retrieval with a timeout of > >> 50 > >>> ms. > >>> > >>> I am using 2 machines as datanode and regionservers, > >>> and one machine as a master for hadoop and Hbase. > >>> > >>> But I am able to fire only 3000 queries per sec and 10% of them are > >> timing > >>> out. > >>> The database has 60 million rows. > >>> > >>> Are these figure okie, or I am missing something. > >>> I have used the scanner caching to be equal to one, because for each > time > >>> we are fetching a single row only. > >>> > >>> Here are the various configurations: > >>> > >>> *Our schema > >>> *{NAME => 'mytable', FAMILIES => [{NAME => 'cf', DATA_BLOCK_ENCODING => > >>> 'NONE', BLOOMFILTER => 'ROWCOL', REPLICATION_SCOPE => '0', COMPRESSION > => > >>> 'GZ', VERSIONS => '1', TTL => '2147483647', MIN_VERSIONS => '0', KEE > >>> P_DELETED_CELLS => 'false', BLOCKSIZE => '8192', ENCODE_ON_DISK => > >> 'true', > >>> IN_MEMORY => 'false', BLOCKCACHE => 'true'}]} > >>> > >>> *Configuration* > >>> 1 Machine having both hbase and hadoop master > >>> 2 machines having both region server node and datanode > >>> total 285 region servers > >>> > >>> *Machine Level Optimizations:* > >>> a)No of file descriptors is 1000000(ulimit -n gives 1000000) > >>> b)Increase the read-ahead value to 4096 > >>> c)Added noatime,nodiratime to the disks > >>> > >>> *Hadoop Optimizations:* > >>> dfs.datanode.max.xcievers = 4096 > >>> dfs.block.size = 33554432 > >>> dfs.datanode.handler.count = 256 > >>> io.file.buffer.size = 65536 > >>> hadoop data is split on 4 directories, so that different disks are > being > >>> accessed > >>> > >>> *Hbase Optimizations*: > >>> > >>> hbase.client.scanner.caching=1 #We have specifcally added this, as we > >>> return always one row. > >>> hbase.regionserver.handler.count=3200 > >>> hfile.block.cache.size=0.35 > >>> hbase.hregion.memstore.mslab.enabled=true > >>> hfile.min.blocksize.size=16384 > >>> hfile.min.blocksize.size=4 > >>> hbase.hstore.blockingStoreFiles=200 > >>> hbase.regionserver.optionallogflushinterval=60000 > >>> hbase.hregion.majorcompaction=0 > >>> hbase.hstore.compaction.max=100 > >>> hbase.hstore.compactionThreshold=100 > >>> > >>> *Hbase-GC > >>> *-XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:+CMSParallelRemarkEnabled > >>> -XX:SurvivorRatio=20 -XX:ParallelGCThreads=16 > >>> *Hadoop-GC* > >>> -XX:+UseConcMarkSweepGC -XX:+UseParNewGC > >>> > >>> -Vibhav > >> >
