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From Ted Yu <yuzhih...@gmail.com>
Subject Re: HBase 6x bigger than raw data
Date Mon, 27 Jan 2014 23:36:07 GMT
Yes.


On Mon, Jan 27, 2014 at 3:34 PM, Koert Kuipers <koert@tresata.com> wrote:

> if compression is already enabled on a column family, do i understand it
> correctly that the main benefit of DATA_BLOCK_ENCODING is in memory?
>
>
> On Mon, Jan 27, 2014 at 6:02 PM, Nick Xie <nick.xie.hadoop@gmail.com>
> wrote:
>
> > Thanks all for the information. Appreciated!! I'll take a look and try.
> >
> > Thanks,
> >
> > Nick
> >
> >
> >
> >
> > On Mon, Jan 27, 2014 at 2:43 PM, Vladimir Rodionov
> > <vrodionov@carrieriq.com>wrote:
> >
> > > Overhead of storing small values is quite high in HBase unless you use
> > > DATA_BLOCK_ENCODING
> > > (not available in 0.92). I recommend you moving to 0.94.latest.
> > >
> > > See: https://issues.apache.org/jira/browse/HBASE-4218
> > >
> > > Best regards,
> > > Vladimir Rodionov
> > > Principal Platform Engineer
> > > Carrier IQ, www.carrieriq.com
> > > e-mail: vrodionov@carrieriq.com
> > >
> > > ________________________________________
> > > From: Nick Xie [nick.xie.hadoop@gmail.com]
> > > Sent: Monday, January 27, 2014 2:40 PM
> > > To: user@hbase.apache.org
> > > Subject: Re: HBase 6x bigger than raw data
> > >
> > > Tom,
> > >
> > > Yes, you are right. According to this analysis (
> > >
> > >
> >
> http://prafull-blog.blogspot.in/2012/06/how-to-calculate-record-size-of-hbase.html
> > > )
> > > if it is right, then the overhead is quite big if the cell value
> > > occupies
> > > a small portion.
> > >
> > > In the analysis in that link, the overhead is actually 10x!!!!(the real
> > > values only takes 12B and it costs 123B in HBase to store them...) Is
> > that
> > > real????
> > >
> > > In this case, should we do some combination to reduce the overhead?
> > >
> > > Thanks,
> > >
> > > Nick
> > >
> > >
> > >
> > >
> > > On Mon, Jan 27, 2014 at 2:33 PM, Tom Brown <tombrown52@gmail.com>
> wrote:
> > >
> > > > I believe each cell stores its own copy of the entire row key, column
> > > > qualifier, and timestamp. Could that account for the increase in
> size?
> > > >
> > > > --Tom
> > > >
> > > >
> > > > On Mon, Jan 27, 2014 at 3:12 PM, Nick Xie <nick.xie.hadoop@gmail.com
> >
> > > > wrote:
> > > >
> > > > > I'm importing a set of data into HBase. The CSV file contains 82
> > > entries
> > > > > per line. Starting with 8 byte ID, followed by 16 byte date and the
> > > rest
> > > > > are 80 numbers with 4 bytes each.
> > > > >
> > > > > The current HBase schema is: ID as row key, date as a 'date' family
> > > with
> > > > > 'value' qualifier, the rest is in another family called 'readings'
> > with
> > > > > 'P0', 'P1', 'P2', ... through 'P79' as qualifiers.
> > > > >
> > > > > I'm testing this on a single node cluster with HBase running in
> > pseudo
> > > > > distributed mode (no replication, no compression for HBase)...After
> > > > > importing a CSV file with 150MB of size in HDFS(no replication),
I
> > > > checked
> > > > > the the table size, and it shows ~900MB which is 6x times larger
> than
> > > it
> > > > is
> > > > > in HDFS....
> > > > >
> > > > > Why there is so large overhead on this? Am I doing anything wrong
> > here?
> > > > >
> > > > > Thanks,
> > > > >
> > > > > Nick
> > > > >
> > > >
> > >
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> > >
> >
>

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