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From "Kumara M S, Hemantha (Nokia - IN/Bangalore)" <>
Subject Re: SplitRecord behaviour
Date Fri, 01 Mar 2019 18:48:44 GMT
Yeah, I will try both the options and will see which option will suite better
1. Split incoming file using SplitRecord and use PublishKafka
2. Take large file and use PublishKafkaRecord

From: Bryan Bende <>
Sent: Friday, March 1, 2019 11:37:00 PM
Subject: Re: SplitRecord behaviour

If you increase the concurrent tasks on PublishKafka then you are
right that you could publish multiple records at the same time, but I
suspect that the overhead of doing the split will cancel out any gains
from publishing in parallel.

Assuming the flow file has a decent amount of records (thousands),
then you could do any of the following...

- Keep all the records in one flow file and use PublishKafkaRecord,
this will be most efficient for NiFi in terms of I/O and heap usage,
but only sending one record at a time to Kafka

- Split to one record per flow file, generally discouraged as it puts
significant stress on NiFI's repos and heap, but could publish
individual records in parallel once they reach PublisKafka

- Split to smaller batches, say you start with 10k records in the
original flow file then split to 5 flow files with 2k records each,
then PublishKafka with 5 concurrent tasks, but have to determine
whether this actually works out better than the first option

On Fri, Mar 1, 2019 at 12:47 PM Kumara M S, Hemantha (Nokia -
IN/Bangalore) <> wrote:
> Thanks Bryan, I got your point.  Yeah we could try PublishKafkaRecord, as in some of
other case we had already used PublishKafkaRecord(csv data to avro) to send out records.
> In the below mentioned use case we thought of sending out bunch of records(as we are
not doing anything with the data) at one shot instead of sending one record at a time.
> Thanks,
> Hemantha
> -----Original Message-----
> From: Bryan Bende <>
> Sent: Friday, March 1, 2019 7:52 PM
> To:
> Subject: Re: SplitRecord behaviour
> Hello,
> Flow files are not transferred until the session they came form is committed. So imagine
we periodically commit and some of the splits are transferred, then half way through a failure
is encountered, the entire original flow file will be reprocessed, producing some of the same
splits that were already send out. The way it is implemented now, it is either completely
successful, or not, but never partially successful producing duplicates.
> Based on the description of your flow with the three processors you mentioned, I wouldn't
bother using SplitRecord, just have ListenHttp
> -> PublishKafkaRecord. PublishKafkaRecorcd can be configured with the
> same reader and writer you were using in SplitRecord, and it will read each record and
send to Kafka, without having to produce unnecessary flow files.
> Thanks,
> Bryan
> On Fri, Mar 1, 2019 at 3:44 AM Kumara M S, Hemantha (Nokia -
> IN/Bangalore) <> wrote:
> >
> > Hi All,
> >
> > We have a use case where receiving huge json(file size might vary from 1GB to 50GB)
via http, convert in to XML(xml format is not fixed, any other format is fine) and send out
using Kafka. - here is the restriction is CPU & RAM usage requirement(once it is fixed,
it should handle all size files) should not getting changed based on incoming file size.
> >
> > We used ListenHTTP -->SplitRecord -->PublishKafa , but we have observed one
behaviour where SplitRecord is sending out data to PublishKafa only after whole FlowFile processing.
Is there any reason why did we design this way? Will it not be good if we send out splits
 to next processor after each configured records instead of all sending all splits at one
> >
> >
> > Regards,
> > Hemantha
> >

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