Yeah, it depends on what you want to do with that timeseries data. We at
Datadog process trillions of points daily using Spark, I cannot really go
about what exactly we do with the data, but just saying that Spark can
handle the volume, scale well and be fault-tolerant, albeit everything I
said com
There is not one answer to this.
It really depends what kind of time Series analysis you do with the data and
what time series database you are using. Then it also depends what Etl you need
to do.
You seem to also need to join data - is it with existing data of the same type
or do you join com
Hi
Have you tested the Cloudera project:
https://github.com/cloudera/spark-timeseries ?
Let me know how did you progress on that route as I am also interested in
that topic ?
Cheers
On 26 June 2015 at 14:07, Caio Cesar Trucolo wrote:
> Hi everyone!
>
> I am working with multiple time series
