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From samal <samalgo...@gmail.com>
Subject Re: timezone time series data model
Date Mon, 30 Apr 2012 17:39:42 GMT
thanks I didn't noticed.
run script for 5  minutes => divide seems to produce result ,modulo is
still changing. If divide is ok will do the trick.
I will run this script on Singapore, East coast server, and New delhi
server whole night today.

======================
unix              =>   1335806983422
unix /1000        =>   1335806983.422
Divid i/86400     =>   15460.728969907408
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62983
======================
======================
unix              =>   1335806985421
unix /1000        =>   1335806985.421
Divid i/86400     =>   15460.728993055556
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62985
======================
======================
unix              =>   1335806987422
unix /1000        =>   1335806987.422
Divid i/86400     =>   15460.729016203704
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62987
======================
======================
unix              =>   1335806989422
unix /1000        =>   1335806989.422
Divid i/86400     =>   15460.729039351852
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62989
======================
======================
unix              =>   1335806991421
unix /1000        =>   1335806991.421
Divid i/86400     =>   15460.7290625
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62991
======================
======================
unix              =>   1335806993422
unix /1000        =>   1335806993.422
Divid i/86400     =>   15460.729085648149
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62993
======================
======================
unix              =>   1335806995422
unix /1000        =>   1335806995.422
Divid i/86400     =>   15460.729108796297
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62995
======================
======================
unix              =>   1335806997421
unix /1000        =>   1335806997.421
Divid i/86400     =>   15460.729131944445
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62997
======================
======================
unix              =>   1335806999422
unix /1000        =>   1335806999.422
Divid i/86400     =>   15460.729155092593
Divid i/86400 INT =>   15460
Modulo i%86400    =>   62999
======================


On Mon, Apr 30, 2012 at 10:44 PM, Tyler Hobbs <tyler@datastax.com> wrote:

> getTime() returns the number of milliseconds since the epoch, not the
> number of seconds: http://www.w3schools.com/jsref/jsref_gettime.asp
>
> If you divide that number by 1000, it should work.
>
>
> On Mon, Apr 30, 2012 at 11:28 AM, samal <samalgorai@gmail.com> wrote:
>
>> I did it with node.js but it is changing after some interval.
>>
>> <code>
>> setInterval(function(){
>>   var d =new Date().getTime();
>>   console.log("====================== ");
>>   console.log("unix         =>  ",d);
>>   i=parseInt(d)
>>   console.log("Divid i/86400=>  ",i/86400);
>>   console.log("Modulo i%86400=> ",i%86400);
>>   console.log("====================== ");
>> },2000);
>>
>> </code>
>> Am I doing wrong?
>>
>>
>> On Mon, Apr 30, 2012 at 9:54 PM, Tyler Hobbs <tyler@datastax.com> wrote:
>>
>>> Correct, that's exactly what I'm saying.
>>>
>>>
>>> On Mon, Apr 30, 2012 at 10:37 AM, samal <samalgorai@gmail.com> wrote:
>>>
>>>> thanks tyler for reply.
>>>>
>>>> are you saying  user1uuid_*{ts%86400}* would lead to unique day bucket
>>>> which will be timezone {NZ to US} independent? I will try.
>>>>
>>>>
>>>> On Mon, Apr 30, 2012 at 8:25 PM, Tyler Hobbs <tyler@datastax.com>wrote:
>>>>
>>>>> Don't use dates or datestamps as the buckets for your row keys, use a
>>>>> unix timestamp modulo whatever size you want your bucket to be instead.
>>>>> Timestamps don't involve time zones or any of that nonsense.
>>>>>
>>>>> So, instead of having keys like "user1uuid_30042012", the second half
>>>>> would be replaced the current unix timestamp mod 86400 (the number of
>>>>> seconds in a day).
>>>>>
>>>>>
>>>>> On Mon, Apr 30, 2012 at 1:46 AM, samal <samalgorai@gmail.com> wrote:
>>>>>
>>>>>> Hello List,
>>>>>>
>>>>>> I need suggestion/ recommendation on time series data.
>>>>>>
>>>>>> I have requirement where users belongs to different timezone and
they
>>>>>> can subscribe to global group.
>>>>>> When users at specific timezone send update to group it is available
>>>>>> to every user in different timezone.
>>>>>>
>>>>>> I am using GroupSubscribedUsers CF where all update to group are
push
>>>>>> to "Each User" time line, and key is timelined by useruuid_date(one
day
>>>>>> update of all groups) and columns are group updates.
>>>>>>
>>>>>> GroupSubscribedUsers ={
>>>>>>     user1uuid_30042012:{//this user belongs to same timezone
>>>>>>          timeuuid1:JSON[group1update1]
>>>>>>          timeuuid2:JSON[group2update2]
>>>>>>          timeuuid3:JSON[group1update2]
>>>>>>         timeuuid4:JSON[group4update1]
>>>>>>    },
>>>>>>   user2uuid_30042012:{//this user belongs to different timezonewhere
date has changed already  to 1may but  30 april is getting update
>>>>>>          timeuuid1:JSON[group1update1]
>>>>>>          timeuuid2:JSON[group2update2]
>>>>>>          timeuuid3:JSON[group1update2]
>>>>>>         timeuuid4:JSON[group4update1]
>>>>>>         timeuuid5:JSON[groupNupdate1]
>>>>>>    },
>>>>>>
>>>>>> }
>>>>>>
>>>>>> I have noticed  this approach is good for single time zone when
>>>>>> different timezone come into picture it breaks.
>>>>>>
>>>>>> I am thinking of like when user pushed update to group ->get user
who
>>>>>> is subscribed to group->check user timezone->push time series
in user time
>>>>>> zone. So for one user update will be on 30april where as other may
have on
>>>>>> 29april and 1may, using timestamps i can find out hours ago update
came.
>>>>>>
>>>>>> Is there any better approach?
>>>>>>
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> >>>Samal
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> Tyler Hobbs
>>>>> DataStax <http://datastax.com/>
>>>>>
>>>>>
>>>>
>>>
>>>
>>> --
>>> Tyler Hobbs
>>> DataStax <http://datastax.com/>
>>>
>>>
>>
>
>
> --
> Tyler Hobbs
> DataStax <http://datastax.com/>
>
>

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