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HBase, mail # user - Possibility of using timestamp as row key in HBase

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Re: Possibility of using timestamp as row key in HBase
Asaf Mesika 2013-06-21, 05:26
On Thu, Jun 20, 2013 at 9:42 PM, yun peng <[EMAIL PROTECTED]> wrote:

> Thanks Asaf, I made the response inline.
> On Thu, Jun 20, 2013 at 9:32 AM, Asaf Mesika <[EMAIL PROTECTED]>
> wrote:
> > On Thu, Jun 20, 2013 at 12:59 AM, yun peng <[EMAIL PROTECTED]>
> wrote:
> >
> > > Thanks for the reply. The idea is interesting, but in practice, our
> > client
> > > don't know in advance how many data should be put to one RS. The data
> > write
> > > is redirected to next RS, only when current RS is initialising a
> flush()
> > > and begins to block the stream..
> > >
> > > Can a single RS handle the load of the duration until HBase splits the
> > region and load balancing kicks in and moves the region another server?
> >
> > Right, currently the timeseries data (i.e., with sequential rowkey) is
> meta data in our system,
> and is not that heavy weight... it can be handled by a single RS...
> > > The real problem is not about splitting existing region, but instead
> > about
> > > adding a new region (or new key range).
> > > In the original example, before node n3 overflows, the system is like
> > > n1 [0,4],
> > > n2 [5,9],
> > > n3 [10,14]
> > > then n3 start to flush() (say Memstore.size = 5) which may block the
> > write
> > > stream to n3. We want the subsequent write stream to redirect back to,
> > say
> > > n1. so now n1 is accepting 15, 16... for range [15,19].
> > >
> > Flush does not block HTable.put() or HTable.batch(), unless your system
> is
> > not tuned and your flushes are slow.
> >
> > If I understand right, flush() need to sort data, build index and
> sequentially write to disk.. which I think
> should, if not block, atleast interfere a lot with the thread for in-memory
> write (plus WAL). A drop in write
> throughput can be expected.
> I think all those phases of sorting and index building are done per
insertion of Put to the Memstore, thus the flush only dumps the bytes from
memory to disk (network). It doesn't interfere with other write happening
at the same time, since they open a new memstore and directs the write
there, and asynchronously flush the old memstore to disk. They only if the
new memstore if filled up very quickly before you finish flushing the first
Regarding WAL, it happens before writing to the memstore. They first get an
ack on writing to the WAL, then write to the memstore and then ack back to
the client. I don't see any blocking here.

> >
> > > As I understand it right, the above behaviour should change HBase's
> > normal
> > > way to manage region-key mapping. And we want to know how much effort
> to
> > > put to change HBase?
> > >
> > Well, as I understand it - you write to n3, to a specific region (say
> > 10,inf). Once you  pass the max size, it splits into (10,14) and
> (15,inf).
> > If now n3 RS has more than the average regions per RS, one region will
> move
> > to another RS. It may be (10,14) or (15,inf).
> >
> > For example, is it possible to specify the "max size" of split to be
> equal
> to Memstore.size
> so that flush and split (actually just updating range from [10,inf) to
> [10,14] in .META table,
> without actual data split) can co-occur?
> Given this possible, is it even possible to mandatorily indicate the new
> interval [15, inf) should
> be mapped to next RS (i.e., not based on # of regions on RS n3).
Can you explain why specifying a max size of split equaling flush size will
help your throughput? also, why it will help immediately moving the write
to another RS? I mean, once (10,inf) if split then (10,14) will not be
written to anymore, right? (15, inf) will get all writes, in the same RS.
this can a couple of more times on this RS, until HBase realizes it has too
many regions on n3 relative to n1 and n2 and thus move some to n1 and n2.
The write throughput to n3 remains the same until the "hot"/active region
is moved. splitting in the middle does not hamper write throughput.


> > > Besides, I found Chapter 9 Advanced usage in Definitive Book talks a