This is a related JIRA which should provide noticeable speed up: HBASE-1935 Scan in parallel
Cheers On Mon, Apr 15, 2013 at 7:13 AM, Ted Yu <[email protected]> wrote: > I looked > at src/main/java/org/apache/hadoop/hbase/client/HConnectionManager.java in > 0.94 > > In processBatchCallback(), starting line 1538, > > // step 1: break up into regionserver-sized chunks and build the > data structs > Map<HRegionLocation, MultiAction<R>> actionsByServer = > new HashMap<HRegionLocation, MultiAction<R>>(); > for (int i = 0; i < workingList.size(); i++) { > > So we do group individual action by server. > > FYI > > On Mon, Apr 15, 2013 at 6:30 AM, Ted Yu <[email protected]> wrote: > >> Doug made a good point. >> >> Take a look at the performance gain for parallel scan (bottom chart >> compared to top chart): >> https://issues.apache.org/jira/secure/attachment/12578083/FDencode.png >> >> See >> https://issues.apache.org/jira/browse/HBASE-8316?focusedCommentId=13628300&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-13628300for >> explanation of the two methods. >> >> Cheers >> >> On Mon, Apr 15, 2013 at 6:21 AM, Doug Meil <[email protected] >> > wrote: >> >>> >>> Hi there, regarding this... >>> >>> > We are passing random 10000 row-keys as input, while HBase is taking >>> around >>> > 17 secs to return 10000 records. >>> >>> >>> …. Given that you are generating 10,000 random keys, your multi-get is >>> very likely hitting all 5 nodes of your cluster. >>> >>> >>> Historically, multi-Get used to first sort the requests by RS and then >>> *serially* go the RS to process the multi-Get. I'm not sure of the >>> current (0.94.x) behavior if it multi-threads or not. >>> >>> One thing you might want to consider is confirming that client behavior, >>> and if it's not multi-threading then perform a test that does the same RS >>> sorting via... >>> >>> >>> http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html# >>> getRegionLocation%28byte[<http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#getRegionLocation%28byte[> >>> ]%29 >>> >>> …. and then spin up your own threads (one per target RS) and see what >>> happens. >>> >>> >>> >>> On 4/15/13 9:04 AM, "Ankit Jain" <[email protected]> wrote: >>> >>> >Hi Liang, >>> > >>> >Thanks Liang for reply.. >>> > >>> >Ans1: >>> >I tried by using HFile block size of 32 KB and bloom filter is enabled. >>> >The >>> >random read performance is 10000 records in 23 secs. >>> > >>> >Ans2: >>> >We are retrieving all the 10000 rows in one call. >>> > >>> >Ans3: >>> >Disk detai: >>> >Model Number: ST2000DM001-1CH164 >>> >Serial Number: Z1E276YF >>> > >>> >Please suggest some more optimization >>> > >>> >Thanks, >>> >Ankit Jain >>> > >>> >On Mon, Apr 15, 2013 at 5:11 PM, 谢良 <[email protected]> wrote: >>> > >>> >> First, it's probably helpless to set block size to 4KB, please refer >>> to >>> >> the beginning of HFile.java: >>> >> >>> >> Smaller blocks are good >>> >> * for random access, but require more memory to hold the block index, >>> >>and >>> >> may >>> >> * be slower to create (because we must flush the compressor stream at >>> >>the >>> >> * conclusion of each data block, which leads to an FS I/O flush). >>> >> Further, due >>> >> * to the internal caching in Compression codec, the smallest possible >>> >> block >>> >> * size would be around 20KB-30KB. >>> >> >>> >> Second, is it a single-thread test client or multi-threads? we >>> couldn't >>> >> expect too much if the requests are one by one. >>> >> >>> >> Third, could you provide more info about your DN disk numbers and IO >>> >> utils ? >>> >> >>> >> Thanks, >>> >> Liang >>> >> ________________________________________ >>> >> 发件人: Ankit Jain [[email protected]] >>> >> 发送时间: 2013年4月15日 18:53 >>> >> 收件人: [email protected] >>> >> 主题: Re: HBase random read performance >>> >> >>> >> Hi Anoop, >>> >> >>> >> Thanks for reply.. >>> >> >>> >> I tried by setting Hfile block size 4KB and also enabled the bloom >>> >> filter(ROW). The maximum read performance that I was able to achieve >>> is >>> >> 10000 records in 14 secs (size of record is 1.6KB). >>> >> >>> >> Please suggest some tuning.. >>> >> >>> >> Thanks, >>> >> Ankit Jain >>> >> >>> >> >>> >> >>> >> On Mon, Apr 15, 2013 at 4:12 PM, Rishabh Agrawal < >>> >> [email protected]> wrote: >>> >> >>> >> > Interesting. Can you explain why this happens? >>> >> > >>> >> > -----Original Message----- >>> >> > From: Anoop Sam John [mailto:[email protected]] >>> >> > Sent: Monday, April 15, 2013 3:47 PM >>> >> > To: [email protected] >>> >> > Subject: RE: HBase random read performance >>> >> > >>> >> > Ankit >>> >> > I guess you might be having default HFile block >>> size >>> >> > which is 64KB. >>> >> > For random gets a lower value will be better. Try will some thing >>> like >>> >> 8KB >>> >> > and check the latency? >>> >> > >>> >> > Ya ofcourse blooms can help (if major compaction was not done at the >>> >>time >>> >> > of testing) >>> >> > >>> >> > -Anoop- >>> >> > ________________________________________ >>> >> > From: Ankit Jain [[email protected]] >>> >> > Sent: Saturday, April 13, 2013 11:01 AM >>> >> > To: [email protected] >>> >> > Subject: HBase random read performance >>> >> > >>> >> > Hi All, >>> >> > >>> >> > We are using HBase 0.94.5 and Hadoop 1.0.4. >>> >> > >>> >> > We have HBase cluster of 5 nodes(5 regionservers and 1 master node). >>> >>Each >>> >> > regionserver has 8 GB RAM. >>> >> > >>> >> > We have loaded 25 millions records in HBase table, regions are >>> >>pre-split >>> >> > into 16 regions and all the regions are equally loaded. >>> >> > >>> >> > We are getting very low random read performance while performing >>> multi >>> >> get >>> >> > from HBase. >>> >> > >>> >> > We are passing random 10000 row-keys as input, while HBase is taking >>> >> around >>> >> > 17 secs to return 10000 records. >>> >> > >>> >> > Please suggest some tuning to increase HBase read performance. >>> >> > >>> >> > Thanks, >>> >> > Ankit Jain >>> >> > iLabs >>> >> > >>> >> > >>> >> > >>> >> > -- >>> >> > Thanks, >>> >> > Ankit Jain >>> >> > >>> >> > ________________________________ >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > NOTE: This message may contain information that is confidential, >>> >> > proprietary, privileged or otherwise protected by law. The message >>> is >>> >> > intended solely for the named addressee. If received in error, >>> please >>> >> > destroy and notify the sender. Any use of this email is prohibited >>> >>when >>> >> > received in error. Impetus does not represent, warrant and/or >>> >>guarantee, >>> >> > that the integrity of this communication has been maintained nor >>> that >>> >>the >>> >> > communication is free of errors, virus, interception or >>> interference. >>> >> > >>> >> >>> >> >>> >> >>> >> -- >>> >> Thanks, >>> >> Ankit Jain >>> >> >>> > >>> > >>> > >>> >-- >>> >Thanks, >>> >Ankit Jain >>> >>> >> >
