Oozie (or something like it) would appear to me to be the correct tool
here. You are likely moving files around and pinning up hive tables:
- Moving the data written in HDFS from /apps/metron/enrichment/${sensor}
to another directory in HDFS
- Running a job in Hive or pig or spark to take the JSON blobs, map them
to rows and pin it up as an ORC table for downstream analytics
NiFi is mostly about getting data in the cluster, not really for scheduling
large-scale batch ETL, I think.
Casey
On Thu, Dec 22, 2016 at 5:18 PM, Dima Kovalyov <[email protected]>
wrote:
> Thank you for reply Carolyn,
>
> Currently for the test purposes we enrich flow with Geo and ThreatIntel
> malware IP, but plan to expand this further.
>
> Our dev team is working on Oozie job to process this. So meanwhile I
> wonder if I could use NiFi for this purpose (because we already using it
> for data ingest and stream).
>
> Could you elaborate why it may be overkill? The idea is to have
> everything in one place instead of hacking into Metron libraries and code.
>
> - Dima
>
> On 12/22/2016 02:26 AM, Carolyn Duby wrote:
> > Hi Dima -
> >
> > What type of analytics are you looking to do? Is the normalized format
> not working? You could use an oozie or spark job to create derivative
> tables.
> >
> > Nifi may be overkill for breaking up the kafka stream. Spark streaming
> may be easier.
> >
> > Thanks
> > Carolyn
> >
> >
> >
> > Sent from my Verizon, Samsung Galaxy smartphone
> >
> >
> > -------- Original message --------
> > From: Dima Kovalyov <[email protected]>
> > Date: 12/21/16 6:28 PM (GMT-05:00)
> > To: [email protected]
> > Subject: Long-term storage for enriched data
> >
> > Hello,
> >
> > Currently we are researching fast and resources efficient way to save
> > enriched data in Hive for further Analytics.
> >
> > There are two scenarios that we consider:
> > a) Use Ozzie Java job that uses Metron enrichment classes to "manually"
> > enrich each line of the source data that is picked up from the source
> > dir (the one that we have developed already and using). That is
> > something that we developed on our own. Downside: custom code that built
> > on top of Metron source code.
> >
> > b) Use NiFi to listen for indexing Kafka topic -> split stream by source
> > type -> Put every source type in corresponding Hive table.
> >
> > I wonder, if someone was going any of this direction and if there are
> > best practices for this? Please advise.
> > Thank you.
> >
> > - Dima
> >
> >
>
>
