Naveen, For throughput can you state what the desired events/sec/node would be for you and can you describe how the flowfile vs content vs prov repo is setup on the machine it is running on?
Thanks Joe On Wed, Nov 11, 2015 at 1:21 PM, Madhire, Naveen <[email protected]> wrote: > Thanks Mark. The workaround to have intermediate split text to split few > lines works well, as you said, the throughput is not quite there. I think it > serves our purpose as of now. > > > > From: Mark Payne <[email protected]> > Reply-To: "[email protected]" <[email protected]> > Date: Tuesday, November 10, 2015 at 7:12 PM > To: "[email protected]" <[email protected]> > Subject: Re: Memory Issues on Split Text > > Naveen, > > There is a ticket [1] that will make this work more cleanly so that we can > use SplitText to split a large > file into millions of FlowFiles. Right now, as you noted you will end up > running out of memory. There are > a few possible solutions that you can use. > > If you need to split each line into a separate FlowFile, the easiest way is > to use two SplitText processors. > The first would be configured with a Line Split Count of say 10,000. Then, > the "splits" relationship is routed > to a second SplitText processor with the Line Split Count set to 1. This > prevents the processor from holding > those millions of FlowFiles in memory. The only downside here is that if you > create a FlowFile for every single > message, your throughput will not be quite as good. > > The next approach is to just send the entire 2 GB FlowFile to PutKafka and > set the Message Delimiter to "\n". > This will send each line in the FlowFile to Kafka as a separate message. The > down side here is that if you have > sent say 1 million messages to Kafka and then NiFi is restarted, it doesn't > know that those 1 million messages have > been sent, so you will end up sending all of the data again and will > duplicate a lot of the messages. > > The third approach is a hybrid of the two. You can use SplitText to split > the FlowFile into 10,000 lines each. Then, > instead of sending to another SplitText, you can send the "splits" > relationship to PutKafka with a Message Delimiter > of "\n". This way, you will still get great throughput by not splitting each > FlowFile into millions of FlowFiles, but you will > avoid duplicating millions of messages (you'll duplicate at the very most > 10,000 messages in this example). > > So you can use any of these approaches. You just have to consider the pro's > and con's of each and decide which > trade-offs you want to make. > > Thanks > -Mark > > > [1] https://issues.apache.org/jira/browse/NIFI-1008 > > > > > > On Nov 10, 2015, at 5:28 PM, Madhire, Naveen <[email protected]> > wrote: > > Hi, > > I am reading a 2 GB file from local and putting the data into a Kafka topic. > > Since GetFile only creates one flow file per file, I am making use of > SplitText processor to split the file into one flow file per line before > inserting the data into a Kafka topic. > I am seeing a lot of “GC Overhead limit exceeded errors” on SplitText > processor. I am running Nifi on a single linux server with 16 GB memory. > > Is this the right approach of reading and putting into Kafka? > Or there is any better approach? > > Thanks, > Naveen > > > > ________________________________ > The information contained in this e-mail is confidential and/or proprietary > to Capital One and/or its affiliates and may only be used solely in > performance of work or services for Capital One. The information transmitted > herewith is intended only for use by the individual or entity to which it is > addressed. If the reader of this message is not the intended recipient, you > are hereby notified that any review, retransmission, dissemination, > distribution, copying or other use of, or taking of any action in reliance > upon this information is strictly prohibited. If you have received this > communication in error, please contact the sender and delete the material > from your computer. > > > > ________________________________ > > The information contained in this e-mail is confidential and/or proprietary > to Capital One and/or its affiliates and may only be used solely in > performance of work or services for Capital One. The information transmitted > herewith is intended only for use by the individual or entity to which it is > addressed. If the reader of this message is not the intended recipient, you > are hereby notified that any review, retransmission, dissemination, > distribution, copying or other use of, or taking of any action in reliance > upon this information is strictly prohibited. If you have received this > communication in error, please contact the sender and delete the material > from your computer.
