Re: [influxdb] Automatic merge does not seem to work

2016-12-13 Thread Ross McDonald 
Are the fields part of the same series
 (do
they share the same tag keys and values)? If not, they will be displayed on
different lines.

Thanks,
Ross

On Mon, Dec 12, 2016 at 3:35 AM,  wrote:

> Hi,
>
> I have a problem with queries like
>
> select var1,var2 from measure1 where time >= '2015-03-01' Limit 4
>
> where the field var1 was added before the field var2 to the database.
> Influx returns e.g.
>
> measure1
> time var1  var2
> 2015-03-01T00:00:00Z 3908
> 2015-03-01T00:00:00Z   3
> 2015-03-01T00:00:02Z 3794
> 2015-03-01T00:00:02Z   3
>
> but I expected that there is an automatic join on the timestamp and influx
> response looks like
>
> measure1
> time var1  var2
> 2015-03-01T00:00:00Z 3908  3
> 2015-03-01T00:00:02Z 3794  3
>
> If I add another field var3 then the influx partly joins the series
>
> measure1
> time var1  var2  var3
> 2015-03-01T00:00:00Z 3908
> 2015-03-01T00:00:00Z   3 2
> 2015-03-01T00:00:02Z 3794
> 2015-03-01T00:00:02Z   3 1
>
>
> I added the data via the DataFrameClient from the python influx library:
>
> db.write_points(df, 'measure1', batch_size=1000)
>
> where df is a pandas DataFrame containing the column var1.
>
> And for the fields added afterwards:
>
> db.write_points(pd.DataFrame(data={'var2': 3}, index=df.index),
> 'measure1', batch_size=5)
>
> where df is again a pandas DataFrame which results from a influxdb query
> for var1 in measure1.
>
> Am I doing something wrong and is this behavior as expected? Then how is
> it possible to merge the series?
>
> I was using the version 1.0 of influxdb and updated to the current version
> on github a few days ago (same behavior).
>
> Thanks in advance!
>
> Best regards,
> Marc
>
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[influxdb] Automatic merge does not seem to work

2016-12-12 Thread gille . marc 
Hi,

I have a problem with queries like

select var1,var2 from measure1 where time >= '2015-03-01' Limit 4

where the field var1 was added before the field var2 to the database. Influx 
returns e.g.

measure1
time var1  var2
2015-03-01T00:00:00Z 3908  
2015-03-01T00:00:00Z   3
2015-03-01T00:00:02Z 3794
2015-03-01T00:00:02Z   3

but I expected that there is an automatic join on the timestamp and influx 
response looks like

measure1
time var1  var2
2015-03-01T00:00:00Z 3908  3
2015-03-01T00:00:02Z 3794  3

If I add another field var3 then the influx partly joins the series

measure1
time var1  var2  var3
2015-03-01T00:00:00Z 3908  
2015-03-01T00:00:00Z   3 2
2015-03-01T00:00:02Z 3794
2015-03-01T00:00:02Z   3 1


I added the data via the DataFrameClient from the python influx library:

db.write_points(df, 'measure1', batch_size=1000)

where df is a pandas DataFrame containing the column var1.

And for the fields added afterwards:

db.write_points(pd.DataFrame(data={'var2': 3}, index=df.index), 'measure1', 
batch_size=5)

where df is again a pandas DataFrame which results from a influxdb query for 
var1 in measure1.

Am I doing something wrong and is this behavior as expected? Then how is it 
possible to merge the series?

I was using the version 1.0 of influxdb and updated to the current version on 
github a few days ago (same behavior).

Thanks in advance!

Best regards,
Marc

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