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Date: Tue, 22 Dec 2009 15:28:58 +0200
Message-ID: <468b21170912220528o11555999u7dbffedd94b50a24@mail.gmail.com>
Subject: Re: TimeUUID Partitioning
From: Richard Grossman <richiesgr@gmail.com>
To: cassandra-user@incubator.apache.org
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Same problem here.
But can't understand why to use TimeUUID instead just long. it make the same
job and much more simple


On Tue, Dec 22, 2009 at 2:48 PM, Daniel Lundin <dln@eintr.org> wrote:

> I'm pondering order preservation and TimeUUID keys, in particular how to
> get distribution across the cluster while maintaining "rangeability".
>
> Basically, I'm working on a logging app, where rows are TimeUUIDs. To be
> able to do range scans we're using OrderPreservingPartitioner.
>
> To get partitioning working, I've currently transformed keys, prepending
> a partitioning token (in my testcase, the day-of-week).
> Basically, this means two range queries to get data for a set spanning
> two days. Crude, but kinda works, and the specialization is alright for
> my case. But it feels a bit hackish, so I begun studying the partitioner
> code a bit, seeking enlightenment.
>
> Has anybody already spent energy + time thinking about generic TimeUUID
> partitioning? Seems like it could be a useful thing, since time series
> data is quite common.
>
> Perhaps a TimeUUIDPartitioner with configurable time resolution for
> tokenization (token = uuid.time % resolution, more or less) would be
> sufficient?
>
> Or could it be even more general, i e no configuration necessary?
>
> /d
>

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<div dir=3D"ltr">Same problem here.<div>But can&#39;t understand why to use=
 TimeUUID instead just long. it make the same job and much more simple</div=
><div><br><br><div class=3D"gmail_quote">On Tue, Dec 22, 2009 at 2:48 PM, D=
aniel Lundin <span dir=3D"ltr">&lt;<a href=3D"mailto:dln@eintr.org">dln@ein=
tr.org</a>&gt;</span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;">I&#39;m pondering order preservation and Ti=
meUUID keys, in particular how to<br>
get distribution across the cluster while maintaining &quot;rangeability&qu=
ot;.<br>
<br>
Basically, I&#39;m working on a logging app, where rows are TimeUUIDs. To b=
e<br>
able to do range scans we&#39;re using OrderPreservingPartitioner.<br>
<br>
To get partitioning working, I&#39;ve currently transformed keys, prependin=
g<br>
a partitioning token (in my testcase, the day-of-week).<br>
Basically, this means two range queries to get data for a set spanning<br>
two days. Crude, but kinda works, and the specialization is alright for<br>
my case. But it feels a bit hackish, so I begun studying the partitioner<br=
>
code a bit, seeking enlightenment.<br>
<br>
Has anybody already spent energy + time thinking about generic TimeUUID<br>
partitioning? Seems like it could be a useful thing, since time series<br>
data is quite common.<br>
<br>
Perhaps a TimeUUIDPartitioner with configurable time resolution for<br>
tokenization (token =3D uuid.time % resolution, more or less) would be<br>
sufficient?<br>
<br>
Or could it be even more general, i e no configuration necessary?<br>
<font color=3D"#888888"><br>
/d<br>
</font></blockquote></div><br></div></div>

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