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FetchDistributedMapCache Retrieving Old Token Instead of New One in NiFi Workflow

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New Contributor

Hello Cloudera Community,

I am currently working with a NiFi workflow that includes a PutDistributedMapCache (version 1.19.1) processor with a Cache Update Strategy set to "Replace if Present". This processor sets the value for the key "token". Additionally, I am using a DistributedMapCacheServer with a First In, First Out (FIFO) Eviction Strategy and a Maximum Cache Entries setting of 500.

In my workflow, there are four subprocess groups, each processing 185 flowfiles. Each group has a Wait processor that ensures the previous group has finished processing its files before starting its own processing. Following these sub process groups, I have a FetchDistributedMapCache processor to fetch the Cache Entry Identifier "token".

However, I am encountering an issue where several files are fetching the old "token" at the FetchDistributedMapCache step instead of the new token. Could anyone provide insights or suggestions on why this might be happening and how to resolve this issue? Thanks in advance for your help!

3 REPLIES 3

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Community Manager

@ShannThomson Welcome to the Cloudera Community!

To help you get the best possible solution, I have tagged our NiFi experts @SAMSAL and @cotopaul  who may be able to assist you further.

Please keep us updated on your post, and we hope you find a satisfactory solution to your query.


Regards,

Diana Torres,
Community Moderator


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Explorer

Hi,

I'm having the same problem for my project. Have you found a solution for this? If you have, could you kindly let me know the solution? It would help me a lot for my project.

Thanks in advance!

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Master Mentor

@Adhitya This is a rather old post.  

Can your provide details on your specific setup (processors and configurations including scheduling) used,  info around your data and what you expect versus what you are seeing?

Is your NiFi a cluster setup or standalone?
How is source data ingested into your NiFi for this dataflow?

Typically issues like this are related to dataflow design, but there is not enough info here to reproduce or make suggestions yet.

Thanks,
Matt