You are viewing a plain text version of this content. The canonical link for it is here.
Posted to user@spark.apache.org by Mohit Durgapal <du...@gmail.com> on 2015/02/06 08:19:08 UTC

spark streaming from kafka real time + batch processing in java

I want to write a spark streaming consumer for kafka in java. I want to
process the data in real-time as well as store the data in hdfs in
year/month/day/hour/ format. I am not sure how to achieve this. Should I
write separate kafka consumers, one for writing data to HDFS and one for
spark streaming?

Also I would like to ask what do people generally do with the result of
spark streams after aggregating over it? Is it okay to update a NoSQL DB
with aggregated counts per batch interval or is it generally stored in hdfs?

Is it possible to store the mini batch data from spark streaming to HDFS in
a way that the data is aggregated  hourly and put into HDFS in its "hour"
folder. I would not want a lot of small files equal to the mini batches of
spark per hour, that would be inefficient for running hadoop jobs later.

Is anyone working on the same problem?

Any help and comments would be great.


Regards
Mohit

Re: spark streaming from kafka real time + batch processing in java

Posted by Andrew Psaltis <ps...@gmail.com>.
Mohit,

>I want to process the data in real-time as well as store the data in hdfs
in year/month/day/hour/ format.
Are you wanting to process it and then put it into HDFS or just put the raw
data into HDFS? If the later then why not just use Camus (
https://github.com/linkedin/camus), it will easily put the data into the
directory structure you are after.

On Fri, Feb 6, 2015 at 12:19 AM, Mohit Durgapal <du...@gmail.com>
wrote:

> I want to write a spark streaming consumer for kafka in java. I want to
> process the data in real-time as well as store the data in hdfs in
> year/month/day/hour/ format. I am not sure how to achieve this. Should I
> write separate kafka consumers, one for writing data to HDFS and one for
> spark streaming?
>
> Also I would like to ask what do people generally do with the result of
> spark streams after aggregating over it? Is it okay to update a NoSQL DB
> with aggregated counts per batch interval or is it generally stored in hdfs?
>
> Is it possible to store the mini batch data from spark streaming to HDFS
> in a way that the data is aggregated  hourly and put into HDFS in its
> "hour" folder. I would not want a lot of small files equal to the mini
> batches of spark per hour, that would be inefficient for running hadoop
> jobs later.
>
> Is anyone working on the same problem?
>
> Any help and comments would be great.
>
>
> Regards
> Mohit
>