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RE: 答复: HBase random read performance
So what is lacking here? The action should also been parallel inside RS for each region, Instead of just parallel on RS level?
Seems this will be rather difficult to implement, and for Get, might not be worthy?

>
> 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=1362
> 8300&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpan
> el#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]]