Thanks for the clarification. 

So in this case, would it still make sense to split the data in multiple 
databases ? For me it means it will be easier to export the DB of a given 
org and import it on an other influx server let's say when the org ask for 
on-premise solutions. 

It would also allow me to set retention policies / org for all the 
measurements in this org. 

I saw the last thread about multiple databases and you seem completely 
against this usage so I was thinking there may be a limitation I was not 
aware of. 

Thanks :)

Le mardi 21 juin 2016 18:05:16 UTC+2, Sean Beckett a écrit :
>
> When tag values are dependent they don't increase cardinality at all. For 
> example, let's say I store user emails as a tag (terrible idea, btw, but 
> just for the example here.) Emails are by definition globally unique. So, 
> if I have a series defined by email, I can store whatever else I want, like 
> First Name, Last Name, Phone Number, Physical Address, Nickname, etc. and I 
> have defined no more series than I did before. Sure, I just added a new tag 
> like First Name with an infinite cardinality, but it's not multiplicative. 
> For any given email address there is one and only one First Name. First 
> Name is dependent on email, it is implied by email. So the series count 
> doesn't rise. Email is globally unique, so I can't have more series than I 
> have emails, no matter what other metadata I add to the series. 
>
> Yes, first names can change and emails can be recycled, but overall the 
> cardinality is perhaps 10% higher than the total emails? Certainly not the 
> multiplication of the cardinality of each tag.
>
> On Tue, Jun 21, 2016 at 10:00 AM, Sean Beckett <[email protected] 
> <javascript:>> wrote:
>
>> The cardinality is not multiplicative unless every possible combination 
>> actually exists in the database. What you've described is the maximum 
>> possible cardinality, but if OrgA and OrgB have distinct values for Tags 1, 
>> 2, and 3, then there is no possibility of a series like:
>>
>> Tag1A, Tag2A, Tag3B
>>
>> Therefore the total cardinality is never going to approach 1000.
>>
>> If TagA and TagB are actually the same, and the above series is 
>> reasonable, then you don't have 10 possible values in Meas1, you have 5. 
>> The cardinality of the database would still be ~125, although presumably 
>> you need a tag to differentiate OrgA and B, so that doubles it to 250. 
>> That's also the sum of the cardinality of the two separate databases.
>>
>> On Tue, Jun 21, 2016 at 3:54 AM, Alexandre Grais <
>> [email protected] <javascript:>> wrote:
>>
>>> Hi guys,
>>>
>>> I recently read the following post : 
>>> https://groups.google.com/forum/#!topic/influxdb/4AzHnMdhyJ0
>>>
>>> Let's say you have the following use cases:
>>>
>>> *-> CASE 1 : One database to store metrics for 2 organizations named A & 
>>> B*
>>>
>>> Measurement1
>>> Tag1 -> 10 values  (5 values for orga A and 5 for orga B)
>>> Tag2 -> 10 values  (5 values for orga A and 5 for orga B)
>>> Tag3 -> 10 Values  (5 values for orga A and 5 for orga B)
>>>
>>> Cardinality: 10*10*10 = *1000*
>>>
>>> *-> CASE 2 : One database for each organization*
>>>
>>> Measurement1A
>>> Tag1 -> 5 values
>>> Tag2 -> 5 Values
>>> Tag3 -> 5 values
>>>
>>> Cardinality: 5*5*5 = *125*
>>>
>>> Measurement1B
>>> Tag1 -> 5 Values
>>> Tag2 -> 5 Values
>>> Tag3 -> 5 Values
>>>
>>> Cardinality: 5*5*5 = *125*
>>>
>>> So from my understanding, in this case, when tags values are highly 
>>> dependant of other values, it may make sense to split the data in different 
>>> base.
>>>
>>> Could you confirm ?
>>>
>>>
>>>
>>>
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>>
>>
>>
>> -- 
>> Sean Beckett
>> Director of Support and Professional Services
>> InfluxDB
>>
>
>
>
> -- 
> Sean Beckett
> Director of Support and Professional Services
> InfluxDB
>

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