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Best Practices for Setting up Nifi in different modes

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Best Practices for Setting up Nifi in different modes

Hello everyone,

Please share the best practices for setting up Nifi in Cluster mode and Standalone mode.

Best Regards

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Re: Best Practices for Setting up Nifi in different modes

Master Guru
@spdvnz

Check out this other article:

https://community.hortonworks.com/articles/7882/hdfnifi-best-practices-for-setting-up-a-high-perfo.h... There is no difference between how a Node in a NiFi cluster and how a Standalone NiFi should be setup. BOth should follow the guidelines outlined in the above article.

As of NiFi 1.x and HDF 2.x, a NiFi cluster no longer has a NiFi Cluster Manager (NCM) and therefore all systems would be setup the same.

For NiFi 0.x and HDF 1.x versions the NCM does not process any data and therefore does not need the content repos, FlowFile repo or provenance repos. The NCM also does not require the same CPU horse power as the Nodes. The NCM can have a significant memory requirement depending on the number of attached nodes and the amount of processors added to the canvas. This is because all the processor and connection stats are reported to the NCM in heartbeats and stored in memory.

Thanks,

Matt

View solution in original post

1 REPLY 1
Highlighted

Re: Best Practices for Setting up Nifi in different modes

Master Guru
@spdvnz

Check out this other article:

https://community.hortonworks.com/articles/7882/hdfnifi-best-practices-for-setting-up-a-high-perfo.h... There is no difference between how a Node in a NiFi cluster and how a Standalone NiFi should be setup. BOth should follow the guidelines outlined in the above article.

As of NiFi 1.x and HDF 2.x, a NiFi cluster no longer has a NiFi Cluster Manager (NCM) and therefore all systems would be setup the same.

For NiFi 0.x and HDF 1.x versions the NCM does not process any data and therefore does not need the content repos, FlowFile repo or provenance repos. The NCM also does not require the same CPU horse power as the Nodes. The NCM can have a significant memory requirement depending on the number of attached nodes and the amount of processors added to the canvas. This is because all the processor and connection stats are reported to the NCM in heartbeats and stored in memory.

Thanks,

Matt

View solution in original post

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